diff --git a/CHANGELOG.md b/CHANGELOG.md
index 88deadb0..5a31cdcb 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -6,6 +6,20 @@ The format is based on Keep a Changelog.
 
 ## Unreleased
 
+### Agents and API
+
+- updated the Pi integration for the current `earendil-works/pi` packages and
+  release feed, registered mere.run through Pi's native dynamic-provider API,
+  and added a reusable package under `integrations/pi`.
+- made `/v1/models` self-describing with additive task, tool-call, reasoning,
+  modality, context/output-limit, and OpenAI-dialect metadata. Pi now exposes
+  only models whose running API lane supports tools, maps model-specific
+  thinking levels, and honors Muse reasoning effort.
+- moved served-model capabilities into typed managed-model catalog profiles.
+  API request validation, `/v1/models`, agent eligibility, and Pi's offline
+  fallback now consume the same source of truth, with runtime limit settings
+  applied only when describing the active server.
+
 ### Music
 
 - accelerated MiniMax Music 3 on Apple Silicon with a reachable 16,385-row
diff --git a/README.md b/README.md
index aec19a04..7bdaea92 100644
--- a/README.md
+++ b/README.md
@@ -289,6 +289,10 @@ swift run mere.run model capabilities --recommended
 # Choose guided, bring-your-own-agent, or manual setup
 swift run mere.run setup
 
+# Or install Pi and launch it against a self-describing local provider
+swift run mere.run agent install-pi
+swift run mere.run agent start
+
 # Pull a Hugging Face-backed model into the local model store
 swift run mere.run model pull image-zimage-nano
 swift run mere.run model pull image-zimage-nano --preflight --json
@@ -1015,6 +1019,11 @@ The public OSS build keeps local-first behavior by default and requires explicit
   model
 - `mere.run api serve` can bind to loopback without auth, but non-loopback hosts require `--api-key` or `MERERUN_API_KEY`
 - the OpenAI-compatible chat and embedding routes require `Content-Type: application/json`, support `--rate-limit-per-minute` for basic abuse control, decode the common OpenAI request shapes, and reject unsupported high-impact fields before generation
+- `/v1/models` adds task, tool-call, reasoning, modality, limit, and
+  compatibility metadata. The bundled Pi provider consumes these fields and
+  exposes only tool-capable chat models instead of guessing from model names.
+  Those fields project from typed managed-model catalog profiles; aliases and
+  active runtime limit overrides are layered on when the server responds.
 - API LoRA adapters are operator-controlled with `--lora`; it accepts a
   verified installed adapter catalog id or a local path, while per-request LoRA
   paths are rejected
diff --git a/Sources/MereRunCLI/Commands/APIServeCommand.swift b/Sources/MereRunCLI/Commands/APIServeCommand.swift
index f9fc9996..c4010d5b 100644
--- a/Sources/MereRunCLI/Commands/APIServeCommand.swift
+++ b/Sources/MereRunCLI/Commands/APIServeCommand.swift
@@ -547,11 +547,27 @@ struct APIEngineCapabilities: Equatable, Sendable {
     var supportsLogprobs: Bool = false
     var supportsProviderThinkingControls: Bool = false
 
-    static let localText = APIEngineCapabilities()
+    static func catalog(_ profile: ManagedModelAPIProfile) -> APIEngineCapabilities {
+        APIEngineCapabilities(
+            supportsRawProxy: profile.supportsRawProxy,
+            supportsTools: profile.toolCall,
+            supportsToolChoice: profile.supportsToolChoice,
+            supportsDeveloperRole: profile.compatibility.supportsDeveloperRole,
+            supportsStructuredOutputs: profile.structuredOutput,
+            supportsReasoningEffort: profile.compatibility.supportsReasoningEffort,
+            supportsMaxCompletionTokens: profile.compatibility.maxTokensField == .maxCompletionTokens,
+            supportsUsageInStreaming: profile.compatibility.supportsUsageInStreaming,
+            supportsVisionContentParts: profile.inputModalities.contains(.image),
+            supportsStrictMode: profile.compatibility.supportsStrictMode,
+            supportsStopSequences: profile.supportsStopSequences,
+            supportsSeed: profile.supportsSeed,
+            supportsPenalties: profile.supportsPenalties,
+            supportsLogprobs: profile.supportsLogprobs,
+            supportsProviderThinkingControls: profile.supportsProviderThinkingControls
+        )
+    }
 
-    static let localTextWithStopSequences = APIEngineCapabilities(
-        supportsStopSequences: true
-    )
+    static let localText = APIEngineCapabilities()
 
     static let localTextWithStructuredJSON = APIEngineCapabilities(
         supportsStructuredOutputs: true
@@ -562,56 +578,11 @@ struct APIEngineCapabilities: Equatable, Sendable {
         supportsToolChoice: true
     )
 
-    static let localTextWithToolsAndStopSequences = APIEngineCapabilities(
-        supportsTools: true,
-        supportsToolChoice: true,
-        supportsStopSequences: true
-    )
-
-    static let localTextWithToolsAndStructuredJSON = APIEngineCapabilities(
-        supportsTools: true,
-        supportsToolChoice: true,
-        supportsStructuredOutputs: true
-    )
-
     static let localTextWithToolsAndVision = APIEngineCapabilities(
         supportsTools: true,
         supportsToolChoice: true,
         supportsVisionContentParts: true
     )
-
-    static let localTextWithToolsVisionAndReasoning = APIEngineCapabilities(
-        supportsTools: true,
-        supportsToolChoice: true,
-        supportsReasoningEffort: true,
-        supportsVisionContentParts: true
-    )
-
-    static let localTextWithToolsVisionAndStructuredJSON = APIEngineCapabilities(
-        supportsTools: true,
-        supportsToolChoice: true,
-        supportsStructuredOutputs: true,
-        supportsVisionContentParts: true,
-        supportsStrictMode: false
-    )
-
-    static let rawProxy = APIEngineCapabilities(
-        supportsRawProxy: true,
-        supportsTools: true,
-        supportsToolChoice: true,
-        supportsDeveloperRole: true,
-        supportsStructuredOutputs: true,
-        supportsReasoningEffort: true,
-        supportsMaxCompletionTokens: true,
-        supportsUsageInStreaming: true,
-        supportsVisionContentParts: true,
-        supportsStrictMode: false,
-        supportsStopSequences: true,
-        supportsSeed: true,
-        supportsPenalties: true,
-        supportsLogprobs: true,
-        supportsProviderThinkingControls: true
-    )
 }
 
 struct APIHealthStatus: Codable, Equatable, Sendable {
@@ -1241,6 +1212,78 @@ enum APIServerContract {
         )
     }
 
+    static func chatModel(
+        id: String,
+        name: String,
+        profile: ManagedModelAPIProfile,
+        contextWindow: Int,
+        maximumOutputTokens: Int,
+        createdAt: Date = Date()
+    ) -> OpenAIModel {
+        let compatibility = profile.compatibility
+        let thinkingLevels = profile.thinkingLevels.isEmpty
+            ? nil
+            : profile.thinkingLevels.map(\.rawValue)
+        let thinkingLevelMap = profile.thinkingLevelMap.isEmpty
+            ? nil
+            : Dictionary(uniqueKeysWithValues: profile.thinkingLevelMap.map {
+                ($0.key.rawValue, $0.value.rawValue)
+            })
+
+        return OpenAIModel(
+            id: id,
+            object: "model",
+            created: Int(createdAt.timeIntervalSince1970),
+            owned_by: "mere.run",
+            name: name,
+            task: profile.task.rawValue,
+            reasoning: profile.reasoning,
+            thinking_levels: thinkingLevels,
+            tool_call: profile.toolCall,
+            structured_output: profile.structuredOutput,
+            modalities: OpenAIModelModalities(
+                input: profile.inputModalities.map(\.rawValue),
+                output: profile.outputModalities.map(\.rawValue)
+            ),
+            limit: OpenAIModelLimit(context: contextWindow, output: maximumOutputTokens),
+            openai_compat: OpenAIModelCompatibility(
+                supports_store: compatibility.supportsStore,
+                supports_developer_role: compatibility.supportsDeveloperRole,
+                supports_reasoning_effort: compatibility.supportsReasoningEffort,
+                supports_usage_in_streaming: compatibility.supportsUsageInStreaming,
+                supports_finish_reason: compatibility.supportsFinishReason,
+                max_tokens_field: compatibility.maxTokensField.rawValue,
+                supports_strict_mode: compatibility.supportsStrictMode,
+                thinking_format: compatibility.thinkingFormat?.rawValue,
+                thinking_level_map: thinkingLevelMap,
+                requires_reasoning_content_on_assistant_messages: compatibility
+                    .requiresReasoningContentOnAssistantMessages
+            )
+        )
+    }
+
+    static func companionModel(
+        id: String,
+        profile: ManagedModelAPIProfile,
+        createdAt: Date = Date()
+    ) -> OpenAIModel {
+        return OpenAIModel(
+            id: id,
+            object: "model",
+            created: Int(createdAt.timeIntervalSince1970),
+            owned_by: "mere.run",
+            name: id,
+            task: profile.task.rawValue,
+            reasoning: profile.reasoning,
+            tool_call: profile.toolCall,
+            structured_output: profile.structuredOutput,
+            modalities: OpenAIModelModalities(
+                input: profile.inputModalities.map(\.rawValue),
+                output: profile.outputModalities.map(\.rawValue)
+            )
+        )
+    }
+
     static func embeddingTexts(from request: OpenAIEmbeddingRequest) throws -> [String] {
         guard !request.model.trimmingCharacters(in: .whitespacesAndNewlines).isEmpty else {
             throw APIRequestValidationError.invalidField("model", "must not be empty")
@@ -2430,7 +2473,8 @@ enum APIServerContract {
         fallbackLoraPath: String?,
         contextSize: Int,
         capabilities: APIEngineCapabilities = .localText,
-        servedModelID: String? = nil
+        servedModelID: String? = nil,
+        apiProfile: ManagedModelAPIProfile? = nil
     ) throws -> ChatRequest {
         guard !openaiRequest.messages.isEmpty else {
             throw APIRequestValidationError.invalidField("messages", "must contain at least one message")
@@ -2476,11 +2520,18 @@ enum APIServerContract {
         // R1-style lanes degenerate without reasoning; their published top_k
         // applies only when the client did not set explicit sampling.
         let laneModelID = servedModelID ?? ""
+        let resolvedAPIProfile = apiProfile
+            ?? servedModelID.flatMap { ManagedModelCatalog.apiProfile(for: $0) }
         let recommendedSampling = Q35Resources.recommendedSampling(forModelId: laneModelID)
         let isLaguna = LagunaResources.handles(modelSpec: laneModelID)
         let usesExplicitSampling = openaiRequest.temperature != nil
             || openaiRequest.top_p != nil
             || openaiRequest.min_p != nil
+        let reasoningEffort = try reasoningEffort(
+            from: openaiRequest.reasoning_effort,
+            capabilities: capabilities,
+            profile: resolvedAPIProfile
+        )
 
         return ChatRequest(
             messages: messages,
@@ -2499,7 +2550,10 @@ enum APIServerContract {
             minP: openaiRequest.min_p == nil && isLaguna
                 ? LagunaResources.recommendedMinP
                 : minP,
-            showThinking: requiresJSON ? false : Q35Resources.thinkingDefault(forModelId: laneModelID),
+            reasoningEffort: reasoningEffort,
+            showThinking: requiresJSON
+                ? false
+                : resolvedAPIProfile?.thinkingLevels == [.high],
             lora: lora,
             requiresJSON: requiresJSON,
             tools: tools,
@@ -2802,6 +2856,28 @@ enum APIServerContract {
         return try validateMaxTokens(maxCompletionTokens ?? maxTokens, contextSize: contextSize)
     }
 
+    private static func reasoningEffort(
+        from rawValue: String?,
+        capabilities: APIEngineCapabilities,
+        profile: ManagedModelAPIProfile?
+    ) throws -> Double? {
+        guard let rawValue else { return nil }
+        guard !capabilities.supportsRawProxy else { return nil }
+        let normalized = rawValue.trimmingCharacters(in: .whitespacesAndNewlines).lowercased()
+        guard let level = ManagedModelThinkingLevel(rawValue: normalized),
+              let strength = profile?.reasoningEffortStrengths[level] else {
+            let supportedLevels = ManagedModelThinkingLevel.allCases
+                .filter { profile?.reasoningEffortStrengths[$0] != nil }
+                .map(\.rawValue)
+                .joined(separator: ", ")
+            throw APIRequestValidationError.invalidField(
+                "reasoning_effort",
+                "must be one of \(supportedLevels)"
+            )
+        }
+        return strength
+    }
+
     static func acceptsJSONContentType(_ rawValue: String?) -> Bool {
         guard let mediaType = rawValue?
             .split(separator: ";", maxSplits: 1, omittingEmptySubsequences: true)
@@ -3810,7 +3886,7 @@ actor CodeGenServer {
         let includeLoopbackArtifactModels = APIVFXArtifactRoutePolicy.allows(
             remoteAddress: remoteAddress
         )
-        var models = try await pool.modelsResponse()
+        var models = try await pool.modelsResponse(serverContextSize: contextSize)
         if !includeLoopbackArtifactModels {
             models.data.removeAll { APIVFXArtifactRoutePolicy.modelIDs.contains($0.id) }
         }
@@ -3818,12 +3894,13 @@ actor CodeGenServer {
             includeLoopbackArtifactModels: includeLoopbackArtifactModels
         )
             where !models.data.contains(where: { $0.id == modelID }) {
+            guard let profile = ManagedModelCatalog.apiProfile(for: modelID) else {
+                continue
+            }
             models.data.append(
-                OpenAIModel(
+                APIServerContract.companionModel(
                     id: modelID,
-                    object: "model",
-                    created: Int(Date().timeIntervalSince1970),
-                    owned_by: "mere.run"
+                    profile: profile
                 )
             )
         }
diff --git a/Sources/MereRunCLI/Commands/AgentCommand.swift b/Sources/MereRunCLI/Commands/AgentCommand.swift
index f8450133..15c3e4e0 100644
--- a/Sources/MereRunCLI/Commands/AgentCommand.swift
+++ b/Sources/MereRunCLI/Commands/AgentCommand.swift
@@ -240,13 +240,13 @@ struct AgentOnboard: AsyncParsableCommand {
         }
 
         let startable = MereRunAgentModelCatalog.fallbackStartableRecommendation(on: machine)
-        let selectedAgentID = startable?.id ?? AgentModelResources.qwen35NineBModelId
+        let selectedAgentID = startable?.id ?? Q35Resources.ornith9BModelId
         print("\nAgent readiness")
         if let startable {
             print("  Recommended setup agent: \(startable.id) (\(startable.displayName)).")
             print("  Start a guided session with: \(CLICommandDisplay.command("agent start --model \(selectedAgentID)"))")
             if startable.id == DeepseekV4FlashResources.defaultModelId {
-                print("  DeepSeek V4 Flash is the preferred 96 GB+ setup-agent tier; smaller Qwen agents are alternatives, not upgrades.")
+                print("  DeepSeek V4 Flash is the preferred 96 GB+ setup-agent tier; smaller tool-capable native agents are alternatives, not upgrades.")
             }
         }
         if let codeReport = reports.first(where: { $0.spec.id == CodeGenResources.defaultModelId }) {
@@ -362,7 +362,12 @@ struct AgentOnboard: AsyncParsableCommand {
         guard let recommendation = SetupAgentRuntime.recommendation(forManagedModelID: normalized) else {
             throw ValidationError("Unsupported Pi provider model: \(modelID)")
         }
-        return SetupAgentRuntime.providerModel(for: recommendation)
+        guard recommendation.isStartableByMereRun else {
+            throw ValidationError(
+                "Pi requires a tool-capable chat model; \(modelID) is only available through the text-code API lane."
+            )
+        }
+        return try SetupAgentRuntime.providerModel(for: recommendation)
     }
 }
 
diff --git a/Sources/MereRunCLI/Commands/ModelCapabilitiesCommand.swift b/Sources/MereRunCLI/Commands/ModelCapabilitiesCommand.swift
index e92a6945..c623cba2 100644
--- a/Sources/MereRunCLI/Commands/ModelCapabilitiesCommand.swift
+++ b/Sources/MereRunCLI/Commands/ModelCapabilitiesCommand.swift
@@ -86,7 +86,7 @@ struct ModelCapabilities: ParsableCommand {
             print("  \(CLICommandDisplay.command("agent start --model \(agent.id)"))")
             print("  \(agent.displayName): \(agent.summary)")
             if agent.id == DeepseekV4FlashResources.defaultModelId {
-                print("  note: DeepSeek V4 Flash is the preferred 96 GB+ setup-agent tier; smaller Qwen agents are lower-memory alternatives, not upgrades.")
+                print("  note: DeepSeek V4 Flash is the preferred 96 GB+ setup-agent tier; smaller tool-capable native agents are lower-memory alternatives, not upgrades.")
             }
         }
 
diff --git a/Sources/MereRunCLI/Commands/SetupCommand.swift b/Sources/MereRunCLI/Commands/SetupCommand.swift
index e94995ba..ccca53de 100644
--- a/Sources/MereRunCLI/Commands/SetupCommand.swift
+++ b/Sources/MereRunCLI/Commands/SetupCommand.swift
@@ -196,7 +196,7 @@ struct Setup: AsyncParsableCommand {
         switch agentModel {
         case .small:
             print("  Unavailable.")
-            print("  Qwen3.5 9B setup agent requires at least 16 GB unified memory.")
+            print("  Ornith 1.0 9B setup agent requires at least 16 GB unified memory.")
         case .tier:
             print("  Unavailable.")
             print("  No local agent tier is supported on this machine.")
@@ -461,30 +461,26 @@ struct SetupAgentRuntime {
     }
 
     static func runtime(for recommendation: MereRunAgentModelRecommendation) throws -> SetupAgentRuntime {
+        guard recommendation.isStartableByMereRun else {
+            throw ValidationError(
+                "\(recommendation.displayName) cannot be used with Pi because its API lane does not support tool calls."
+            )
+        }
         guard let modelID = recommendation.managedModelID,
               let spec = ManagedModelCatalog.spec(for: modelID) else {
             throw ValidationError("\(recommendation.displayName) is not managed by mere.run yet.")
         }
-        let engine: APIEngine
-        switch recommendation.servingEngine {
-        case .textCode:
-            engine = .textCode
-        case .textChatGemma4:
-            engine = .textChatGemma4
-        case .textChatQ36:
-            engine = .textChatQ36
-        case .textChatQ35:
-            engine = .textChatQ36
-        case .deepseekV4Flash:
-            engine = .textChatDeepseekV4Flash
-        case .sourceConfigured:
-            throw ValidationError("\(recommendation.displayName) requires an external local model before it can be started.")
+        guard let runtimeServingEngine = spec.apiProfile?.servingEngine,
+              let engine = APIEngine(rawValue: runtimeServingEngine.rawValue) else {
+            throw ValidationError(
+                "\(recommendation.displayName) does not have a cataloged local serving engine."
+            )
         }
         return SetupAgentRuntime(
             recommendation: recommendation,
             spec: spec,
             engine: engine,
-            providerModel: providerModel(for: recommendation)
+            providerModel: try providerModel(for: recommendation)
         )
     }
 
@@ -495,32 +491,19 @@ struct SetupAgentRuntime {
         return try runtime(for: recommendation)
     }
 
-    static func providerModel(for recommendation: MereRunAgentModelRecommendation) -> PiProviderModel {
-        // DeepSeek V4 Flash has a specific Pi compat profile (DSML thinking
-        // format, reasoning effort, etc.) documented in the ds4 README.
-        if recommendation.servingEngine == .deepseekV4Flash {
-            return .deepseekV4Flash
+    static func providerModel(
+        for recommendation: MereRunAgentModelRecommendation
+    ) throws -> PiProviderModel {
+        guard let modelID = recommendation.managedModelID,
+              let profile = ManagedModelCatalog.apiProfile(for: modelID) else {
+            throw ValidationError(
+                "\(recommendation.displayName) does not have a cataloged API profile."
+            )
         }
-        return PiProviderModel(
+        return try PiProviderModel(
             id: recommendation.id,
             name: "\(recommendation.displayName) (mere.run)",
-            contextWindow: contextWindow(for: recommendation),
-            maxTokens: 4096
+            profile: profile
         )
     }
-
-    private static func contextWindow(for recommendation: MereRunAgentModelRecommendation) -> Int {
-        switch recommendation.servingEngine {
-        case .textChatGemma4:
-            return Gemma4Resources.defaultContextLength
-        case .textChatQ36, .textChatQ35:
-            return Q35Resources.defaultContextLength
-        case .deepseekV4Flash:
-            return DeepseekV4FlashResources.defaultContextLength
-        case .sourceConfigured:
-            return 32768
-        case .textCode:
-            return 32768
-        }
-    }
 }
diff --git a/Sources/MereRunCLI/Guides/agent-install-pi.md b/Sources/MereRunCLI/Guides/agent-install-pi.md
index 898bc538..1a01325f 100644
--- a/Sources/MereRunCLI/Guides/agent-install-pi.md
+++ b/Sources/MereRunCLI/Guides/agent-install-pi.md
@@ -2,7 +2,10 @@
 
 ## Purpose
 
-Install the latest Pi coding-agent release so mere.run can launch a guided local setup agent. Auto-install uses the published macOS release assets; on Linux, install Pi separately and pass `--pi-path` or put `pi` on PATH.
+Install the latest Pi coding-agent release from the current
+`earendil-works/pi` upstream so mere.run can launch a guided local setup agent.
+Auto-install uses the published macOS release assets; on Linux, install Pi
+separately and pass `--pi-path` or put `pi` on PATH.
 
 ## Required Models
 
@@ -23,7 +26,8 @@ mere.run agent install-pi --help
 
 - Run before `agent start` on macOS when Pi is not on PATH or not managed by mere.run.
 - Use `--force` when the installed Pi binary is corrupt or outdated.
-- Pair with `agent onboard --configure-pi` to register the local provider.
+- Pair with `agent onboard --configure-pi` to register a native Pi provider
+  that discovers tool-capable models from mere.run.
 
 ## Examples
 
@@ -52,3 +56,4 @@ mere.run agent install-pi --force
 
 - https://github.com/sawfwair/mere-run/blob/main/Sources/MereRunCLI/Commands/AgentCommand.swift
 - https://github.com/sawfwair/mere-run/blob/main/Sources/MereRunCLI/Support/PiAgentIntegration.swift
+- https://github.com/earendil-works/pi
diff --git a/Sources/MereRunCLI/Guides/agent-onboard.md b/Sources/MereRunCLI/Guides/agent-onboard.md
index 8b7c9288..d3a5b6ba 100644
--- a/Sources/MereRunCLI/Guides/agent-onboard.md
+++ b/Sources/MereRunCLI/Guides/agent-onboard.md
@@ -8,12 +8,10 @@ Summarize this Mac's model capabilities and optionally prepare the Pi coding-age
 
 No model is required to print readiness. Optional model pulls/configuration
 should use the recommended setup-agent tier; on 96 GB+ Apple Silicon Macs that
-is `text-agent-deepseek-v4-flash`. Smaller Qwen agent models are lower-memory
-or comparison alternatives. `text-code-north-mini` is available for native
-GGUF coding-agent experiments, `text-agent-ornith-35b` is available for larger
-native GGUF Ornith evals, and `text-agent-ornith-9b` is available for native
-Qwen-family MLX/OptiQ coding-agent experiments. `text-agent-ornith-35b-mlx`
-is the local converted native MLX Q4 lane for larger Ornith evals.
+is `text-agent-deepseek-v4-flash`. Tool-capable native chat models such as
+`text-agent-ornith-9b` are lower-memory alternatives. GGUF models served by
+the `text-code` engine remain useful for direct coding experiments and evals,
+but that API lane rejects tool calls and is not exposed to Pi.
 
 ## Install And Check
 
@@ -38,10 +36,6 @@ mere.run agent onboard --help
 - Run plain `agent onboard` first; it is informational.
 - Use `--install-pi` before `agent start` if Pi is not already installed.
 - Use `--configure-pi --model <id>` when Pi should call a local mere.run API provider.
-- For North Mini Code, pull `text-code-north-mini`, start `api serve --engine text-code`,
-  then use `--configure-pi --model text-code-north-mini --host <host> --port <port>`.
-- For Ornith 35B, pull `text-agent-ornith-35b`, start `api serve --engine text-code --model text-agent-ornith-35b`,
-  then use `--configure-pi --model text-agent-ornith-35b --host <host> --port <port>`.
 - For Ornith 35B MLX, install `text-agent-ornith-35b-mlx`, start `api serve --engine text-chat-q36 --model text-agent-ornith-35b-mlx`,
   then use `--configure-pi --model text-agent-ornith-35b-mlx --host <host> --port <port>`.
 - For Ornith, pull `text-agent-ornith-9b`, start `api serve --engine text-chat-q36 --model text-agent-ornith-9b`,
@@ -57,16 +51,6 @@ mere.run agent onboard
 mere.run agent onboard --install-pi --configure-pi --model text-agent-deepseek-v4-flash
 ```
 
-```bash
-mere.run model pull text-code-north-mini
-mere.run agent onboard --configure-pi --model text-code-north-mini --port 8080
-```
-
-```bash
-mere.run model pull text-agent-ornith-35b
-mere.run agent onboard --configure-pi --model text-agent-ornith-35b --port 8080
-```
-
 ```bash
 mere.run model pull text-agent-ornith-9b
 mere.run agent onboard --configure-pi --model text-agent-ornith-9b --port 8080
@@ -81,7 +65,8 @@ mere.run agent onboard --configure-pi --model text-agent-ornith-9b --port 8080
 
 ## Troubleshooting
 
-- Provider model unsupported: choose a model printed by onboarding.
+- Provider model unsupported: choose a tool-capable model printed as startable
+  by onboarding; `text-code` models cannot run Pi tools.
 - Pi install fails: rerun with network access and without `--quiet`.
 - No recommended downloads: use manual setup or a local model path.
 
diff --git a/Sources/MereRunCLI/Guides/agent-start.md b/Sources/MereRunCLI/Guides/agent-start.md
index 159de0b6..e5d33519 100644
--- a/Sources/MereRunCLI/Guides/agent-start.md
+++ b/Sources/MereRunCLI/Guides/agent-start.md
@@ -6,7 +6,10 @@ Start Pi against a local mere.run setup-agent API server. This is the guided "he
 
 ## Required Models
 
-Use this machine's supported setup-agent tier. On 96 GB+ Apple Silicon Macs, `text-agent-deepseek-v4-flash` is the preferred managed setup agent. Smaller Qwen, North Mini Code, and Ornith 35B models are lower-memory or comparison alternatives, not upgrades from DeepSeek V4 Flash. On Linux, provide Pi with `--pi-path` or PATH; auto-install uses macOS release assets.
+Use this machine's supported tool-capable setup-agent tier. On 96 GB+ Apple
+Silicon Macs, `text-agent-deepseek-v4-flash` is the preferred managed setup
+agent. On Linux, provide Pi with `--pi-path` or PATH; auto-install uses macOS
+release assets.
 
 ## Install And Check
 
@@ -33,12 +36,10 @@ mere.run status
 - Run `model capabilities --recommended` or `agent onboard` first and use the recommended setup-agent id.
 - Pull the selected model before `agent start`.
 - Use `--skip-server` only when you already started a compatible local API server.
-- Use `agent start --model text-code-north-mini` to compare North Mini Code
-  through the native GGUF code runtime.
-- Use `agent start --model text-agent-ornith-35b` to compare the larger Ornith
-  GGUF coding-agent target through the same native `text-code` runtime.
 - Use `agent start --model text-agent-ornith-35b-mlx` to compare the locally
   converted Ornith 35B MLX target through the native Qwen-family runtime.
+- Use `text code` or `api serve --engine text-code` for GGUF coding models;
+  that API lane intentionally rejects Pi tool calls.
 - On Linux, provide an existing Pi binary with `--pi-path` or PATH before starting.
 - Run `status` when you need to confirm the local server and served model.
 - Keep the default prompt unless the user has a specific setup goal.
@@ -57,13 +58,14 @@ mere.run agent start \
 
 ## Iteration Tips
 
-- Use DeepSeek V4 Flash on 96 GB+ Macs; start with a smaller Qwen agent only on lower-memory machines or when comparing behavior.
+- Use DeepSeek V4 Flash on 96 GB+ Macs; start with a smaller tool-capable native
+  agent on lower-memory machines or when comparing behavior.
 - Check the server log path printed to stderr when startup hangs.
 - Re-run onboarding after model pulls or provider changes.
 
 ## Troubleshooting
 
-- Model unsupported: choose a supported model from `agent onboard`.
+- Model unsupported: choose a tool-capable startable model from `agent onboard`.
 - Model missing: run `mere.run model pull <id>`.
 - Pi missing: run `mere.run agent install-pi` on macOS, or pass `--pi-path` / put `pi` on PATH on Linux.
 - Health check times out: verify host/port and local API logs.
diff --git a/Sources/MereRunCLI/Guides/api-serve.md b/Sources/MereRunCLI/Guides/api-serve.md
index f206ce5f..f5d7c2f7 100644
--- a/Sources/MereRunCLI/Guides/api-serve.md
+++ b/Sources/MereRunCLI/Guides/api-serve.md
@@ -133,7 +133,13 @@ download route.
 - Request `model` resolves by runtime alias, then curated catalog id, then the
   startup default from `--engine`/`--model`.
 - `/v1/models` returns installed API-capable chat catalog ids, aliases, and
-  installed native embedding, image, TTS, and ASR sidecar model ids.
+  installed native sidecars. Mere-specific additive fields describe each
+  model's task, tool-call and reasoning support, thinking levels, input/output
+  modalities, context/output limits, and OpenAI compatibility dialect so agent
+  harnesses do not have to guess from an id.
+- Managed-model metadata comes from the typed catalog API profile. The running
+  server overlays aliases and configured context/output defaults; explicit
+  uncataloged model paths use a conservative profile for their serving engine.
 - The embedding, image/image-edit, TTS, and ASR endpoints each retain one
   bounded most-recently-used runtime. Their autonomous idle timers default to 300
   seconds and re-read managed `pinned`/`ttlSeconds` settings while idle. Active
diff --git a/Sources/MereRunCLI/Guides/setup.md b/Sources/MereRunCLI/Guides/setup.md
index c96fc2e7..01ee9563 100644
--- a/Sources/MereRunCLI/Guides/setup.md
+++ b/Sources/MereRunCLI/Guides/setup.md
@@ -8,10 +8,10 @@ Choose a guided, bring-your-own-agent, or manual setup path for a new mere.run i
 
 No model is required to view the plan. Agent setup selects this machine's
 supported tier; on 96 GB+ machines that is `text-agent-deepseek-v4-flash`.
-Smaller Qwen agent models are lower-memory or comparison alternatives, not
-upgrades from DeepSeek V4 Flash. `text-code-north-mini` can be pulled for
-native GGUF coding-agent experiments through the same `text-code` runtime;
-`text-agent-ornith-35b` is the larger explicit Ornith GGUF eval target.
+The small tier is the tool-capable native `text-agent-ornith-9b`. GGUF models
+such as North Mini and Ornith 35B remain available for direct coding
+experiments, but the `text-code` API lane rejects tool calls and cannot host
+the Pi setup agent.
 
 ## Install And Check
 
@@ -39,9 +39,7 @@ mere.run model capabilities --recommended
 - Use `--mode manual --dry-run` for docs or scripts.
 - Use agent mode only with a supported local runtime and model. Prefer `--agent-model tier` unless the user asks for a smaller comparison model.
 - On Linux, provide Pi with `--pi-path` or put `pi` on PATH; auto-install uses macOS release assets.
-- Use `--agent-model small` for the smallest setup model, or pull
-  `text-code-north-mini` or `text-agent-ornith-35b` manually when comparing
-  coding models against Qwen.
+- Use `--agent-model small` for the smallest tool-capable setup model.
 
 ## Examples
 
diff --git a/Sources/MereRunCLI/Support/PiAgentIntegration.swift b/Sources/MereRunCLI/Support/PiAgentIntegration.swift
index 29b012a1..9fbe029d 100644
--- a/Sources/MereRunCLI/Support/PiAgentIntegration.swift
+++ b/Sources/MereRunCLI/Support/PiAgentIntegration.swift
@@ -13,19 +13,35 @@ struct PiAgentInstallResult {
     let binaryURL: URL
 }
 
+enum PiProviderModelError: LocalizedError {
+    case invalidCatalogProfile(String)
+
+    var errorDescription: String? {
+        switch self {
+        case .invalidCatalogProfile(let modelID):
+            return "Catalog model '\(modelID)' does not define a complete chat API profile."
+        }
+    }
+}
+
 struct PiProviderModel {
     let id: String
     let name: String
     let contextWindow: Int
     let maxTokens: Int
+    /// Input modalities Pi can represent for this model.
+    let inputModalities: [String]
     /// Whether the model supports a separate "thinking" / reasoning channel.
     let reasoning: Bool
+    /// Whether the API/model pair can execute Pi's function tools.
+    let toolCall: Bool
     /// Provider-level OpenAI-compat flags. Matches the shape pi-coding-agent's
     /// provider catalog expects (see the ds4 README "For Pi" section).
     let supportsStore: Bool
     let supportsDeveloperRole: Bool
     let supportsReasoningEffort: Bool
     let supportsUsageInStreaming: Bool
+    let supportsFinishReason: Bool
     let supportsStrictMode: Bool
     /// "max_tokens" for legacy OpenAI servers, "max_completion_tokens" for newer.
     let maxTokensField: String
@@ -34,75 +50,59 @@ struct PiProviderModel {
     /// DSML servers require the original `reasoning_content` to be sent back on
     /// follow-up assistant messages so the transcript matches what was sampled.
     let requiresReasoningContentOnAssistantMessages: Bool
-    /// Optional map from Pi thinking-level keys (off/minimal/low/medium/high/xhigh)
-    /// to the provider's native effort label. `nil` value in JS means the model
-    /// should be invoked without a reasoning_effort argument.
+    /// Optional map from Pi thinking-level keys to the provider's native effort
+    /// label. A nil value is rendered as null, which marks that level unsupported.
     let thinkingLevelMap: [(key: String, value: String?)]?
 
     init(
         id: String,
         name: String,
-        contextWindow: Int,
-        maxTokens: Int,
-        reasoning: Bool = false,
-        supportsStore: Bool = false,
-        supportsDeveloperRole: Bool = false,
-        supportsReasoningEffort: Bool = false,
-        supportsUsageInStreaming: Bool = false,
-        supportsStrictMode: Bool = false,
-        maxTokensField: String = "max_tokens",
-        thinkingFormat: String? = nil,
-        requiresReasoningContentOnAssistantMessages: Bool = false,
-        thinkingLevelMap: [(key: String, value: String?)]? = nil
-    ) {
+        profile: ManagedModelAPIProfile
+    ) throws {
+        guard profile.task == .chatCompletions,
+              let contextWindow = profile.contextWindow,
+              let maxTokens = profile.maximumOutputTokens else {
+            throw PiProviderModelError.invalidCatalogProfile(id)
+        }
+        let supportedThinkingLevels = Set(profile.thinkingLevels)
+        let thinkingLevelMap = profile.reasoning
+            ? ManagedModelThinkingLevel.allCases.compactMap { level -> (key: String, value: String?)? in
+                guard supportedThinkingLevels.contains(level) else {
+                    return (level.rawValue, nil)
+                }
+                guard let mapped = profile.thinkingLevelMap[level] else {
+                    return nil
+                }
+                return (level.rawValue, mapped.rawValue)
+            }
+            : nil
+        let compatibility = profile.compatibility
         self.id = id
         self.name = name
         self.contextWindow = contextWindow
         self.maxTokens = maxTokens
-        self.reasoning = reasoning
-        self.supportsStore = supportsStore
-        self.supportsDeveloperRole = supportsDeveloperRole
-        self.supportsReasoningEffort = supportsReasoningEffort
-        self.supportsUsageInStreaming = supportsUsageInStreaming
-        self.supportsStrictMode = supportsStrictMode
-        self.maxTokensField = maxTokensField
-        self.thinkingFormat = thinkingFormat
-        self.requiresReasoningContentOnAssistantMessages = requiresReasoningContentOnAssistantMessages
+        self.inputModalities = profile.inputModalities.compactMap { modality in
+            switch modality {
+            case .text, .image:
+                return modality.rawValue
+            case .audio, .video, .embedding, .geometry, .threeD:
+                return nil
+            }
+        }
+        self.reasoning = profile.reasoning
+        self.toolCall = profile.toolCall
+        self.supportsStore = compatibility.supportsStore
+        self.supportsDeveloperRole = compatibility.supportsDeveloperRole
+        self.supportsReasoningEffort = compatibility.supportsReasoningEffort
+        self.supportsUsageInStreaming = compatibility.supportsUsageInStreaming
+        self.supportsFinishReason = compatibility.supportsFinishReason
+        self.supportsStrictMode = compatibility.supportsStrictMode
+        self.maxTokensField = compatibility.maxTokensField.rawValue
+        self.thinkingFormat = compatibility.thinkingFormat?.rawValue
+        self.requiresReasoningContentOnAssistantMessages = compatibility
+            .requiresReasoningContentOnAssistantMessages
         self.thinkingLevelMap = thinkingLevelMap
     }
-
-    static let qwen3CoderNext = PiProviderModel(
-        id: CodeGenResources.defaultModelId,
-        name: "Qwen3-Coder Next (mere.run)",
-        contextWindow: 32768,
-        maxTokens: 4096
-    )
-
-    /// DeepSeek V4 Flash compat profile from the upstream ds4 README's
-    /// "For Pi, add a provider to ~/.pi/agent/models.json" section.
-    static let deepseekV4Flash = PiProviderModel(
-        id: DeepseekV4FlashResources.defaultModelId,
-        name: "DeepSeek V4 Flash (mere.run)",
-        contextWindow: DeepseekV4FlashResources.defaultContextLength,
-        maxTokens: DeepseekV4FlashResources.defaultContextLength,
-        reasoning: true,
-        supportsStore: false,
-        supportsDeveloperRole: false,
-        supportsReasoningEffort: true,
-        supportsUsageInStreaming: true,
-        supportsStrictMode: false,
-        maxTokensField: "max_tokens",
-        thinkingFormat: "deepseek",
-        requiresReasoningContentOnAssistantMessages: true,
-        thinkingLevelMap: [
-            ("off", nil),
-            ("minimal", "low"),
-            ("low", "low"),
-            ("medium", "medium"),
-            ("high", "high"),
-            ("xhigh", "xhigh"),
-        ]
-    )
 }
 
 enum PiAgentIntegration {
@@ -221,7 +221,7 @@ enum PiAgentIntegration {
     static func writeLocalProviderExtension(
         host: String,
         port: Int,
-        model: PiProviderModel = .qwen3CoderNext,
+        model: PiProviderModel,
         apiKey: String = "mere-run",
         homeDirectory: URL? = nil,
         persistConfiguration: Bool = true,
@@ -251,9 +251,8 @@ enum PiAgentIntegration {
         return extensionURL
     }
 
-    /// Render the pi-coding-agent extension TS for a single mere.run provider.
-    /// Mirrors the JSON provider catalog shape documented in the ds4 README
-    /// ("For Pi, add a provider to ~/.pi/agent/models.json").
+    /// Render a current Pi extension with one offline fallback and live model
+    /// discovery from mere.run's self-describing `/v1/models` endpoint.
     static func renderPiProviderExtension(
         model: PiProviderModel,
         baseURL: String,
@@ -264,6 +263,7 @@ enum PiAgentIntegration {
         providerCompat.append("supportsDeveloperRole: \(model.supportsDeveloperRole)")
         providerCompat.append("supportsReasoningEffort: \(model.supportsReasoningEffort)")
         providerCompat.append("supportsUsageInStreaming: \(model.supportsUsageInStreaming)")
+        providerCompat.append("supportsFinishReason: \(model.supportsFinishReason)")
         providerCompat.append("maxTokensField: \"\(model.maxTokensField)\"")
         providerCompat.append("supportsStrictMode: \(model.supportsStrictMode)")
         if let format = model.thinkingFormat {
@@ -273,12 +273,15 @@ enum PiAgentIntegration {
             providerCompat.append("requiresReasoningContentOnAssistantMessages: true")
         }
         let compatBlock = providerCompat
-            .map { "      \($0)" }
+            .map { "        \($0)" }
             .joined(separator: ",\n")
 
         var modelLines: [String] = []
-        modelLines.append("id: \"\(model.id)\"")
-        modelLines.append("name: \"\(model.name)\"")
+        modelLines.append("id: \(javascriptStringLiteral(model.id))")
+        modelLines.append("name: \(javascriptStringLiteral(model.name))")
+        modelLines.append("api: \"openai-completions\" as const")
+        modelLines.append("provider: \"mere-run\"")
+        modelLines.append("baseUrl")
         modelLines.append("reasoning: \(model.reasoning)")
         if let map = model.thinkingLevelMap, !map.isEmpty {
             let entries = map.map { entry -> String in
@@ -289,7 +292,10 @@ enum PiAgentIntegration {
             }.joined(separator: ",\n")
             modelLines.append("thinkingLevelMap: {\n\(entries)\n        }")
         }
-        modelLines.append("input: [\"text\"]")
+        let inputModalities = model.inputModalities
+            .map(javascriptStringLiteral)
+            .joined(separator: ", ")
+        modelLines.append("input: [\(inputModalities)] as Array<\"text\" | \"image\">")
         modelLines.append("contextWindow: \(model.contextWindow)")
         modelLines.append("maxTokens: \(model.maxTokens)")
         modelLines.append("""
@@ -301,31 +307,164 @@ enum PiAgentIntegration {
                 }
         """)
         let modelBody = modelLines
-            .map { "        \($0)" }
+            .map { "      \($0)" }
             .joined(separator: ",\n")
 
+        let fallbackModel: String
+        if model.toolCall {
+            fallbackModel = [
+                "  {",
+                modelBody + ",",
+                "    compat: {",
+                compatBlock,
+                "    }",
+                "  }",
+            ].joined(separator: "\n")
+        } else {
+            fallbackModel = ""
+        }
+
+        let quotedBaseURL = javascriptStringLiteral(baseURL)
+        let quotedAPIKey = javascriptStringLiteral(apiKey)
+
         return """
-        import type { ExtensionAPI } from "@mariozechner/pi-coding-agent";
+        import { createProvider, openAICompletionsApi, type Model } from "@earendil-works/pi-ai/compat";
+        import type { ExtensionAPI } from "@earendil-works/pi-coding-agent";
+
+        type ThinkingLevel = "off" | "minimal" | "low" | "medium" | "high" | "xhigh" | "max";
+
+        interface MereRunModel {
+          id: string;
+          name?: string;
+          task?: string;
+          reasoning?: boolean;
+          thinking_levels?: ThinkingLevel[];
+          tool_call?: boolean;
+          modalities?: { input: string[]; output: string[] };
+          limit?: { context: number; output: number };
+          openai_compat?: {
+            supports_store: boolean;
+            supports_developer_role: boolean;
+            supports_reasoning_effort: boolean;
+            supports_usage_in_streaming: boolean;
+            supports_finish_reason: boolean;
+            max_tokens_field: "max_tokens" | "max_completion_tokens";
+            supports_strict_mode: boolean;
+            thinking_format?: "deepseek";
+            thinking_level_map?: Partial<Record<ThinkingLevel, string>>;
+            requires_reasoning_content_on_assistant_messages: boolean;
+          };
+        }
 
-        export default function(pi: ExtensionAPI) {
-          pi.registerProvider("mere-run", {
-            name: "mere.run Local",
-            baseUrl: "\(baseURL)",
+        const baseUrl = \(quotedBaseURL);
+        const apiKey = \(quotedAPIKey);
+        const thinkingLevels: ThinkingLevel[] = [
+          "off", "minimal", "low", "medium", "high", "xhigh", "max"
+        ];
+        const fallbackModels: ReturnType<typeof mapModel>[] = [
+        \(fallbackModel)
+        ];
+
+        function mapThinkingLevels(model: MereRunModel) {
+          if (!model.reasoning || !model.thinking_levels?.length) return undefined;
+          const supported = new Set(model.thinking_levels);
+          const overrides = model.openai_compat?.thinking_level_map ?? {};
+          const result: Partial<Record<ThinkingLevel, string | null>> = {};
+          for (const level of thinkingLevels) {
+            if (!supported.has(level)) result[level] = null;
+            else if (overrides[level]) result[level] = overrides[level];
+          }
+          return result;
+        }
+
+        function mapModel(model: MereRunModel): Model<"openai-completions"> {
+          const compat = model.openai_compat;
+          return {
+            id: model.id,
+            name: model.name ?? model.id,
             api: "openai-completions",
-            apiKey: "\(apiKey)",
-            compat: {
-        \(compatBlock)
-            },
-            models: [
-              {
-        \(modelBody)
-              }
-            ]
+            provider: "mere-run",
+            baseUrl,
+            reasoning: model.reasoning ?? false,
+            thinkingLevelMap: mapThinkingLevels(model),
+            input: (model.modalities?.input ?? ["text"])
+              .filter((value): value is "text" | "image" => value === "text" || value === "image"),
+            cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0 },
+            contextWindow: model.limit?.context ?? 32_768,
+            maxTokens: model.limit?.output ?? 4_096,
+            compat: compat ? {
+              supportsStore: compat.supports_store,
+              supportsDeveloperRole: compat.supports_developer_role,
+              supportsReasoningEffort: compat.supports_reasoning_effort,
+              supportsUsageInStreaming: compat.supports_usage_in_streaming,
+              supportsFinishReason: compat.supports_finish_reason,
+              maxTokensField: compat.max_tokens_field,
+              supportsStrictMode: compat.supports_strict_mode,
+              thinkingFormat: compat.thinking_format,
+              requiresReasoningContentOnAssistantMessages:
+                compat.requires_reasoning_content_on_assistant_messages
+            } : undefined
+          };
+        }
+
+        async function discoverModels(
+          credential: string,
+          signal: AbortSignal
+        ): Promise<Model<"openai-completions">[]> {
+          const response = await fetch(`${baseUrl}/models`, {
+            headers: { Authorization: `Bearer ${credential}` },
+            signal
           });
+          if (!response.ok) throw new Error(`mere.run model discovery failed: HTTP ${response.status}`);
+          const payload = await response.json() as { data?: MereRunModel[] };
+          return (payload.data ?? [])
+            .filter((entry) => entry.task === "chat.completions" && entry.tool_call === true)
+            .map(mapModel);
+        }
+
+        export default async function(pi: ExtensionAPI) {
+          const initialModels = await discoverModels(
+            apiKey,
+            AbortSignal.timeout(2_000)
+          ).catch(() => fallbackModels);
+          pi.registerProvider(createProvider({
+            id: "mere-run",
+            name: "mere.run Local",
+            baseUrl,
+            auth: {
+              apiKey: {
+                name: "mere.run local API key",
+                async resolve({ credential }) {
+                  const key = credential?.key ?? apiKey;
+                  return { auth: { apiKey: key }, source: "mere.run local" };
+                }
+              }
+            },
+            models: initialModels,
+            async fetchModels(context) {
+              const credential = context.credential?.type === "api_key"
+                ? context.credential.key ?? apiKey
+                : apiKey;
+              return discoverModels(credential, context.signal);
+            },
+            api: openAICompletionsApi()
+          }));
         }
         """
     }
 
+    private static func javascriptStringLiteral(_ value: String) -> String {
+        let escaped = value
+            .replacingOccurrences(of: "\\", with: "\\\\")
+            .replacingOccurrences(of: "\"", with: "\\\"")
+            .replacingOccurrences(of: "\n", with: "\\n")
+            .replacingOccurrences(of: "\r", with: "\\r")
+            .replacingOccurrences(of: "\t", with: "\\t")
+            .replacingOccurrences(of: "\u{2028}", with: "\\u2028")
+            .replacingOccurrences(of: "\u{2029}", with: "\\u2029")
+        return "\"\(escaped)\""
+    }
+
     static func mereRunPiHomeDirectory() -> URL {
         MereRunModelPaths.applicationSupportBase
             .appendingPathComponent("agent", isDirectory: true)
@@ -422,7 +561,7 @@ enum PiAgentIntegration {
     }
 
     private static func fetchLatestRelease() async throws -> GitHubRelease {
-        let url = URL(string: "https://api.github.com/repos/badlogic/pi-mono/releases/latest")!
+        let url = URL(string: "https://api.github.com/repos/earendil-works/pi/releases/latest")!
         let (data, _) = try await URLSession.shared.data(from: url)
         return try JSONDecoder().decode(GitHubRelease.self, from: data)
     }
diff --git a/Sources/MereRunCLI/Support/RuntimeModelPool.swift b/Sources/MereRunCLI/Support/RuntimeModelPool.swift
index 121552b5..1810dedd 100644
--- a/Sources/MereRunCLI/Support/RuntimeModelPool.swift
+++ b/Sources/MereRunCLI/Support/RuntimeModelPool.swift
@@ -898,12 +898,12 @@ actor RuntimeModelPool {
         let settings: RuntimeModelSettings
         let spec: ManagedModelSpec?
 
+        var apiProfile: ManagedModelAPIProfile {
+            spec?.apiProfile ?? .runtimeFallback(for: engine)
+        }
+
         var openAICompatibility: APIEngineCapabilities {
-            var capabilities = engine.openAICompatibility
-            if spec?.category == .visionChat {
-                capabilities.supportsVisionContentParts = true
-            }
-            return capabilities
+            .catalog(apiProfile)
         }
     }
 
@@ -992,8 +992,35 @@ actor RuntimeModelPool {
         _ = try await loadModel(idOrAlias: defaultModelID)
     }
 
-    func modelsResponse(createdAt: Date = Date()) throws -> OpenAIModelsResponse {
-        APIServerContract.modelsResponse(modelIds: try listedOpenAIModelIDs(), createdAt: createdAt)
+    func modelsResponse(
+        serverContextSize: Int = 32_768,
+        createdAt: Date = Date()
+    ) throws -> OpenAIModelsResponse {
+        let models = try listedOpenAIModelIDs().map { listedID in
+            let resolved = try resolveModel(listedID, requireInstalled: false)
+            let profile = resolved.apiProfile
+            let configuredContextWindow = resolved.settings.maxContextTokens ?? serverContextSize
+            let contextWindow = min(
+                profile.contextWindow ?? configuredContextWindow,
+                configuredContextWindow
+            )
+            let catalogOutputLimit = profile.maximumOutputTokens ?? contextWindow
+            let configuredOutputLimit = resolved.settings.maxTokens ?? catalogOutputLimit
+            let maximumOutputTokens = min(
+                min(catalogOutputLimit, configuredOutputLimit),
+                contextWindow
+            )
+            let name = resolved.spec?.upstreamRepoId ?? resolved.id
+            return APIServerContract.chatModel(
+                id: listedID,
+                name: name,
+                profile: profile,
+                contextWindow: contextWindow,
+                maximumOutputTokens: maximumOutputTokens,
+                createdAt: createdAt
+            )
+        }
+        return OpenAIModelsResponse(object: "list", data: models)
     }
 
     func status() async -> RuntimeModelPoolStatus {
@@ -1192,7 +1219,8 @@ actor RuntimeModelPool {
             fallbackLoraPath: fallbackLoraPath,
             contextSize: contextSize,
             capabilities: capabilities,
-            servedModelID: resolved.id
+            servedModelID: resolved.id,
+            apiProfile: resolved.apiProfile
         )
         chatRequest.kvCacheMode = resolved.settings.kvCacheMode
         let includeUsage = try APIServerContract.includeUsageInStreaming(
@@ -2344,26 +2372,7 @@ enum RuntimeLoadedModel: Sendable {
 
 extension RuntimeServingEngine {
     var openAICompatibility: APIEngineCapabilities {
-        switch self {
-        case .textCode:
-            return .localTextWithStopSequences
-        case .textChatKlein:
-            return .localTextWithStructuredJSON
-        case .textChatGemma4:
-            return .localTextWithToolsAndStructuredJSON
-        case .textChatLaguna:
-            return .localTextWithToolsAndStopSequences
-        case .textChatQ36, .textChatQ35:
-            return .localTextWithToolsVisionAndStructuredJSON
-        case .textChatLFM2:
-            return .localTextWithTools
-        case .textChatDeepseekV4Flash:
-            return .rawProxy
-        case .textChatMuseGlimmer:
-            return .localTextWithToolsVisionAndReasoning
-        case .textChatNemotronH:
-            return .localTextWithToolsAndStopSequences
-        }
+        .catalog(.runtimeFallback(for: self))
     }
 }
 
diff --git a/Sources/MereRunCLI/Support/SetupAgentPrompt.swift b/Sources/MereRunCLI/Support/SetupAgentPrompt.swift
index abda81b7..83999926 100644
--- a/Sources/MereRunCLI/Support/SetupAgentPrompt.swift
+++ b/Sources/MereRunCLI/Support/SetupAgentPrompt.swift
@@ -45,7 +45,7 @@ enum SetupAgentPrompt {
 
         Setup workflow rules:
         - If the selected setup-agent is recommended, do not suggest another setup/chat agent as an upgrade.
-        - On 96 GB+ Apple Silicon Macs, DeepSeek V4 Flash is the preferred premier setup-agent tier; smaller Qwen agents are alternatives for lower-memory workflows.
+        - On 96 GB+ Apple Silicon Macs, DeepSeek V4 Flash is the preferred premier setup-agent tier; smaller tool-capable native agents are alternatives for lower-memory workflows.
         - Treat the recommended setup-agent line as authoritative for agent/chat setup recommendations; the broader supported managed-model list is cross-modality coverage, not a ranked upgrade list.
         - Do not explore the repository to discover setup facts unless a listed command fails.
         - Do not run demo scripts, sample scripts, `demo.sh`, `scripts/check.sh`, `swift build`, or `swift test` for onboarding.
diff --git a/Sources/MereRunCore/AgentModelResources.swift b/Sources/MereRunCore/AgentModelResources.swift
index fe3b71ac..0dae926a 100644
--- a/Sources/MereRunCore/AgentModelResources.swift
+++ b/Sources/MereRunCore/AgentModelResources.swift
@@ -80,7 +80,12 @@ public struct MereRunAgentModelRecommendation: Hashable, Sendable {
     public let reason: String?
 
     public var isStartableByMereRun: Bool {
-        managedModelID != nil && !sourceConfigurationRequired
+        guard let managedModelID,
+              !sourceConfigurationRequired,
+              let profile = ManagedModelCatalog.apiProfile(for: managedModelID) else {
+            return false
+        }
+        return profile.task == .chatCompletions && profile.toolCall
     }
 
     public init(
@@ -128,7 +133,7 @@ public enum MereRunAgentModelCatalog {
         on machine: MereRunMachineProfile = .current
     ) -> MereRunAgentModelRecommendation? {
         guard machine.unifiedMemoryGB >= 16 else { return nil }
-        return qwen35NineB()
+        return ornith9B()
     }
 
     public static func tierRecommendation(
@@ -138,15 +143,12 @@ public enum MereRunAgentModelCatalog {
         if machine.unifiedMemoryGB >= 96 {
             return deepseekV4Flash()
         }
-        if machine.isLinux && machine.unifiedMemoryGB >= 64 {
-            return qwen3CoderNext()
+        if machine.isLinux && machine.unifiedMemoryGB >= 24 {
+            return q36Nano()
         }
         if machine.unifiedMemoryGB >= 64 {
             return gemma12B4Bit()
         }
-        if machine.isLinux && machine.unifiedMemoryGB >= 24 {
-            return q36Nano()
-        }
         if machine.unifiedMemoryGB >= 24 {
             return gemma12B4Bit()
         }
@@ -169,15 +171,12 @@ public enum MereRunAgentModelCatalog {
         if machine.unifiedMemoryGB >= 96 {
             return deepseekV4Flash()
         }
-        if machine.isLinux && machine.unifiedMemoryGB >= 64 {
-            return qwen3CoderNext()
+        if machine.isLinux && machine.unifiedMemoryGB >= 24 {
+            return q36Nano()
         }
         if machine.unifiedMemoryGB >= 64 {
             return gemma12B4Bit()
         }
-        if machine.isLinux && machine.unifiedMemoryGB >= 24 {
-            return q36Nano()
-        }
         if machine.unifiedMemoryGB >= 24 {
             return gemma12B4Bit()
         }
diff --git a/Sources/MereRunCore/CodeGen/OpenAITypes.swift b/Sources/MereRunCore/CodeGen/OpenAITypes.swift
index 66852e50..0f887285 100644
--- a/Sources/MereRunCore/CodeGen/OpenAITypes.swift
+++ b/Sources/MereRunCore/CodeGen/OpenAITypes.swift
@@ -1049,12 +1049,101 @@ public struct OpenAIModel: Codable, Sendable {
     public var object: String
     public var created: Int
     public var owned_by: String
+    public var name: String?
+    public var task: String?
+    public var reasoning: Bool?
+    public var thinking_levels: [String]?
+    public var tool_call: Bool?
+    public var structured_output: Bool?
+    public var modalities: OpenAIModelModalities?
+    public var limit: OpenAIModelLimit?
+    public var openai_compat: OpenAIModelCompatibility?
 
-    public init(id: String, object: String, created: Int, owned_by: String) {
+    public init(
+        id: String,
+        object: String,
+        created: Int,
+        owned_by: String,
+        name: String? = nil,
+        task: String? = nil,
+        reasoning: Bool? = nil,
+        thinking_levels: [String]? = nil,
+        tool_call: Bool? = nil,
+        structured_output: Bool? = nil,
+        modalities: OpenAIModelModalities? = nil,
+        limit: OpenAIModelLimit? = nil,
+        openai_compat: OpenAIModelCompatibility? = nil
+    ) {
         self.id = id
         self.object = object
         self.created = created
         self.owned_by = owned_by
+        self.name = name
+        self.task = task
+        self.reasoning = reasoning
+        self.thinking_levels = thinking_levels
+        self.tool_call = tool_call
+        self.structured_output = structured_output
+        self.modalities = modalities
+        self.limit = limit
+        self.openai_compat = openai_compat
+    }
+}
+
+public struct OpenAIModelModalities: Codable, Equatable, Sendable {
+    public var input: [String]
+    public var output: [String]
+
+    public init(input: [String], output: [String]) {
+        self.input = input
+        self.output = output
+    }
+}
+
+public struct OpenAIModelLimit: Codable, Equatable, Sendable {
+    public var context: Int
+    public var output: Int
+
+    public init(context: Int, output: Int) {
+        self.context = context
+        self.output = output
+    }
+}
+
+public struct OpenAIModelCompatibility: Codable, Equatable, Sendable {
+    public var supports_store: Bool
+    public var supports_developer_role: Bool
+    public var supports_reasoning_effort: Bool
+    public var supports_usage_in_streaming: Bool
+    public var supports_finish_reason: Bool
+    public var max_tokens_field: String
+    public var supports_strict_mode: Bool
+    public var thinking_format: String?
+    public var thinking_level_map: [String: String]?
+    public var requires_reasoning_content_on_assistant_messages: Bool
+
+    public init(
+        supports_store: Bool,
+        supports_developer_role: Bool,
+        supports_reasoning_effort: Bool,
+        supports_usage_in_streaming: Bool,
+        supports_finish_reason: Bool,
+        max_tokens_field: String,
+        supports_strict_mode: Bool,
+        thinking_format: String? = nil,
+        thinking_level_map: [String: String]? = nil,
+        requires_reasoning_content_on_assistant_messages: Bool = false
+    ) {
+        self.supports_store = supports_store
+        self.supports_developer_role = supports_developer_role
+        self.supports_reasoning_effort = supports_reasoning_effort
+        self.supports_usage_in_streaming = supports_usage_in_streaming
+        self.supports_finish_reason = supports_finish_reason
+        self.max_tokens_field = max_tokens_field
+        self.supports_strict_mode = supports_strict_mode
+        self.thinking_format = thinking_format
+        self.thinking_level_map = thinking_level_map
+        self.requires_reasoning_content_on_assistant_messages = requires_reasoning_content_on_assistant_messages
     }
 }
 
diff --git a/Sources/MereRunCore/ManagedModelCatalog.swift b/Sources/MereRunCore/ManagedModelCatalog.swift
index 7a9c8aad..be5b32f6 100644
--- a/Sources/MereRunCore/ManagedModelCatalog.swift
+++ b/Sources/MereRunCore/ManagedModelCatalog.swift
@@ -26,6 +26,417 @@ public enum ManagedModelCategory: String, CaseIterable, Hashable, Sendable {
     case video = "video"
 }
 
+public enum ManagedModelAPITask: String, Hashable, Sendable {
+    case chatCompletions = "chat.completions"
+    case imageGenerations = "images.generations"
+    case imageEdits = "images.edits"
+    case audioSpeech = "audio.speech"
+    case audioTranscriptions = "audio.transcriptions"
+    case embeddings
+    case visionGeometry = "vision.geometry"
+    case visionDepth = "vision.depth"
+    case visionImageTo3D = "vision.image_to_3d"
+}
+
+public enum ManagedModelAPIModality: String, Hashable, Sendable {
+    case text
+    case image
+    case audio
+    case video
+    case embedding
+    case geometry
+    case threeD = "3d"
+}
+
+public enum ManagedModelThinkingLevel: String, CaseIterable, Hashable, Sendable {
+    case off
+    case minimal
+    case low
+    case medium
+    case high
+    case xhigh
+    case max
+}
+
+public enum ManagedModelMaxTokensField: String, Hashable, Sendable {
+    case maxTokens = "max_tokens"
+    case maxCompletionTokens = "max_completion_tokens"
+}
+
+public enum ManagedModelThinkingFormat: String, Hashable, Sendable {
+    case deepseek
+}
+
+public struct ManagedModelOpenAICompatibilityProfile: Hashable, Sendable {
+    public let supportsStore: Bool
+    public let supportsDeveloperRole: Bool
+    public let supportsReasoningEffort: Bool
+    public let supportsUsageInStreaming: Bool
+    public let supportsFinishReason: Bool
+    public let maxTokensField: ManagedModelMaxTokensField
+    public let supportsStrictMode: Bool
+    public let thinkingFormat: ManagedModelThinkingFormat?
+    public let requiresReasoningContentOnAssistantMessages: Bool
+
+    public init(
+        supportsStore: Bool = false,
+        supportsDeveloperRole: Bool = true,
+        supportsReasoningEffort: Bool = false,
+        supportsUsageInStreaming: Bool = true,
+        supportsFinishReason: Bool = true,
+        maxTokensField: ManagedModelMaxTokensField = .maxCompletionTokens,
+        supportsStrictMode: Bool = false,
+        thinkingFormat: ManagedModelThinkingFormat? = nil,
+        requiresReasoningContentOnAssistantMessages: Bool = false
+    ) {
+        self.supportsStore = supportsStore
+        self.supportsDeveloperRole = supportsDeveloperRole
+        self.supportsReasoningEffort = supportsReasoningEffort
+        self.supportsUsageInStreaming = supportsUsageInStreaming
+        self.supportsFinishReason = supportsFinishReason
+        self.maxTokensField = maxTokensField
+        self.supportsStrictMode = supportsStrictMode
+        self.thinkingFormat = thinkingFormat
+        self.requiresReasoningContentOnAssistantMessages = requiresReasoningContentOnAssistantMessages
+    }
+}
+
+/// The capabilities mere.run promises when it serves a managed model.
+///
+/// This is deliberately catalog metadata rather than a client-specific model
+/// definition. API discovery, request validation, and harness integrations all
+/// project from the same profile, then apply runtime settings such as context
+/// and output-token overrides.
+public struct ManagedModelAPIProfile: Hashable, Sendable {
+    public let task: ManagedModelAPITask
+    public let servingEngine: RuntimeServingEngine?
+    public let inputModalities: [ManagedModelAPIModality]
+    public let outputModalities: [ManagedModelAPIModality]
+    public let contextWindow: Int?
+    public let maximumOutputTokens: Int?
+    public let thinkingLevels: [ManagedModelThinkingLevel]
+    public let thinkingLevelMap: [ManagedModelThinkingLevel: ManagedModelThinkingLevel]
+    public let reasoningEffortStrengths: [ManagedModelThinkingLevel: Double]
+    public let toolCall: Bool
+    public let structuredOutput: Bool
+    public let compatibility: ManagedModelOpenAICompatibilityProfile
+    public let supportsRawProxy: Bool
+    public let supportsToolChoice: Bool
+    public let supportsStopSequences: Bool
+    public let supportsSeed: Bool
+    public let supportsPenalties: Bool
+    public let supportsLogprobs: Bool
+    public let supportsProviderThinkingControls: Bool
+
+    public var reasoning: Bool {
+        !thinkingLevels.isEmpty
+    }
+
+    public init(
+        task: ManagedModelAPITask,
+        servingEngine: RuntimeServingEngine? = nil,
+        inputModalities: [ManagedModelAPIModality],
+        outputModalities: [ManagedModelAPIModality],
+        contextWindow: Int? = nil,
+        maximumOutputTokens: Int? = nil,
+        thinkingLevels: [ManagedModelThinkingLevel] = [],
+        thinkingLevelMap: [ManagedModelThinkingLevel: ManagedModelThinkingLevel] = [:],
+        reasoningEffortStrengths: [ManagedModelThinkingLevel: Double] = [:],
+        toolCall: Bool = false,
+        structuredOutput: Bool = false,
+        compatibility: ManagedModelOpenAICompatibilityProfile = .init(),
+        supportsRawProxy: Bool = false,
+        supportsToolChoice: Bool = false,
+        supportsStopSequences: Bool = false,
+        supportsSeed: Bool = false,
+        supportsPenalties: Bool = false,
+        supportsLogprobs: Bool = false,
+        supportsProviderThinkingControls: Bool = false
+    ) {
+        self.task = task
+        self.servingEngine = servingEngine
+        self.inputModalities = inputModalities
+        self.outputModalities = outputModalities
+        self.contextWindow = contextWindow
+        self.maximumOutputTokens = maximumOutputTokens
+        self.thinkingLevels = thinkingLevels
+        self.thinkingLevelMap = thinkingLevelMap
+        self.reasoningEffortStrengths = reasoningEffortStrengths
+        self.toolCall = toolCall
+        self.structuredOutput = structuredOutput
+        self.compatibility = compatibility
+        self.supportsRawProxy = supportsRawProxy
+        self.supportsToolChoice = supportsToolChoice
+        self.supportsStopSequences = supportsStopSequences
+        self.supportsSeed = supportsSeed
+        self.supportsPenalties = supportsPenalties
+        self.supportsLogprobs = supportsLogprobs
+        self.supportsProviderThinkingControls = supportsProviderThinkingControls
+    }
+}
+
+public extension ManagedModelAPIProfile {
+    static func textCode(
+        contextWindow: Int = 32_768,
+        maximumOutputTokens: Int = 4_096
+    ) -> ManagedModelAPIProfile {
+        chat(
+            servingEngine: .textCode,
+            contextWindow: contextWindow,
+            maximumOutputTokens: maximumOutputTokens,
+            supportsStopSequences: true
+        )
+    }
+
+    static func klein(contextWindow: Int = 32_768) -> ManagedModelAPIProfile {
+        chat(
+            servingEngine: .textChatKlein,
+            contextWindow: contextWindow,
+            maximumOutputTokens: 4_096,
+            structuredOutput: true
+        )
+    }
+
+    static func gemma4(
+        inputModalities: [ManagedModelAPIModality] = [.text],
+        contextWindow: Int = Gemma4Resources.defaultContextLength
+    ) -> ManagedModelAPIProfile {
+        chat(
+            servingEngine: .textChatGemma4,
+            inputModalities: inputModalities,
+            contextWindow: contextWindow,
+            maximumOutputTokens: 4_096,
+            toolCall: true,
+            structuredOutput: true
+        )
+    }
+
+    static func laguna(contextWindow: Int = LagunaResources.defaultContextLength) -> ManagedModelAPIProfile {
+        chat(
+            servingEngine: .textChatLaguna,
+            contextWindow: contextWindow,
+            maximumOutputTokens: 4_096,
+            toolCall: true,
+            supportsStopSequences: true
+        )
+    }
+
+    static func q36(
+        contextWindow: Int,
+        fixedReasoning: Bool = false
+    ) -> ManagedModelAPIProfile {
+        chat(
+            servingEngine: .textChatQ36,
+            inputModalities: [.text, .image],
+            contextWindow: contextWindow,
+            maximumOutputTokens: 4_096,
+            thinkingLevels: fixedReasoning ? [.high] : [],
+            toolCall: true,
+            structuredOutput: true
+        )
+    }
+
+    static func lfm2(
+        inputModalities: [ManagedModelAPIModality] = [.text],
+        contextWindow: Int = LFM2Resources.defaultContextLength
+    ) -> ManagedModelAPIProfile {
+        chat(
+            servingEngine: .textChatLFM2,
+            inputModalities: inputModalities,
+            contextWindow: contextWindow,
+            maximumOutputTokens: 4_096,
+            toolCall: true
+        )
+    }
+
+    static func deepseekV4Flash(
+        contextWindow: Int = DeepseekV4FlashResources.defaultContextLength
+    ) -> ManagedModelAPIProfile {
+        chat(
+            servingEngine: .textChatDeepseekV4Flash,
+            inputModalities: [.text, .image],
+            contextWindow: contextWindow,
+            maximumOutputTokens: contextWindow,
+            thinkingLevels: [.off, .minimal, .low, .medium, .high, .xhigh],
+            thinkingLevelMap: [.minimal: .low],
+            toolCall: true,
+            compatibility: ManagedModelOpenAICompatibilityProfile(
+                supportsDeveloperRole: false,
+                supportsReasoningEffort: true,
+                maxTokensField: .maxTokens,
+                thinkingFormat: .deepseek,
+                requiresReasoningContentOnAssistantMessages: true
+            ),
+            supportsRawProxy: true,
+            supportsStopSequences: true,
+            supportsSeed: true,
+            supportsPenalties: true,
+            supportsLogprobs: true,
+            supportsProviderThinkingControls: true
+        )
+    }
+
+    static func museGlimmer(
+        contextWindow: Int = MuseGlimmerResources.defaultContextLength
+    ) -> ManagedModelAPIProfile {
+        chat(
+            servingEngine: .textChatMuseGlimmer,
+            inputModalities: [.text, .image],
+            contextWindow: contextWindow,
+            maximumOutputTokens: 4_096,
+            thinkingLevels: [.minimal, .low, .medium, .high, .xhigh, .max],
+            thinkingLevelMap: [.minimal: .low, .max: .xhigh],
+            reasoningEffortStrengths: [
+                .minimal: 0.1,
+                .low: 0.25,
+                .medium: 0.5,
+                .high: 0.8,
+                .xhigh: 1,
+                .max: 1,
+            ],
+            toolCall: true,
+            compatibility: ManagedModelOpenAICompatibilityProfile(
+                supportsReasoningEffort: true
+            )
+        )
+    }
+
+    static func nemotronH(
+        contextWindow: Int = NemotronHResources.defaultContextLength
+    ) -> ManagedModelAPIProfile {
+        chat(
+            servingEngine: .textChatNemotronH,
+            contextWindow: contextWindow,
+            maximumOutputTokens: 4_096,
+            toolCall: true,
+            supportsStopSequences: true
+        )
+    }
+
+    static func runtimeFallback(for engine: RuntimeServingEngine) -> ManagedModelAPIProfile {
+        switch engine {
+        case .textCode:
+            return .textCode()
+        case .textChatKlein:
+            return .klein()
+        case .textChatGemma4:
+            return .gemma4()
+        case .textChatLaguna:
+            return .laguna()
+        case .textChatQ36, .textChatQ35:
+            return .q36(contextWindow: Q35Resources.defaultContextLength)
+        case .textChatLFM2:
+            return .lfm2()
+        case .textChatDeepseekV4Flash:
+            return .deepseekV4Flash()
+        case .textChatMuseGlimmer:
+            return .museGlimmer()
+        case .textChatNemotronH:
+            return .nemotronH()
+        }
+    }
+
+    static func companion(
+        modelID: String,
+        category: ManagedModelCategory?
+    ) -> ManagedModelAPIProfile? {
+        if modelID == QwenImageEditRepository.modelId {
+            return ManagedModelAPIProfile(
+                task: .imageEdits,
+                inputModalities: [.text, .image],
+                outputModalities: [.image]
+            )
+        }
+        switch category {
+        case .image:
+            return ManagedModelAPIProfile(
+                task: .imageGenerations,
+                inputModalities: [.text],
+                outputModalities: [.image]
+            )
+        case .image3D:
+            return ManagedModelAPIProfile(
+                task: .visionImageTo3D,
+                inputModalities: [.image],
+                outputModalities: [.threeD]
+            )
+        case .speechTTS:
+            return ManagedModelAPIProfile(
+                task: .audioSpeech,
+                inputModalities: [.text],
+                outputModalities: [.audio]
+            )
+        case .speechASR:
+            return ManagedModelAPIProfile(
+                task: .audioTranscriptions,
+                inputModalities: [.audio],
+                outputModalities: [.text]
+            )
+        case .textEmbed:
+            return ManagedModelAPIProfile(
+                task: .embeddings,
+                inputModalities: [.text],
+                outputModalities: [.embedding]
+            )
+        case .visionGeometry:
+            return ManagedModelAPIProfile(
+                task: .visionGeometry,
+                inputModalities: [.image],
+                outputModalities: [.geometry]
+            )
+        case .visionDepth:
+            return ManagedModelAPIProfile(
+                task: .visionDepth,
+                inputModalities: [.video],
+                outputModalities: [.video]
+            )
+        default:
+            return nil
+        }
+    }
+
+    private static func chat(
+        servingEngine: RuntimeServingEngine,
+        inputModalities: [ManagedModelAPIModality] = [.text],
+        contextWindow: Int,
+        maximumOutputTokens: Int,
+        thinkingLevels: [ManagedModelThinkingLevel] = [],
+        thinkingLevelMap: [ManagedModelThinkingLevel: ManagedModelThinkingLevel] = [:],
+        reasoningEffortStrengths: [ManagedModelThinkingLevel: Double] = [:],
+        toolCall: Bool = false,
+        structuredOutput: Bool = false,
+        compatibility: ManagedModelOpenAICompatibilityProfile = .init(),
+        supportsRawProxy: Bool = false,
+        supportsStopSequences: Bool = false,
+        supportsSeed: Bool = false,
+        supportsPenalties: Bool = false,
+        supportsLogprobs: Bool = false,
+        supportsProviderThinkingControls: Bool = false
+    ) -> ManagedModelAPIProfile {
+        ManagedModelAPIProfile(
+            task: .chatCompletions,
+            servingEngine: servingEngine,
+            inputModalities: inputModalities,
+            outputModalities: [.text],
+            contextWindow: contextWindow,
+            maximumOutputTokens: maximumOutputTokens,
+            thinkingLevels: thinkingLevels,
+            thinkingLevelMap: thinkingLevelMap,
+            reasoningEffortStrengths: reasoningEffortStrengths,
+            toolCall: toolCall,
+            structuredOutput: structuredOutput,
+            compatibility: compatibility,
+            supportsRawProxy: supportsRawProxy,
+            supportsToolChoice: toolCall,
+            supportsStopSequences: supportsStopSequences,
+            supportsSeed: supportsSeed,
+            supportsPenalties: supportsPenalties,
+            supportsLogprobs: supportsLogprobs,
+            supportsProviderThinkingControls: supportsProviderThinkingControls
+        )
+    }
+}
+
 public enum ManagedModelInstallShape: Hashable, Sendable {
     case directoryRoot
     case singleFile(relativePath: String)
@@ -176,6 +587,7 @@ public struct ManagedModelSpec: Hashable, Sendable {
     public let estimatedDownloadBytes: Int64?
     public let defaultCLICommands: [String]
     public let companionModelIDs: [String]
+    public let apiProfile: ManagedModelAPIProfile?
 
     public init(
         id: String,
@@ -193,7 +605,8 @@ public struct ManagedModelSpec: Hashable, Sendable {
         resolutionFallbackIDs: [String] = [],
         estimatedDownloadBytes: Int64? = nil,
         defaultCLICommands: [String] = [],
-        companionModelIDs: [String] = []
+        companionModelIDs: [String] = [],
+        apiProfile: ManagedModelAPIProfile? = nil
     ) {
         self.id = id
         self.category = category
@@ -211,10 +624,19 @@ public struct ManagedModelSpec: Hashable, Sendable {
         self.estimatedDownloadBytes = estimatedDownloadBytes
         self.defaultCLICommands = defaultCLICommands
         self.companionModelIDs = companionModelIDs
+        self.apiProfile = apiProfile ?? ManagedModelAPIProfile.companion(
+            modelID: id,
+            category: category
+        )
     }
 }
 
 public enum ManagedModelCatalog {
+    public static func apiProfile(for modelID: String) -> ManagedModelAPIProfile? {
+        spec(for: modelID)?.apiProfile
+            ?? ManagedModelAPIProfile.companion(modelID: modelID, category: nil)
+    }
+
     private static let diffusersImageSnapshotPatterns = [
         "LICENSE*",
         "README.md",
@@ -1002,7 +1424,8 @@ public enum ManagedModelCatalog {
             installShape: .directoryRoot,
             validationKind: .hfTextChat,
             runtimeAutoDownloadAllowed: false,
-            defaultCLICommands: ["api serve"]
+            defaultCLICommands: ["api serve"],
+            apiProfile: .klein()
         ),
         ManagedModelSpec(
             id: "text-chat-psi-agent",
@@ -1023,7 +1446,8 @@ public enum ManagedModelCatalog {
             validationKind: .gemma4,
             resolutionFallbackIDs: ["text-chat-gemma4-max", "text-chat-gemma4-nano"],
             estimatedDownloadBytes: 62_578_654_199,
-            defaultCLICommands: ["text chat", "text train-lora", "api serve"]
+            defaultCLICommands: ["text chat", "text train-lora", "api serve"],
+            apiProfile: .gemma4()
         ),
         ManagedModelSpec(
             id: Gemma4Resources.turboModelId,
@@ -1037,7 +1461,8 @@ public enum ManagedModelCatalog {
             validationKind: .gemma4,
             runtimeAutoDownloadAllowed: false,
             estimatedDownloadBytes: 31 * 1_073_741_824,
-            defaultCLICommands: ["text chat", "text train-lora", "api serve"]
+            defaultCLICommands: ["text chat", "text train-lora", "api serve"],
+            apiProfile: .gemma4()
         ),
         ManagedModelSpec(
             id: Gemma4Resources.twelveBModelId,
@@ -1051,7 +1476,8 @@ public enum ManagedModelCatalog {
             validationKind: .gemma4,
             estimatedDownloadBytes: 25 * 1_073_741_824,
             defaultCLICommands: ["text chat", "text train-lora", "api serve"],
-            companionModelIDs: [Gemma4MTPResources.modelId]
+            companionModelIDs: [Gemma4MTPResources.modelId],
+            apiProfile: .gemma4()
         ),
         ManagedModelSpec(
             id: Gemma4Resources.twelveB4BitModelId,
@@ -1067,7 +1493,8 @@ public enum ManagedModelCatalog {
             validationKind: .gemma4,
             estimatedDownloadBytes: 6_773_374_762,
             defaultCLICommands: ["text chat", "text train-lora", "api serve"],
-            companionModelIDs: [Gemma4MTPResources.modelId]
+            companionModelIDs: [Gemma4MTPResources.modelId],
+            apiProfile: .gemma4()
         ),
         ManagedModelSpec(
             id: Gemma4Resources.visionTwelveBModelId,
@@ -1081,7 +1508,8 @@ public enum ManagedModelCatalog {
             validationKind: .gemma4Unified,
             estimatedDownloadBytes: 25 * 1_073_741_824,
             defaultCLICommands: ["api serve"],
-            companionModelIDs: [Gemma4MTPResources.modelId]
+            companionModelIDs: [Gemma4MTPResources.modelId],
+            apiProfile: .gemma4(inputModalities: [.text, .image])
         ),
         ManagedModelSpec(
             id: "text-chat-gemma4-nano",
@@ -1094,7 +1522,8 @@ public enum ManagedModelCatalog {
             upstreamRepoId: Gemma4Resources.nanoUpstreamModelId,
             validationKind: .gemma4,
             estimatedDownloadBytes: 16_024_791_983,
-            defaultCLICommands: ["text chat", "text train-lora", "api serve"]
+            defaultCLICommands: ["text chat", "text train-lora", "api serve"],
+            apiProfile: .gemma4()
         ),
         ManagedModelSpec(
             id: "text-chat-gemma4-max",
@@ -1107,7 +1536,8 @@ public enum ManagedModelCatalog {
             upstreamRepoId: Gemma4Resources.maxUpstreamModelId,
             validationKind: .gemma4,
             estimatedDownloadBytes: 62_578_654_199,
-            defaultCLICommands: ["text chat", "text train-lora", "api serve"]
+            defaultCLICommands: ["text chat", "text train-lora", "api serve"],
+            apiProfile: .gemma4()
         ),
         ManagedModelSpec(
             id: LagunaResources.modelID,
@@ -1124,7 +1554,8 @@ public enum ManagedModelCatalog {
             runtimeAutoDownloadAllowed: false,
             estimatedDownloadBytes: LagunaResources.estimatedDownloadBytes,
             defaultCLICommands: ["text chat", "api serve", "model benchmark chat"],
-            companionModelIDs: [LagunaResources.dflashModelID]
+            companionModelIDs: [LagunaResources.dflashModelID],
+            apiProfile: .laguna()
         ),
         ManagedModelSpec(
             id: LagunaResources.xsModelID,
@@ -1145,7 +1576,8 @@ public enum ManagedModelCatalog {
                 "text train-lora",
                 "api serve",
                 "model benchmark chat",
-            ]
+            ],
+            apiProfile: .laguna()
         ),
         ManagedModelSpec(
             id: InklingResources.modelID,
@@ -1187,7 +1619,8 @@ public enum ManagedModelCatalog {
             runtimeAutoDownloadAllowed: false,
             estimatedDownloadBytes: MuseGlimmerResources.estimatedDownloadBytes,
             defaultCLICommands: ["text chat", "api serve"],
-            companionModelIDs: [MuseGlimmerResources.assistantModelId]
+            companionModelIDs: [MuseGlimmerResources.assistantModelId],
+            apiProfile: .museGlimmer()
         ),
         ManagedModelSpec(
             id: NemotronHResources.modelID,
@@ -1204,7 +1637,8 @@ public enum ManagedModelCatalog {
             runtimeAutoDownloadAllowed: false,
             estimatedDownloadBytes: NemotronHResources.estimatedDownloadBytes,
             defaultCLICommands: ["text chat", "api serve", "model benchmark chat"],
-            companionModelIDs: [NemotronHResources.dsparkModelID]
+            companionModelIDs: [NemotronHResources.dsparkModelID],
+            apiProfile: .nemotronH()
         ),
         ManagedModelSpec(
             id: Q35Resources.q36NanoModelId,
@@ -1215,7 +1649,8 @@ public enum ManagedModelCatalog {
             upstreamRevision: Q35Resources.q36NanoUpstreamRevision,
             validationKind: .q35,
             estimatedDownloadBytes: 24 * 1_073_741_824,
-            defaultCLICommands: ["chat", "api serve"]
+            defaultCLICommands: ["chat", "api serve"],
+            apiProfile: .q36(contextWindow: Q35Resources.defaultContextLength)
         ),
         ManagedModelSpec(
             id: Q35Resources.bonsai27B1BitModelId,
@@ -1226,7 +1661,11 @@ public enum ManagedModelCatalog {
             upstreamRevision: Q35Resources.bonsai27B1BitUpstreamRevision,
             validationKind: .q35,
             estimatedDownloadBytes: Q35Resources.bonsai27B1BitEstimatedDownloadBytes,
-            defaultCLICommands: ["text chat", "api serve", "model benchmark chat"]
+            defaultCLICommands: ["text chat", "api serve", "model benchmark chat"],
+            apiProfile: .q36(
+                contextWindow: Q35Resources.bonsai27B1BitContextLength,
+                fixedReasoning: true
+            )
         ),
         ManagedModelSpec(
             id: Q35Resources.bonsai27B2BitModelId,
@@ -1237,7 +1676,11 @@ public enum ManagedModelCatalog {
             upstreamRevision: Q35Resources.bonsai27B2BitUpstreamRevision,
             validationKind: .q35,
             estimatedDownloadBytes: Q35Resources.bonsai27B2BitEstimatedDownloadBytes,
-            defaultCLICommands: ["text chat", "api serve", "model benchmark chat"]
+            defaultCLICommands: ["text chat", "api serve", "model benchmark chat"],
+            apiProfile: .q36(
+                contextWindow: Q35Resources.bonsai27B2BitContextLength,
+                fixedReasoning: true
+            )
         ),
         ManagedModelSpec(
             id: Q35Resources.ornith9BModelId,
@@ -1248,7 +1691,11 @@ public enum ManagedModelCatalog {
             upstreamRevision: Q35Resources.ornith9BUpstreamRevision,
             validationKind: .q35,
             estimatedDownloadBytes: Q35Resources.ornith9BEstimatedDownloadBytes,
-            defaultCLICommands: ["chat", "api serve", "agent start"]
+            defaultCLICommands: ["chat", "api serve", "agent start"],
+            apiProfile: .q36(
+                contextWindow: Q35Resources.defaultContextLength,
+                fixedReasoning: true
+            )
         ),
         ManagedModelSpec(
             id: Q35Resources.ornith35BMLXModelId,
@@ -1259,7 +1706,11 @@ public enum ManagedModelCatalog {
             validationKind: .q35,
             runtimeAutoDownloadAllowed: false,
             estimatedDownloadBytes: Q35Resources.ornith35BMLXEstimatedDownloadBytes,
-            defaultCLICommands: ["chat", "api serve", "agent start", "model benchmark code"]
+            defaultCLICommands: ["chat", "api serve", "agent start", "model benchmark code"],
+            apiProfile: .q36(
+                contextWindow: Q35Resources.defaultContextLength,
+                fixedReasoning: true
+            )
         ),
         ManagedModelSpec(
             id: AgentModelResources.qwen35NineBModelId,
@@ -1270,7 +1721,8 @@ public enum ManagedModelCatalog {
             upstreamRevision: AgentModelResources.qwen35NineBRevision,
             validationKind: .codegenGGUF,
             estimatedDownloadBytes: 5_680_522_464,
-            defaultCLICommands: ["api serve", "text code"]
+            defaultCLICommands: ["api serve", "text code"],
+            apiProfile: .textCode()
         ),
         ManagedModelSpec(
             id: NorthMiniCodeResources.modelId,
@@ -1281,7 +1733,11 @@ public enum ManagedModelCatalog {
             upstreamRevision: NorthMiniCodeResources.upstreamRevision,
             validationKind: .codegenGGUF,
             estimatedDownloadBytes: NorthMiniCodeResources.estimatedDownloadBytes,
-            defaultCLICommands: ["text code", "api serve", "agent start"]
+            defaultCLICommands: ["text code", "api serve", "agent start"],
+            apiProfile: .textCode(
+                contextWindow: NorthMiniCodeResources.runtimeContextLength,
+                maximumOutputTokens: NorthMiniCodeResources.maxOutputTokens
+            )
         ),
         ManagedModelSpec(
             id: Ornith35BCodeResources.modelId,
@@ -1292,7 +1748,11 @@ public enum ManagedModelCatalog {
             upstreamRevision: Ornith35BCodeResources.upstreamRevision,
             validationKind: .codegenGGUF,
             estimatedDownloadBytes: Ornith35BCodeResources.estimatedDownloadBytes,
-            defaultCLICommands: ["text code", "api serve", "agent start"]
+            defaultCLICommands: ["text code", "api serve", "agent start"],
+            apiProfile: .textCode(
+                contextWindow: Ornith35BCodeResources.runtimeContextLength,
+                maximumOutputTokens: Ornith35BCodeResources.maxOutputTokens
+            )
         ),
         ManagedModelSpec(
             // GGUF Qwen3.6-35B-A3B: the CUDA default chat model. Routes through
@@ -1312,7 +1772,8 @@ public enum ManagedModelCatalog {
             upstreamRevision: "main",
             validationKind: .codegenGGUF,
             estimatedDownloadBytes: 22 * 1_073_741_824,
-            defaultCLICommands: ["text chat", "api serve"]
+            defaultCLICommands: ["text chat", "api serve"],
+            apiProfile: .textCode()
         ),
         ManagedModelSpec(
             id: DeepseekV4FlashResources.defaultModelId,
@@ -1323,7 +1784,8 @@ public enum ManagedModelCatalog {
             upstreamRevision: DeepseekV4FlashResources.defaultRevision,
             validationKind: .deepseekV4FlashIMatrixGGUF,
             estimatedDownloadBytes: DeepseekV4FlashResources.defaultGGUFByteCount,
-            defaultCLICommands: ["api serve", "agent"]
+            defaultCLICommands: ["api serve", "agent"],
+            apiProfile: .deepseekV4Flash()
         ),
         ManagedModelSpec(
             id: LFM2Resources.defaultModelId,
@@ -1346,7 +1808,8 @@ public enum ManagedModelCatalog {
             validationKind: .lfm2,
             runtimeAutoDownloadAllowed: false,
             estimatedDownloadBytes: 10 * 1_073_741_824,
-            defaultCLICommands: ["text chat", "api serve"]
+            defaultCLICommands: ["text chat", "api serve"],
+            apiProfile: .lfm2()
         ),
         ManagedModelSpec(
             id: LFM2Resources.denseModelId,
@@ -1369,7 +1832,8 @@ public enum ManagedModelCatalog {
             validationKind: .lfm2,
             runtimeAutoDownloadAllowed: false,
             estimatedDownloadBytes: 1_601_108_788,
-            defaultCLICommands: ["text chat", "api serve"]
+            defaultCLICommands: ["text chat", "api serve"],
+            apiProfile: .lfm2()
         ),
         ManagedModelSpec(
             id: LFM2Resources.visionModelId,
@@ -1392,7 +1856,8 @@ public enum ManagedModelCatalog {
             validationKind: .lfm2,
             runtimeAutoDownloadAllowed: false,
             estimatedDownloadBytes: LFM2Resources.visionEstimatedDownloadBytes,
-            defaultCLICommands: ["text chat", "api serve"]
+            defaultCLICommands: ["text chat", "api serve"],
+            apiProfile: .lfm2(inputModalities: [.text, .image])
         ),
         ManagedModelSpec(
             id: "speech-tts-qwen3-nano",
@@ -1524,7 +1989,8 @@ public enum ManagedModelCatalog {
             validationKind: .codegenGGUF,
             aliasKind: .codegenGGUF,
             estimatedDownloadBytes: 48_410_992_032,
-            defaultCLICommands: ["text code"]
+            defaultCLICommands: ["text code"],
+            apiProfile: .textCode()
         ),
         ManagedModelSpec(
             id: "text-embed-qwen3-0.6b",
diff --git a/Sources/MereRunCore/RuntimeModelSettings.swift b/Sources/MereRunCore/RuntimeModelSettings.swift
index 4032d37e..be153e18 100644
--- a/Sources/MereRunCore/RuntimeModelSettings.swift
+++ b/Sources/MereRunCore/RuntimeModelSettings.swift
@@ -410,28 +410,7 @@ public struct RuntimeModelSettingsStore {
 
 public extension ManagedModelSpec {
     var defaultRuntimeServingEngine: RuntimeServingEngine? {
-        switch validationKind {
-        case .codegenGGUF:
-            return .textCode
-        case .gemma4, .gemma4Unified:
-            return .textChatGemma4
-        case .laguna:
-            return .textChatLaguna
-        case .q35:
-            return .textChatQ36
-        case .lfm2:
-            return .textChatLFM2
-        case .museGlimmer:
-            return .textChatMuseGlimmer
-        case .nemotronH:
-            return .textChatNemotronH
-        case .deepseekV4FlashIMatrixGGUF:
-            return .textChatDeepseekV4Flash
-        case .hfTextChat where id == ModelResolver.ModelID.mebot.rawValue:
-            return .textChatKlein
-        default:
-            return nil
-        }
+        apiProfile?.servingEngine
     }
 
     var isAPIServableRuntimeModel: Bool {
diff --git a/Tests/MereRunCLITests/APIServeCommandTests.swift b/Tests/MereRunCLITests/APIServeCommandTests.swift
index 6c455a24..acb9662d 100644
--- a/Tests/MereRunCLITests/APIServeCommandTests.swift
+++ b/Tests/MereRunCLITests/APIServeCommandTests.swift
@@ -519,6 +519,54 @@ final class APIServeCommandTests: XCTestCase {
         XCTAssertEqual(Set(response.data.map(\.owned_by)), Set(["mere.run"]))
     }
 
+    func testChatModelContractDescribesDeepSeekForHarnesses() throws {
+        let model = APIServerContract.chatModel(
+            id: DeepseekV4FlashResources.defaultModelId,
+            name: "DeepSeek V4 Flash",
+            profile: .deepseekV4Flash(),
+            contextWindow: 32_768,
+            maximumOutputTokens: 32_768,
+            createdAt: Date(timeIntervalSince1970: 123)
+        )
+
+        XCTAssertEqual(model.task, "chat.completions")
+        XCTAssertEqual(model.reasoning, true)
+        XCTAssertEqual(model.thinking_levels, ["off", "minimal", "low", "medium", "high", "xhigh"])
+        XCTAssertEqual(model.tool_call, true)
+        XCTAssertEqual(model.modalities, OpenAIModelModalities(input: ["text", "image"], output: ["text"]))
+        XCTAssertEqual(model.limit, OpenAIModelLimit(context: 32_768, output: 32_768))
+        XCTAssertEqual(model.openai_compat?.supports_developer_role, false)
+        XCTAssertEqual(model.openai_compat?.supports_reasoning_effort, true)
+        XCTAssertEqual(model.openai_compat?.supports_finish_reason, true)
+        XCTAssertEqual(model.openai_compat?.max_tokens_field, "max_tokens")
+        XCTAssertEqual(model.openai_compat?.thinking_format, "deepseek")
+        XCTAssertEqual(model.openai_compat?.thinking_level_map, ["minimal": "low"])
+        XCTAssertEqual(model.openai_compat?.requires_reasoning_content_on_assistant_messages, true)
+
+        let json = try XCTUnwrap(String(data: JSONEncoder().encode(model), encoding: .utf8))
+        XCTAssertTrue(json.contains("\"tool_call\":true"))
+        XCTAssertTrue(json.contains("\"thinking_levels\""))
+        XCTAssertTrue(json.contains("\"openai_compat\""))
+    }
+
+    func testCompanionModelContractLabelsNonChatTasks() throws {
+        let profile = try XCTUnwrap(
+            ManagedModelCatalog.apiProfile(for: ModelResolver.ModelID.qwen3Embedding.rawValue)
+        )
+        let embedding = APIServerContract.companionModel(
+            id: ModelResolver.ModelID.qwen3Embedding.rawValue,
+            profile: profile,
+            createdAt: Date(timeIntervalSince1970: 123)
+        )
+
+        XCTAssertEqual(embedding.task, "embeddings")
+        XCTAssertEqual(embedding.tool_call, false)
+        XCTAssertEqual(
+            embedding.modalities,
+            OpenAIModelModalities(input: ["text"], output: ["embedding"])
+        )
+    }
+
     func testEmbeddingRequestDecodesStringInputAndUnknownFields() throws {
         let data = """
         {
@@ -2590,6 +2638,24 @@ final class APIServeCommandTests: XCTestCase {
         }
     }
 
+    func testMuseReasoningEffortMapsToNativeStrength() throws {
+        let request = OpenAIChatRequest(
+            model: MuseGlimmerResources.modelId,
+            messages: [OpenAIChatMessage(role: "user", content: "hello")],
+            reasoning_effort: "high"
+        )
+
+        let chatRequest = try APIServerContract.chatRequest(
+            from: request,
+            fallbackLoraPath: nil,
+            contextSize: 4_096,
+            capabilities: RuntimeServingEngine.textChatMuseGlimmer.openAICompatibility,
+            servedModelID: MuseGlimmerResources.modelId
+        )
+
+        XCTAssertEqual(chatRequest.reasoningEffort, 0.8)
+    }
+
     func testStreamingUsageOptionHonorsCapabilities() throws {
         let request = OpenAIChatRequest(
             model: "mererun-test-model",
diff --git a/Tests/MereRunCLITests/RuntimeModelPoolTests.swift b/Tests/MereRunCLITests/RuntimeModelPoolTests.swift
index f2b89420..49b26022 100644
--- a/Tests/MereRunCLITests/RuntimeModelPoolTests.swift
+++ b/Tests/MereRunCLITests/RuntimeModelPoolTests.swift
@@ -208,10 +208,49 @@ final class RuntimeModelPoolTests: XCTestCase {
             settingsStore: RuntimeModelSettingsStore(modelsDir: root)
         )
 
-        let response = try await pool.modelsResponse(createdAt: Date(timeIntervalSince1970: 10))
+        let response = try await pool.modelsResponse(
+            serverContextSize: 8_192,
+            createdAt: Date(timeIntervalSince1970: 10)
+        )
 
         XCTAssertTrue(response.data.contains { $0.id == "custom.gguf" })
-        XCTAssertEqual(response.data.first { $0.id == "custom.gguf" }?.created, 10)
+        let model = try XCTUnwrap(response.data.first { $0.id == "custom.gguf" })
+        XCTAssertEqual(model.created, 10)
+        XCTAssertEqual(model.task, "chat.completions")
+        XCTAssertEqual(model.tool_call, false)
+        XCTAssertEqual(model.reasoning, false)
+        XCTAssertEqual(model.modalities, OpenAIModelModalities(input: ["text"], output: ["text"]))
+        XCTAssertEqual(model.limit, OpenAIModelLimit(context: 8_192, output: 4_096))
+    }
+
+    func testModelsResponseOverlaysRuntimeLimitsOnCatalogProfile() async throws {
+        let root = try makeTemporaryDirectory()
+        defer { try? FileManager.default.removeItem(at: root) }
+        let settingsStore = RuntimeModelSettingsStore(modelsDir: root)
+        try settingsStore.writeSettings(
+            RuntimeModelSettings(maxContextTokens: 8_192, maxTokens: 1_024),
+            for: Q35Resources.ornith9BModelId
+        )
+        let pool = RuntimeModelPool(
+            defaultModelID: Q35Resources.ornith9BModelId,
+            defaultEngine: .textChatQ36,
+            startupModelPath: nil,
+            settingsStore: settingsStore
+        )
+
+        let response = try await pool.modelsResponse(serverContextSize: 32_768)
+        let model = try XCTUnwrap(
+            response.data.first { $0.id == Q35Resources.ornith9BModelId }
+        )
+
+        XCTAssertEqual(model.limit, OpenAIModelLimit(context: 8_192, output: 1_024))
+        XCTAssertEqual(model.reasoning, true)
+        XCTAssertEqual(model.thinking_levels, ["high"])
+        XCTAssertEqual(model.tool_call, true)
+        XCTAssertEqual(
+            model.modalities,
+            OpenAIModelModalities(input: ["text", "image"], output: ["text"])
+        )
     }
 
     func testStatusReportsGemma4PrefixKVCacheCapabilityWhenEnabled() async throws {
diff --git a/Tests/MereRunCLITests/SetupCommandParsingTests.swift b/Tests/MereRunCLITests/SetupCommandParsingTests.swift
index 33331529..14c3bea7 100644
--- a/Tests/MereRunCLITests/SetupCommandParsingTests.swift
+++ b/Tests/MereRunCLITests/SetupCommandParsingTests.swift
@@ -47,10 +47,12 @@ final class SetupCommandParsingTests: XCTestCase {
             )
         )
 
-        let providerModel = SetupAgentRuntime.providerModel(for: recommendation)
+        let providerModel = try SetupAgentRuntime.providerModel(for: recommendation)
 
-        XCTAssertEqual(providerModel.id, AgentModelResources.qwen35NineBModelId)
+        XCTAssertEqual(providerModel.id, Q35Resources.ornith9BModelId)
         XCTAssertNotEqual(providerModel.id, CodeGenResources.defaultModelId)
+        XCTAssertTrue(providerModel.reasoning)
+        XCTAssertTrue(providerModel.toolCall)
     }
 
     func testDeepseekProviderMatchesServedContextAndStartupTimeout() throws {
@@ -66,7 +68,7 @@ final class SetupCommandParsingTests: XCTestCase {
         )
 
         let runtime = try SetupAgentRuntime.runtime(for: recommendation)
-        let providerModel = SetupAgentRuntime.providerModel(for: recommendation)
+        let providerModel = try SetupAgentRuntime.providerModel(for: recommendation)
 
         XCTAssertEqual(providerModel.contextWindow, DeepseekV4FlashResources.defaultContextLength)
         XCTAssertEqual(providerModel.maxTokens, DeepseekV4FlashResources.defaultContextLength)
@@ -89,13 +91,13 @@ final class SetupCommandParsingTests: XCTestCase {
                 .first { $0.id == NorthMiniCodeResources.modelId }
         )
 
-        let providerModel = SetupAgentRuntime.providerModel(for: recommendation)
+        let providerModel = try SetupAgentRuntime.providerModel(for: recommendation)
 
         XCTAssertEqual(providerModel.id, NorthMiniCodeResources.modelId)
         XCTAssertEqual(providerModel.contextWindow, NorthMiniCodeResources.runtimeContextLength)
         XCTAssertEqual(providerModel.maxTokens, NorthMiniCodeResources.maxOutputTokens)
         XCTAssertFalse(providerModel.reasoning)
-        XCTAssertTrue(recommendation.isStartableByMereRun)
+        XCTAssertFalse(recommendation.isStartableByMereRun)
         XCTAssertEqual(recommendation.servingEngine, .textCode)
     }
 
@@ -112,7 +114,7 @@ final class SetupCommandParsingTests: XCTestCase {
         )
 
         let runtime = try SetupAgentRuntime.runtime(for: recommendation)
-        let providerModel = SetupAgentRuntime.providerModel(for: recommendation)
+        let providerModel = try SetupAgentRuntime.providerModel(for: recommendation)
 
         XCTAssertEqual(runtime.engine, .textChatGemma4)
         XCTAssertEqual(providerModel.id, Gemma4Resources.twelveB4BitModelId)
@@ -134,13 +136,13 @@ final class SetupCommandParsingTests: XCTestCase {
                 .first { $0.id == Ornith35BCodeResources.modelId }
         )
 
-        let providerModel = SetupAgentRuntime.providerModel(for: recommendation)
+        let providerModel = try SetupAgentRuntime.providerModel(for: recommendation)
 
         XCTAssertEqual(providerModel.id, Ornith35BCodeResources.modelId)
         XCTAssertEqual(providerModel.contextWindow, Ornith35BCodeResources.runtimeContextLength)
         XCTAssertEqual(providerModel.maxTokens, Ornith35BCodeResources.maxOutputTokens)
         XCTAssertFalse(providerModel.reasoning)
-        XCTAssertTrue(recommendation.isStartableByMereRun)
+        XCTAssertFalse(recommendation.isStartableByMereRun)
         XCTAssertEqual(recommendation.servingEngine, .textCode)
     }
 
@@ -158,11 +160,13 @@ final class SetupCommandParsingTests: XCTestCase {
         )
 
         let runtime = try SetupAgentRuntime.runtime(for: recommendation)
-        let providerModel = SetupAgentRuntime.providerModel(for: recommendation)
+        let providerModel = try SetupAgentRuntime.providerModel(for: recommendation)
 
         XCTAssertEqual(runtime.engine, .textChatQ36)
         XCTAssertEqual(providerModel.id, Q35Resources.ornith9BModelId)
         XCTAssertEqual(providerModel.contextWindow, Q35Resources.defaultContextLength)
+        XCTAssertTrue(providerModel.reasoning)
+        XCTAssertTrue(providerModel.toolCall)
         XCTAssertTrue(recommendation.isStartableByMereRun)
         XCTAssertEqual(recommendation.servingEngine, .textChatQ35)
     }
@@ -173,15 +177,17 @@ final class SetupCommandParsingTests: XCTestCase {
         defer {
             try? FileManager.default.removeItem(at: home)
         }
+        let profile = try XCTUnwrap(
+            ManagedModelCatalog.apiProfile(for: Q35Resources.ornith9BModelId)
+        )
 
         let extensionURL = try PiAgentIntegration.writeLocalProviderExtension(
             host: "127.0.0.1",
             port: 8080,
             model: PiProviderModel(
-                id: AgentModelResources.qwen35NineBModelId,
-                name: "Qwen3.5 9B",
-                contextWindow: 32_768,
-                maxTokens: 4_096
+                id: Q35Resources.ornith9BModelId,
+                name: "Ornith 9B",
+                profile: profile
             ),
             homeDirectory: home,
             persistConfiguration: false
@@ -194,6 +200,15 @@ final class SetupCommandParsingTests: XCTestCase {
                 .path
         )
         XCTAssertTrue(FileManager.default.fileExists(atPath: extensionURL.path))
+        let extensionSource = try String(contentsOf: extensionURL, encoding: .utf8)
+        XCTAssertTrue(extensionSource.contains("@earendil-works/pi-coding-agent"))
+        XCTAssertTrue(extensionSource.contains("createProvider"))
+        XCTAssertTrue(extensionSource.contains("openAICompletionsApi"))
+        XCTAssertTrue(extensionSource.contains("const initialModels = await discoverModels"))
+        XCTAssertTrue(extensionSource.contains("fetchModels"))
+        XCTAssertTrue(extensionSource.contains("entry.tool_call === true"))
+        XCTAssertTrue(extensionSource.contains("input: [\"text\", \"image\"]"))
+        XCTAssertTrue(extensionSource.contains("supportsFinishReason: true"))
     }
 
     func testAgentStartModelIsOptional() throws {
@@ -293,7 +308,7 @@ final class SetupCommandParsingTests: XCTestCase {
         XCTAssertTrue(prompt.contains("Recommended setup-agent tier for this Mac"))
         XCTAssertTrue(prompt.contains("Selected setup-agent is recommended: true"))
         XCTAssertTrue(prompt.contains("DeepSeek V4 Flash is the preferred premier setup-agent tier"))
-        XCTAssertTrue(prompt.contains("smaller Qwen agents are alternatives"))
+        XCTAssertTrue(prompt.contains("smaller tool-capable native agents are alternatives"))
         XCTAssertTrue(prompt.contains("mere.run model capabilities --recommended"))
         XCTAssertTrue(prompt.contains("mere.run model list"))
         XCTAssertTrue(prompt.contains("Do not run demo scripts"))
@@ -301,7 +316,7 @@ final class SetupCommandParsingTests: XCTestCase {
         XCTAssertTrue(prompt.contains("Never pass `--allow-unsupported`"))
     }
 
-    func testAgentStartPrefersInstalledStartableAgentModel() throws {
+    func testAgentStartDoesNotTreatTextOnlyModelAsPiStartable() throws {
         let root = FileManager.default.temporaryDirectory
             .appendingPathComponent("mere-run-agent-start-\(UUID().uuidString)", isDirectory: true)
         try FileManager.default.createDirectory(at: root, withIntermediateDirectories: true)
@@ -324,7 +339,7 @@ final class SetupCommandParsingTests: XCTestCase {
             )
         )
 
-        XCTAssertEqual(recommendation?.id, AgentModelResources.qwen35NineBModelId)
+        XCTAssertNil(recommendation)
     }
 
     func testAgentStartPrefersInstalledDeepseekOverQwenCode() throws {
diff --git a/Tests/MereRunCoreTests/ManagedModelCatalogTests.swift b/Tests/MereRunCoreTests/ManagedModelCatalogTests.swift
index 3995a3f9..927d5864 100644
--- a/Tests/MereRunCoreTests/ManagedModelCatalogTests.swift
+++ b/Tests/MereRunCoreTests/ManagedModelCatalogTests.swift
@@ -42,6 +42,83 @@ final class ManagedModelCatalogTests: XCTestCase {
         XCTAssertNil(ModelResolver.ModelID(rawValue: "text-chat-q35-nano"))
     }
 
+    func testAPIServableModelsOwnCompleteCatalogProfiles() {
+        let expectedChatModels = ManagedModelCatalog.allSpecs.filter {
+            $0.defaultCLICommands.contains("api serve")
+                || $0.id == CodeGenResources.defaultModelId
+        }
+
+        XCTAssertFalse(expectedChatModels.isEmpty)
+        for spec in expectedChatModels {
+            guard let profile = spec.apiProfile else {
+                XCTFail("API-served model \(spec.id) is missing a catalog API profile.")
+                continue
+            }
+            XCTAssertEqual(profile.task, .chatCompletions, spec.id)
+            XCTAssertNotNil(profile.servingEngine, spec.id)
+            XCTAssertGreaterThan(profile.contextWindow ?? 0, 0, spec.id)
+            XCTAssertGreaterThan(profile.maximumOutputTokens ?? 0, 0, spec.id)
+        }
+    }
+
+    func testCatalogProfilesOwnHarnessSpecificCapabilities() throws {
+        let ornith = try XCTUnwrap(
+            ManagedModelCatalog.apiProfile(for: Q35Resources.ornith9BModelId)
+        )
+        XCTAssertEqual(ornith.contextWindow, Q35Resources.defaultContextLength)
+        XCTAssertEqual(ornith.maximumOutputTokens, 4_096)
+        XCTAssertEqual(ornith.thinkingLevels, [.high])
+        XCTAssertTrue(ornith.toolCall)
+        XCTAssertTrue(ornith.inputModalities.contains(.image))
+
+        let deepseek = try XCTUnwrap(
+            ManagedModelCatalog.apiProfile(for: DeepseekV4FlashResources.defaultModelId)
+        )
+        XCTAssertEqual(deepseek.compatibility.maxTokensField, .maxTokens)
+        XCTAssertEqual(deepseek.compatibility.thinkingFormat, .deepseek)
+        XCTAssertEqual(deepseek.thinkingLevelMap, [.minimal: .low])
+        XCTAssertFalse(deepseek.compatibility.supportsDeveloperRole)
+        XCTAssertTrue(deepseek.compatibility.supportsReasoningEffort)
+        XCTAssertTrue(deepseek.toolCall)
+
+        let muse = try XCTUnwrap(
+            ManagedModelCatalog.apiProfile(for: MuseGlimmerResources.modelId)
+        )
+        XCTAssertEqual(muse.reasoningEffortStrengths[.minimal], 0.1)
+        XCTAssertEqual(muse.reasoningEffortStrengths[.high], 0.8)
+        XCTAssertEqual(muse.reasoningEffortStrengths[.max], 1)
+    }
+
+    func testQ35OCRModelsAreNotChatRuntimeModels() throws {
+        let full = try XCTUnwrap(
+            ManagedModelCatalog.spec(for: Q35Resources.infinityParser2ProModelId)
+        )
+        let quantized = try XCTUnwrap(
+            ManagedModelCatalog.spec(for: Q35Resources.infinityParser2ProInt8ModelId)
+        )
+
+        XCTAssertNil(full.apiProfile)
+        XCTAssertNil(full.defaultRuntimeServingEngine)
+        XCTAssertNil(quantized.apiProfile)
+        XCTAssertNil(quantized.defaultRuntimeServingEngine)
+    }
+
+    func testCompanionAPIProfilesComeFromCatalog() throws {
+        let embedding = try XCTUnwrap(
+            ManagedModelCatalog.apiProfile(for: ModelResolver.ModelID.qwen3Embedding.rawValue)
+        )
+        XCTAssertEqual(embedding.task, .embeddings)
+        XCTAssertEqual(embedding.inputModalities, [.text])
+        XCTAssertEqual(embedding.outputModalities, [.embedding])
+
+        let imageEdit = try XCTUnwrap(
+            ManagedModelCatalog.apiProfile(for: QwenImageEditRepository.modelId)
+        )
+        XCTAssertEqual(imageEdit.task, .imageEdits)
+        XCTAssertEqual(imageEdit.inputModalities, [.text, .image])
+        XCTAssertEqual(imageEdit.outputModalities, [.image])
+    }
+
     func testAllRuntimeAutoDownloadSpecsHaveManagedSource() {
         for spec in ManagedModelCatalog.allSpecs where spec.runtimeAutoDownloadAllowed {
             XCTAssertTrue(
diff --git a/Tests/MereRunCoreTests/ManagedModelSupportTests.swift b/Tests/MereRunCoreTests/ManagedModelSupportTests.swift
index 5f287515..0d31ed8a 100644
--- a/Tests/MereRunCoreTests/ManagedModelSupportTests.swift
+++ b/Tests/MereRunCoreTests/ManagedModelSupportTests.swift
@@ -267,7 +267,7 @@ final class ManagedModelSupportTests: XCTestCase {
     }
 
 
-    func testNorthMiniCodeIsSupportedOnThirtyTwoGBAndStartable() throws {
+    func testNorthMiniCodeIsSupportedOnThirtyTwoGBButNotPiStartable() throws {
         let spec = try XCTUnwrap(ManagedModelCatalog.spec(for: NorthMiniCodeResources.modelId))
         let machine = MereRunMachineProfile(
             physicalMemoryBytes: 32 * 1_073_741_824,
@@ -283,7 +283,7 @@ final class ManagedModelSupportTests: XCTestCase {
         )
 
         XCTAssertTrue(report.isSupported)
-        XCTAssertTrue(recommendation.isStartableByMereRun)
+        XCTAssertFalse(recommendation.isStartableByMereRun)
         XCTAssertEqual(recommendation.servingEngine, .textCode)
     }
 
@@ -348,7 +348,7 @@ final class ManagedModelSupportTests: XCTestCase {
         XCTAssertEqual(recommendation.servingEngine, .textChatQ35)
     }
 
-    func testOrnith35BIsSupportedOnSixtyFourGBAndStartableThroughTextCode() throws {
+    func testOrnith35BIsSupportedOnSixtyFourGBButNotPiStartable() throws {
         let spec = try XCTUnwrap(ManagedModelCatalog.spec(for: Ornith35BCodeResources.modelId))
         let machine = MereRunMachineProfile(
             physicalMemoryBytes: 64 * 1_073_741_824,
@@ -364,7 +364,7 @@ final class ManagedModelSupportTests: XCTestCase {
         )
 
         XCTAssertTrue(report.isSupported)
-        XCTAssertTrue(recommendation.isStartableByMereRun)
+        XCTAssertFalse(recommendation.isStartableByMereRun)
         XCTAssertEqual(recommendation.servingEngine, .textCode)
     }
 
@@ -504,7 +504,7 @@ final class ManagedModelSupportTests: XCTestCase {
 
         let recommendation = try XCTUnwrap(MereRunAgentModelCatalog.recommendation(for: .tier, on: machine))
 
-        XCTAssertEqual(recommendation.id, AgentModelResources.qwen35NineBModelId)
+        XCTAssertEqual(recommendation.id, Q35Resources.ornith9BModelId)
         XCTAssertTrue(recommendation.isStartableByMereRun)
     }
 
@@ -601,7 +601,7 @@ final class ManagedModelSupportTests: XCTestCase {
         XCTAssertNil(MereRunAgentModelCatalog.recommendation(for: .tier, on: machine))
     }
 
-    func testAgentTierSelectsCoderOnLinuxWithEnoughMemory() throws {
+    func testAgentTierSelectsToolCapableQ36OnLinuxWithEnoughMemory() throws {
         let machine = MereRunMachineProfile(
             physicalMemoryBytes: 64 * 1_073_741_824,
             processorName: "Linux",
@@ -611,7 +611,7 @@ final class ManagedModelSupportTests: XCTestCase {
 
         let recommendation = try XCTUnwrap(MereRunAgentModelCatalog.recommendation(for: .tier, on: machine))
 
-        XCTAssertEqual(recommendation.id, CodeGenResources.defaultModelId)
+        XCTAssertEqual(recommendation.id, Q35Resources.q36NanoModelId)
         XCTAssertTrue(recommendation.isStartableByMereRun)
     }
 }
diff --git a/docs/cli.md b/docs/cli.md
index f9dcc020..64b851a9 100644
--- a/docs/cli.md
+++ b/docs/cli.md
@@ -2831,15 +2831,15 @@ swift run mere.run setup --mode manual
 
 Agent model choices:
 
-- `small`: `text-agent-qwen35-9b`, a Qwen3.5 9B Q4 GGUF setup agent for 16 GB machines
-- `tier`: the best supported local tier for this machine, currently 9B, Qwen3.6 nano, Qwen3-Coder Next, or DeepSeek V4 Flash on 96 GB+ machines
+- `small`: `text-agent-ornith-9b`, a tool-capable native OptiQ setup agent for 16 GB machines
+- `tier`: the best supported tool-capable local tier for this machine, currently Ornith 9B, Gemma 4, Qwen3.6 nano on Linux, or DeepSeek V4 Flash on 96 GB+ machines
 - `premier`: `text-agent-deepseek-v4-flash`, the preferred managed 96 GB+ setup-agent tier served by the bundled DS4 engine
 
 North Mini Code (`text-code-north-mini`) is available as a managed native GGUF
 coding model. It is pullable through `model pull`, can be served with
-`api serve --engine text-code --model text-code-north-mini`, and can be started
-through the Pi-backed `agent start` path like other `text-code` models once the
-installed llama.cpp runtime supports the `cohere2moe` architecture.
+`api serve --engine text-code --model text-code-north-mini`, and can be used
+for direct code sessions and evals. The `text-code` API lane rejects tool calls,
+so it is not exposed to Pi.
 
 Ornith (`text-agent-ornith-9b`) is available as an experimental native
 MLX/OptiQ coding-agent model. It uses the Qwen-family runtime, so serve it with
@@ -2871,7 +2871,6 @@ swift run mere.run agent onboard
 swift run mere.run agent onboard --pull-recommended --accept-model-license
 swift run mere.run agent onboard --install-pi --configure-pi
 swift run mere.run agent onboard --configure-pi --model text-agent-deepseek-v4-flash
-swift run mere.run agent onboard --configure-pi --model text-code-north-mini --port 8080
 swift run mere.run agent onboard --configure-pi --model text-agent-ornith-9b --port 8080
 ```
 
@@ -2893,7 +2892,7 @@ extension that the CLI will actually use.
 
 ### `mere.run agent install-pi`
 
-Install the latest `badlogic/pi-mono` release asset for the current macOS
+Install the latest `earendil-works/pi` release asset for the current macOS
 architecture into the mere.run application-support directory.
 
 ```bash
@@ -2902,9 +2901,9 @@ swift run mere.run agent install-pi
 
 ### `mere.run agent start`
 
-Start a local API server for a selected managed agent model and launch Pi
-against the `mere-run` provider. GGUF code models use `--engine text-code`,
-Qwen3.6 uses `--engine text-chat-q36`, and DeepSeek V4 Flash uses the DS4-backed
+Start a local API server for a selected tool-capable managed agent model and
+launch Pi against the native `mere-run` provider. Qwen-family models use a
+native chat engine and DeepSeek V4 Flash uses the DS4-backed
 `--engine text-chat-deepseek-v4-flash`. If `--model` is omitted, `agent start`
 uses the best installed startable setup agent first, then a valid persisted Pi
 provider model, then the current machine's startable hardware tier. On 96 GB+
diff --git a/docs/getting-started.md b/docs/getting-started.md
index 45649750..79362668 100644
--- a/docs/getting-started.md
+++ b/docs/getting-started.md
@@ -233,8 +233,8 @@ swift run mere.run setup
 
 The setup command offers a local Mere agent powered by Pi, a bring-your-own-agent
 handoff prompt for Claude/Codex, or manual commands. Use
-`--mode agent --agent-model small` to select the Qwen3.5 9B GGUF setup agent
-explicitly. On 96 GB+ Apple Silicon Macs, the hardware-tier and premier agent
+`--mode agent --agent-model small` to select the tool-capable native Ornith 9B
+setup agent explicitly. On 96 GB+ Apple Silicon Macs, the hardware-tier and premier agent
 path selects DeepSeek V4 Flash as the preferred setup agent. On Linux, install
 or provide Pi separately with `--pi-path` or PATH before using `--start`.
 
diff --git a/docs/model-sources.md b/docs/model-sources.md
index c07bb5e5..5af435c9 100644
--- a/docs/model-sources.md
+++ b/docs/model-sources.md
@@ -38,6 +38,13 @@ This is the authoritative public catalog list. It is kept in sync with
 from the runtime catalog used by `mere.run model list`,
 `mere.run model capabilities --all`, and `mere.run model pull`.
 
+API-served catalog entries also own a typed profile for their task, serving
+engine, input/output modalities, tool and structured-output support, reasoning
+levels and mappings, context/output limits, and OpenAI compatibility behavior.
+`/v1/models`, request validation, agent eligibility, and the Pi provider all
+project from that profile. Runtime aliases and configured limits are applied as
+an effective overlay; they are not a second capability catalog.
+
 <!-- managed-model-catalog:start -->
 | Catalog category | Model ID |
 | --- | --- |
@@ -262,9 +269,10 @@ existing installs and explicit local paths keep working:
 text-chat IDs listed here remain local-path-only until they have public Hugging
 Face sources.
 
-`text-agent-qwen35-9b` is the low-memory setup-agent model. It uses the public
+`text-agent-qwen35-9b` is a low-memory GGUF coding model. It uses the public
 Hugging Face source `unsloth/Qwen3.5-9B-GGUF` and selects
-`Qwen3.5-9B-Q4_K_M.gguf`.
+`Qwen3.5-9B-Q4_K_M.gguf`. Its `text-code` API lane does not expose tool calls;
+the small Pi setup-agent tier instead uses `text-agent-ornith-9b`.
 
 `text-code-north-mini` installs the Unsloth GGUF quant of Cohere Labs' North
 Mini Code 1.0 at the pinned catalog revision. North Mini Code is a 30B total /
diff --git a/docs/runtime/api-server.md b/docs/runtime/api-server.md
index 66fd70b5..b9888ba8 100644
--- a/docs/runtime/api-server.md
+++ b/docs/runtime/api-server.md
@@ -427,9 +427,19 @@ load/unload/settings endpoint. Sidecars still appear in `/v1/models` and in the
 `sidecars` object returned by `/runtime/status`.
 
 `GET /v1/models` returns installed API-servable chat managed IDs, configured
-aliases, and installed native sidecar model ids for embeddings, image, TTS, and
-ASR. Missing catalog models fail with an OpenAI-style error that tells the user
-to pull the model first.
+aliases, and installed native sidecars. In addition to the standard OpenAI
+fields, each entry can describe its `task`, `tool_call`, `reasoning`,
+`thinking_levels`, input/output `modalities`, context/output `limit`, and
+`openai_compat` dialect. Agent harnesses can therefore discover what the
+running server actually supports instead of inferring capabilities from a
+model name. Missing catalog models fail with an OpenAI-style error that tells
+the user to pull the model first.
+
+For managed models, these capabilities come from the typed API profile attached
+to the managed-model catalog entry. The runtime layer adds the request-facing
+ID or alias and applies configured context/output defaults to the reported
+limits. A server started from an explicit uncataloged path uses a conservative
+profile for its selected serving engine.
 
 ## OpenAI chat compatibility
 
diff --git a/docs/runtime/model-management.md b/docs/runtime/model-management.md
index ca446c31..383694dc 100644
--- a/docs/runtime/model-management.md
+++ b/docs/runtime/model-management.md
@@ -256,12 +256,16 @@ adapter ID and its published four-step schedule automatically.
 
 Guided onboarding for the shared model store and first local agent. The command
 offers a Pi-powered Mere agent, a BYOA prompt for Claude/Codex, or manual
-commands. The small local agent model is `text-agent-qwen35-9b`; hardware-tier
-setup can select Qwen3.6 nano, Qwen3-Coder Next, or DeepSeek V4 Flash. On 96 GB+
+commands. The small local agent model is the tool-capable
+`text-agent-ornith-9b`; hardware-tier setup can select Gemma 4, Qwen3.6 nano on
+Linux, or DeepSeek V4 Flash. On 96 GB+
 Apple Silicon Macs, `text-agent-deepseek-v4-flash` is the preferred managed
-setup-agent tier; smaller Qwen agent models are alternatives, not upgrades.
+setup-agent tier; smaller tool-capable native agents are alternatives, not
+upgrades.
 `text-code-north-mini` can be pulled, inspected, and run through the native
-GGUF code runtime for coding-agent comparisons against `text-code-qwen3`.
+GGUF code runtime for direct coding comparisons against `text-code-qwen3`.
+The `text-code` API lane rejects tool calls, so these models are not Pi setup
+agents.
 `text-agent-ornith-9b` can be pulled, inspected, and run through the native
 Qwen-family MLX/OptiQ runtime for coding-agent comparisons.
 `text-agent-ornith-35b-mlx` is a local-only converted MLX Q4 Ornith target; it
diff --git a/integrations/pi/README.md b/integrations/pi/README.md
new file mode 100644
index 00000000..50a1fea1
--- /dev/null
+++ b/integrations/pi/README.md
@@ -0,0 +1,30 @@
+# mere.run for Pi
+
+This Pi package registers a native `mere-run` provider and discovers compatible local models from the running mere.run API server. It reads the server's model task, tool-call support, reasoning levels, input modalities, context/output limits, and OpenAI compatibility flags instead of guessing from a model ID.
+
+## Use it
+
+Start mere.run first:
+
+```bash
+mere.run api serve --host 127.0.0.1 --port 8080
+```
+
+Install this package from a local checkout:
+
+```bash
+pi install /path/to/mere-run/integrations/pi
+pi --provider mere-run
+```
+
+The package defaults to `http://127.0.0.1:8080/v1`. Override the endpoint or API key when needed:
+
+```bash
+MERERUN_BASE_URL=http://127.0.0.1:9090/v1 \
+MERERUN_API_KEY=secret \
+pi --provider mere-run
+```
+
+Only `chat.completions` models that report `tool_call: true` are exposed to Pi. Image, audio, embedding, geometry, and text-only chat models remain available through the mere.run API but are not presented as coding-agent models.
+
+`mere.run agent start` remains the managed one-command path. It installs the current Pi release, starts the local server, writes an isolated provider extension with a selected-model fallback, and launches Pi.
diff --git a/integrations/pi/extensions/mere-run.ts b/integrations/pi/extensions/mere-run.ts
new file mode 100644
index 00000000..57bedccb
--- /dev/null
+++ b/integrations/pi/extensions/mere-run.ts
@@ -0,0 +1,140 @@
+import { createProvider, openAICompletionsApi, type Model } from "@earendil-works/pi-ai/compat";
+import type { ExtensionAPI } from "@earendil-works/pi-coding-agent";
+
+export type ThinkingLevel = "off" | "minimal" | "low" | "medium" | "high" | "xhigh" | "max";
+
+export interface MereRunModel {
+  id: string;
+  name?: string;
+  task?: string;
+  reasoning?: boolean;
+  thinking_levels?: ThinkingLevel[];
+  tool_call?: boolean;
+  modalities?: { input: string[]; output: string[] };
+  limit?: { context: number; output: number };
+  openai_compat?: {
+    supports_store: boolean;
+    supports_developer_role: boolean;
+    supports_reasoning_effort: boolean;
+    supports_usage_in_streaming: boolean;
+    supports_finish_reason: boolean;
+    max_tokens_field: "max_tokens" | "max_completion_tokens";
+    supports_strict_mode: boolean;
+    thinking_format?: "deepseek";
+    thinking_level_map?: Partial<Record<ThinkingLevel, string>>;
+    requires_reasoning_content_on_assistant_messages: boolean;
+  };
+}
+
+const thinkingLevels: ThinkingLevel[] = [
+  "off",
+  "minimal",
+  "low",
+  "medium",
+  "high",
+  "xhigh",
+  "max",
+];
+
+export function mapThinkingLevels(model: MereRunModel) {
+  if (!model.reasoning || !model.thinking_levels?.length) return undefined;
+  const supported = new Set(model.thinking_levels);
+  const overrides = model.openai_compat?.thinking_level_map ?? {};
+  const result: Partial<Record<ThinkingLevel, string | null>> = {};
+  for (const level of thinkingLevels) {
+    if (!supported.has(level)) result[level] = null;
+    else if (overrides[level]) result[level] = overrides[level];
+  }
+  return result;
+}
+
+export function mapModel(model: MereRunModel, baseUrl: string): Model<"openai-completions"> {
+  const compat = model.openai_compat;
+  return {
+    id: model.id,
+    name: model.name ?? model.id,
+    api: "openai-completions",
+    provider: "mere-run",
+    baseUrl,
+    reasoning: model.reasoning ?? false,
+    thinkingLevelMap: mapThinkingLevels(model),
+    input: (model.modalities?.input ?? ["text"]).filter(
+      (value): value is "text" | "image" => value === "text" || value === "image",
+    ),
+    cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0 },
+    contextWindow: model.limit?.context ?? 32_768,
+    maxTokens: model.limit?.output ?? 4_096,
+    compat: compat
+      ? {
+          supportsStore: compat.supports_store,
+          supportsDeveloperRole: compat.supports_developer_role,
+          supportsReasoningEffort: compat.supports_reasoning_effort,
+          supportsUsageInStreaming: compat.supports_usage_in_streaming,
+          supportsFinishReason: compat.supports_finish_reason,
+          maxTokensField: compat.max_tokens_field,
+          supportsStrictMode: compat.supports_strict_mode,
+          thinkingFormat: compat.thinking_format,
+          requiresReasoningContentOnAssistantMessages:
+            compat.requires_reasoning_content_on_assistant_messages,
+        }
+      : undefined,
+  };
+}
+
+export function selectPiModels(models: MereRunModel[], baseUrl: string) {
+  return models
+    .filter((model) => model.task === "chat.completions" && model.tool_call === true)
+    .map((model) => mapModel(model, baseUrl));
+}
+
+export async function discoverModels(
+  baseUrl: string,
+  apiKey: string,
+  signal: AbortSignal,
+): Promise<Model<"openai-completions">[]> {
+  const response = await fetch(`${baseUrl}/models`, {
+    headers: { Authorization: `Bearer ${apiKey}` },
+    signal,
+  });
+  if (!response.ok) {
+    throw new Error(`mere.run model discovery failed: HTTP ${response.status}`);
+  }
+  const payload = (await response.json()) as { data?: MereRunModel[] };
+  return selectPiModels(payload.data ?? [], baseUrl);
+}
+
+export default async function mereRunExtension(pi: ExtensionAPI) {
+  const baseUrl = process.env.MERERUN_BASE_URL ?? "http://127.0.0.1:8080/v1";
+  const fallbackAPIKey = process.env.MERERUN_API_KEY ?? "mere-run";
+  const initialModels = await discoverModels(
+    baseUrl,
+    fallbackAPIKey,
+    AbortSignal.timeout(2_000),
+  ).catch(() => []);
+
+  pi.registerProvider(
+    createProvider({
+      id: "mere-run",
+      name: "mere.run Local",
+      baseUrl,
+      auth: {
+        apiKey: {
+          name: "mere.run local API key",
+          async resolve({ ctx, credential }) {
+            const key = credential?.key ?? (await ctx.env("MERERUN_API_KEY")) ?? fallbackAPIKey;
+            return { auth: { apiKey: key }, source: "mere.run local" };
+          },
+        },
+      },
+      models: initialModels,
+      async fetchModels(context) {
+        const key =
+          context.credential?.type === "api_key"
+            ? context.credential.key ?? fallbackAPIKey
+            : fallbackAPIKey;
+        return discoverModels(baseUrl, key, context.signal);
+      },
+      api: openAICompletionsApi(),
+    }),
+  );
+}
diff --git a/integrations/pi/package.json b/integrations/pi/package.json
new file mode 100644
index 00000000..79b8149d
--- /dev/null
+++ b/integrations/pi/package.json
@@ -0,0 +1,50 @@
+{
+  "name": "@mere-run/pi",
+  "version": "0.1.0",
+  "description": "Dynamic mere.run provider for the Pi coding agent",
+  "type": "module",
+  "license": "Apache-2.0",
+  "keywords": [
+    "pi-package",
+    "pi-coding-agent",
+    "mere.run",
+    "local-ai"
+  ],
+  "files": [
+    "extensions",
+    "README.md"
+  ],
+  "pi": {
+    "extensions": [
+      "./extensions/mere-run.ts"
+    ]
+  },
+  "scripts": {
+    "test": "tsx --test test/*.test.ts",
+    "typecheck": "tsc --noEmit"
+  },
+  "peerDependencies": {
+    "@earendil-works/pi-ai": ">=0.84.2",
+    "@earendil-works/pi-coding-agent": ">=0.84.2"
+  },
+  "pnpm": {
+    "onlyBuiltDependencies": [
+      "esbuild"
+    ],
+    "ignoredBuiltDependencies": [
+      "@google/genai",
+      "protobufjs"
+    ],
+    "overrides": {
+      "@smithy/core": "3.32.0",
+      "@smithy/node-http-handler": "4.7.3"
+    }
+  },
+  "devDependencies": {
+    "@earendil-works/pi-ai": "0.84.2",
+    "@earendil-works/pi-coding-agent": "0.84.2",
+    "@types/node": "26.2.0",
+    "tsx": "4.23.12",
+    "typescript": "7.0.2"
+  }
+}
diff --git a/integrations/pi/pnpm-lock.yaml b/integrations/pi/pnpm-lock.yaml
new file mode 100644
index 00000000..cb620e7f
--- /dev/null
+++ b/integrations/pi/pnpm-lock.yaml
@@ -0,0 +1,1755 @@
+lockfileVersion: '9.0'
+
+settings:
+  autoInstallPeers: true
+  excludeLinksFromLockfile: false
+
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+        version: 26.2.0
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+        version: 4.23.12
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+        version: 7.0.2
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+
+  node-domexception@1.0.0: {}
+
+  node-fetch@3.3.2:
+    dependencies:
+      data-uri-to-buffer: 4.0.1
+      fetch-blob: 3.2.0
+      formdata-polyfill: 4.0.10
+
+  openai@6.40.0(ws@8.21.3):
+    optionalDependencies:
+      ws: 8.21.3
+
+  p-retry@4.6.2:
+    dependencies:
+      '@types/retry': 0.12.0
+      retry: 0.13.1
+
+  partial-json@0.1.7: {}
+
+  path-key@3.1.1: {}
+
+  path-scurry@2.0.2:
+    dependencies:
+      lru-cache: 11.5.2
+      minipass: 7.1.3
+
+  proper-lockfile@4.1.2:
+    dependencies:
+      graceful-fs: 4.2.11
+      retry: 0.12.0
+      signal-exit: 3.0.7
+
+  protobufjs@7.6.5:
+    dependencies:
+      '@protobufjs/aspromise': 1.1.2
+      '@protobufjs/base64': 1.1.2
+      '@protobufjs/codegen': 2.0.5
+      '@protobufjs/eventemitter': 1.1.1
+      '@protobufjs/fetch': 1.1.1
+      '@protobufjs/float': 1.0.2
+      '@protobufjs/path': 1.1.2
+      '@protobufjs/pool': 1.1.0
+      '@protobufjs/utf8': 1.1.2
+      '@types/node': 26.2.0
+      long: 5.3.2
+
+  retry@0.12.0: {}
+
+  retry@0.13.1: {}
+
+  safe-buffer@5.2.1: {}
+
+  semver@7.8.0: {}
+
+  shebang-command@2.0.0:
+    dependencies:
+      shebang-regex: 3.0.0
+
+  shebang-regex@3.0.0: {}
+
+  signal-exit@3.0.7: {}
+
+  ts-algebra@2.0.0: {}
+
+  tslib@2.8.1: {}
+
+  tsx@4.23.12:
+    dependencies:
+      esbuild: 0.28.2
+    optionalDependencies:
+      fsevents: 2.3.3
+
+  typebox@1.3.7: {}
+
+  typescript@7.0.2:
+    optionalDependencies:
+      '@typescript/typescript-aix-ppc64': 7.0.2
+      '@typescript/typescript-darwin-arm64': 7.0.2
+      '@typescript/typescript-darwin-x64': 7.0.2
+      '@typescript/typescript-freebsd-arm64': 7.0.2
+      '@typescript/typescript-freebsd-x64': 7.0.2
+      '@typescript/typescript-linux-arm': 7.0.2
+      '@typescript/typescript-linux-arm64': 7.0.2
+      '@typescript/typescript-linux-loong64': 7.0.2
+      '@typescript/typescript-linux-mips64el': 7.0.2
+      '@typescript/typescript-linux-ppc64': 7.0.2
+      '@typescript/typescript-linux-riscv64': 7.0.2
+      '@typescript/typescript-linux-s390x': 7.0.2
+      '@typescript/typescript-linux-x64': 7.0.2
+      '@typescript/typescript-netbsd-arm64': 7.0.2
+      '@typescript/typescript-netbsd-x64': 7.0.2
+      '@typescript/typescript-openbsd-arm64': 7.0.2
+      '@typescript/typescript-openbsd-x64': 7.0.2
+      '@typescript/typescript-sunos-x64': 7.0.2
+      '@typescript/typescript-win32-arm64': 7.0.2
+      '@typescript/typescript-win32-x64': 7.0.2
+
+  undici-types@8.3.0: {}
+
+  undici@8.9.0: {}
+
+  web-streams-polyfill@3.3.3: {}
+
+  which@2.0.2:
+    dependencies:
+      isexe: 2.0.0
+
+  ws@8.21.3: {}
+
+  yaml@2.9.0: {}
diff --git a/integrations/pi/test/mere-run.test.ts b/integrations/pi/test/mere-run.test.ts
new file mode 100644
index 00000000..758ea406
--- /dev/null
+++ b/integrations/pi/test/mere-run.test.ts
@@ -0,0 +1,99 @@
+import assert from "node:assert/strict";
+import { createServer } from "node:http";
+import test from "node:test";
+
+import {
+  discoverModels,
+  mapModel,
+  mapThinkingLevels,
+  selectPiModels,
+  type MereRunModel,
+} from "../extensions/mere-run.ts";
+
+const deepSeek: MereRunModel = {
+  id: "text-agent-deepseek-v4-flash",
+  name: "DeepSeek V4 Flash",
+  task: "chat.completions",
+  reasoning: true,
+  thinking_levels: ["off", "minimal", "low", "medium", "high", "xhigh"],
+  tool_call: true,
+  modalities: { input: ["text", "image", "audio"], output: ["text"] },
+  limit: { context: 32_768, output: 32_768 },
+  openai_compat: {
+    supports_store: false,
+    supports_developer_role: false,
+    supports_reasoning_effort: true,
+    supports_usage_in_streaming: true,
+    supports_finish_reason: true,
+    max_tokens_field: "max_tokens",
+    supports_strict_mode: false,
+    thinking_format: "deepseek",
+    thinking_level_map: { minimal: "low" },
+    requires_reasoning_content_on_assistant_messages: true,
+  },
+};
+
+test("maps self-described mere.run capabilities into Pi model metadata", () => {
+  const mapped = mapModel(deepSeek, "http://127.0.0.1:8080/v1");
+
+  assert.equal(mapped.provider, "mere-run");
+  assert.equal(mapped.contextWindow, 32_768);
+  assert.equal(mapped.maxTokens, 32_768);
+  assert.deepEqual(mapped.input, ["text", "image"]);
+  assert.equal(mapped.compat?.thinkingFormat, "deepseek");
+  assert.equal(mapped.compat?.maxTokensField, "max_tokens");
+  assert.equal(mapped.thinkingLevelMap?.minimal, "low");
+  assert.equal(mapped.thinkingLevelMap?.max, null);
+  assert.equal(mapped.thinkingLevelMap?.off, undefined);
+});
+
+test("keeps only chat models that can execute Pi tools", () => {
+  const selected = selectPiModels(
+    [
+      deepSeek,
+      { id: "plain-chat", task: "chat.completions", tool_call: false },
+      { id: "embedding", task: "embeddings", tool_call: false },
+    ],
+    "http://127.0.0.1:8080/v1",
+  );
+
+  assert.deepEqual(selected.map((model) => model.id), [deepSeek.id]);
+});
+
+test("discovers models from the live endpoint with bearer authentication", async () => {
+  const server = createServer((request, response) => {
+    assert.equal(request.url, "/v1/models");
+    assert.equal(request.headers.authorization, "Bearer local-secret");
+    response.setHeader("content-type", "application/json");
+    response.end(JSON.stringify({ data: [deepSeek] }));
+  });
+  await new Promise<void>((resolve) => server.listen(0, "127.0.0.1", resolve));
+
+  try {
+    const address = server.address();
+    assert(address && typeof address !== "string");
+    const models = await discoverModels(
+      `http://127.0.0.1:${address.port}/v1`,
+      "local-secret",
+      AbortSignal.timeout(1_000),
+    );
+    assert.deepEqual(models.map((model) => model.id), [deepSeek.id]);
+  } finally {
+    await new Promise<void>((resolve, reject) => {
+      server.close((error) => (error ? reject(error) : resolve()));
+    });
+  }
+});
+
+test("represents a fixed reasoning lane without inventing adjustable levels", () => {
+  const mapped = mapThinkingLevels({
+    id: "text-agent-ornith-9b",
+    reasoning: true,
+    thinking_levels: ["high"],
+  });
+
+  assert.equal(mapped?.high, undefined);
+  assert.equal(mapped?.off, null);
+  assert.equal(mapped?.low, null);
+  assert.equal(mapped?.xhigh, null);
+});
diff --git a/integrations/pi/tsconfig.json b/integrations/pi/tsconfig.json
new file mode 100644
index 00000000..5e1cefe9
--- /dev/null
+++ b/integrations/pi/tsconfig.json
@@ -0,0 +1,13 @@
+{
+  "compilerOptions": {
+    "target": "ES2022",
+    "module": "NodeNext",
+    "moduleResolution": "NodeNext",
+    "strict": true,
+    "noEmit": true,
+    "allowImportingTsExtensions": true,
+    "skipLibCheck": true,
+    "types": ["node"]
+  },
+  "include": ["extensions/**/*.ts", "test/**/*.ts"]
+}