examples

ATI Examples

These examples show how to integrate ATI with popular agentic AI SDKs. The core pattern is identical across all: the agent gets a shell/bash tool, a system prompt explains ati commands, and the agent calls ati via shell like a human would. No custom @tool wrappers around ATI — just shell access.

SDK Examples

SDK	Directory	Shell Mechanism	API Key	Default Model
Claude Agent SDK	claude-agent-sdk/	Built-in Bash tool	ANTHROPIC_API_KEY	claude-haiku-4-5
OpenAI Agents SDK	openai-agents-sdk/	@function_tool async shell	OPENAI_API_KEY	gpt-5.2
Codex CLI	codex/	Built-in (Codex IS a shell agent)	OPENAI_API_KEY	gpt-5.2
Google ADK	google-adk/	run_shell() function tool	GOOGLE_API_KEY	gemini-3-flash-preview
LangChain/LangGraph	langchain/	ShellTool (zero-config)	OPENAI_API_KEY	gpt-5.2
Pi	pi/	Built-in bashTool	ANTHROPIC_API_KEY	claude-haiku-4-5

Each Example Includes

File	Purpose
mcp_agent.py (or .ts)	Research agent using DeepWiki (MCP provider)
openapi_agent.py (or .ts)	Multi-source research using Crossref, arXiv, HN (OpenAPI + HTTP providers)
README.md	Setup, prerequisites, run commands
requirements.txt / package.json	Dependencies

Quick Start

# 1. Build ATI
cd /path/to/ati
cargo build --release

# 2. Set common env vars
export ATI_DIR=/path/to/ati
export PATH="/path/to/ati/target/release:$PATH"

# 3. Pick an SDK and run
cd examples/claude-agent-sdk    # or openai-agents-sdk, google-adk, langchain, codex, pi
pip install -r requirements.txt  # or `npm install` for pi/codex
export ANTHROPIC_API_KEY="..."   # or OPENAI_API_KEY, GOOGLE_API_KEY
python mcp_agent.py              # or `npx tsx mcp_agent.ts` for pi

Tools Used (All Free, No Auth Required)

All examples use the same set of free, unauthenticated tools:

Tool	Provider Type	What It Does
deepwiki__ask_question	MCP (Streamable HTTP)	AI-powered documentation for any GitHub repo
academic_search_arxiv	HTTP	arXiv preprint paper search
crossref__get_works	OpenAPI	Published academic papers with DOI metadata
hackernews_top_stories	HTTP	Hacker News top stories

The Pattern

Any AI Agent (any SDK)
  |
  +-- shell tool (Bash, ShellTool, run_shell, etc.)
       |
       +-- ati tool search <query>      ->  discover available tools
       +-- ati tool info <name>         ->  inspect tool schema
       +-- ati run <tool> --key val     ->  execute tool
             |
             +-- MCP provider    ->  JSON-RPC to remote MCP server
             +-- OpenAPI provider ->  auto-classified HTTP request
             +-- HTTP provider    ->  hand-written endpoint call
             |
             +-- structured response -> agent continues reasoning

The agent gets a shell tool and a system prompt. That's it. ATI handles auth injection, protocol bridging, scope enforcement, and response formatting. The agent doesn't know (or care) whether a tool is MCP, OpenAPI, or hand-written HTTP.