diff --git a/docs/nvidia-rag-mcp.md b/docs/nvidia-rag-mcp.md
index e03fb4de..517ea159 100644
--- a/docs/nvidia-rag-mcp.md
+++ b/docs/nvidia-rag-mcp.md
@@ -55,7 +55,7 @@ The MCP server supports three transport modes:
 - Python 3.11+ and dependencies:
 
 ```bash
-pip install -r nvidia_rag_mcp/requirements.txt
+pip install -r examples/nvidia_rag_mcp/requirements.txt
 ```
 
 ### 1) Start the MCP Server
@@ -67,7 +67,7 @@ From the repo root, start either transport:
 # Free port 8000 if needed (Linux)
 fuser -k 8000/tcp || true
 
-python nvidia_rag_mcp/mcp_server.py --transport sse --host 127.0.0.1 --port 8000
+python examples/nvidia_rag_mcp/mcp_server.py --transport sse --host 127.0.0.1 --port 8000
 ```
 
 #### streamable_http
@@ -75,7 +75,7 @@ python nvidia_rag_mcp/mcp_server.py --transport sse --host 127.0.0.1 --port 8000
 # Free port 8000 if needed (Linux)
 fuser -k 8000/tcp || true
 
-python nvidia_rag_mcp/mcp_server.py --transport streamable_http --host 127.0.0.1 --port 8000
+python examples/nvidia_rag_mcp/mcp_server.py --transport streamable_http --host 127.0.0.1 --port 8000
 ```
 
 ### 2) List available MCP tools
@@ -84,24 +84,24 @@ Use the `list` subcommand to see all exposed tools (RAG + Ingestor):
 
 SSE:
 ```bash
-python nvidia_rag_mcp/mcp_client.py list \
+python examples/nvidia_rag_mcp/mcp_client.py list \
   --transport=sse \
   --url=http://127.0.0.1:8000/sse
 ```
 
 streamable_http:
 ```bash
-python nvidia_rag_mcp/mcp_client.py list \
+python examples/nvidia_rag_mcp/mcp_client.py list \
   --transport=streamable_http \
   --url=http://127.0.0.1:8000/mcp
 ```
 
 stdio:
 ```bash
-python nvidia_rag_mcp/mcp_client.py list \
+python examples/nvidia_rag_mcp/mcp_client.py list \
   --transport=stdio \
   --command=python \
-  --args="nvidia_rag_mcp/mcp_server.py --transport stdio"
+  --args="examples/nvidia_rag_mcp/mcp_server.py --transport stdio"
 ```
 
 Expected tools:  
@@ -110,13 +110,13 @@ Expected tools:
 
 ### 3) Retriever tools
 
-The CLI lives at `nvidia_rag_mcp/mcp_client.py`. The examples below show all transports (SSE, streamable_http, stdio) for the retriever (RAG) tools.
+The CLI lives at `examples/nvidia_rag_mcp/mcp_client.py`. The examples below show all transports (SSE, streamable_http, stdio) for the retriever (RAG) tools.
 
 #### `generate`
 
 SSE:
 ```bash
-python nvidia_rag_mcp/mcp_client.py call \
+python examples/nvidia_rag_mcp/mcp_client.py call \
   --transport=sse \
   --url=http://127.0.0.1:8000/sse \
   --tool=generate \
@@ -125,7 +125,7 @@ python nvidia_rag_mcp/mcp_client.py call \
 
 streamable_http:
 ```bash
-python nvidia_rag_mcp/mcp_client.py call \
+python examples/nvidia_rag_mcp/mcp_client.py call \
   --transport=streamable_http \
   --url=http://127.0.0.1:8000/mcp \
   --tool=generate \
@@ -134,10 +134,10 @@ python nvidia_rag_mcp/mcp_client.py call \
 
 stdio:
 ```bash
-python nvidia_rag_mcp/mcp_client.py call \
+python examples/nvidia_rag_mcp/mcp_client.py call \
   --transport=stdio \
   --command=python \
-  --args="nvidia_rag_mcp/mcp_server.py --transport stdio" \
+  --args="examples/nvidia_rag_mcp/mcp_server.py --transport stdio" \
   --tool=generate \
   --json-args='{"messages":[{"role":"user","content":"Say \"ok\""}],"collection_names":["my_collection"]}'
 ```
@@ -146,7 +146,7 @@ python nvidia_rag_mcp/mcp_client.py call \
 
 SSE:
 ```bash
-python nvidia_rag_mcp/mcp_client.py call \
+python examples/nvidia_rag_mcp/mcp_client.py call \
   --transport=sse \
   --url=http://127.0.0.1:8000/sse \
   --tool=search \
@@ -155,7 +155,7 @@ python nvidia_rag_mcp/mcp_client.py call \
 
 streamable_http:
 ```bash
-python nvidia_rag_mcp/mcp_client.py call \
+python examples/nvidia_rag_mcp/mcp_client.py call \
   --transport=streamable_http \
   --url=http://127.0.0.1:8000/mcp \
   --tool=search \
@@ -164,10 +164,10 @@ python nvidia_rag_mcp/mcp_client.py call \
 
 stdio:
 ```bash
-python nvidia_rag_mcp/mcp_client.py call \
+python examples/nvidia_rag_mcp/mcp_client.py call \
   --transport=stdio \
   --command=python \
-  --args="nvidia_rag_mcp/mcp_server.py --transport stdio" \
+  --args="examples/nvidia_rag_mcp/mcp_server.py --transport stdio" \
   --tool=search \
   --json-args='{"query":"Tell me about Robert Frost''s poems","collection_names":["my_collection"],"reranker_top_k":2,"vdb_top_k":5,"enable_query_rewriting":false,"enable_reranker":true}'
 ```
@@ -176,7 +176,7 @@ python nvidia_rag_mcp/mcp_client.py call \
 
 SSE:
 ```bash
-python nvidia_rag_mcp/mcp_client.py call \
+python examples/nvidia_rag_mcp/mcp_client.py call \
   --transport=sse \
   --url=http://127.0.0.1:8000/sse \
   --tool=get_summary \
@@ -185,7 +185,7 @@ python nvidia_rag_mcp/mcp_client.py call \
 
 streamable_http:
 ```bash
-python nvidia_rag_mcp/mcp_client.py call \
+python examples/nvidia_rag_mcp/mcp_client.py call \
   --transport=streamable_http \
   --url=http://127.0.0.1:8000/mcp \
   --tool=get_summary \
@@ -194,10 +194,10 @@ python nvidia_rag_mcp/mcp_client.py call \
 
 stdio:
 ```bash
-python nvidia_rag_mcp/mcp_client.py call \
+python examples/nvidia_rag_mcp/mcp_client.py call \
   --transport=stdio \
   --command=python \
-  --args="nvidia_rag_mcp/mcp_server.py --transport stdio" \
+  --args="examples/nvidia_rag_mcp/mcp_server.py --transport stdio" \
   --tool=get_summary \
   --json-args='{"collection_name":"my_collection","file_name":"woods_frost.pdf","blocking":false,"timeout":60}'
 ```
@@ -210,7 +210,7 @@ Use these before/after the retriever tools to manage collections and documents i
 
 SSE:
 ```bash
-python nvidia_rag_mcp/mcp_client.py call \
+python examples/nvidia_rag_mcp/mcp_client.py call \
   --transport=sse --url=http://127.0.0.1:8000/sse \
   --tool=create_collections \
   --json-args='{"collection_names":["my_collection"]}'
@@ -218,7 +218,7 @@ python nvidia_rag_mcp/mcp_client.py call \
 
 streamable_http:
 ```bash
-python nvidia_rag_mcp/mcp_client.py call \
+python examples/nvidia_rag_mcp/mcp_client.py call \
   --transport=streamable_http --url=http://127.0.0.1:8000/mcp \
   --tool=create_collections \
   --json-args='{"collection_names":["my_collection"]}'
@@ -226,9 +226,9 @@ python nvidia_rag_mcp/mcp_client.py call \
 
 stdio:
 ```bash
-python nvidia_rag_mcp/mcp_client.py call \
+python examples/nvidia_rag_mcp/mcp_client.py call \
   --transport=stdio --command=python \
-  --args="nvidia_rag_mcp/mcp_server.py --transport stdio" \
+  --args="examples/nvidia_rag_mcp/mcp_server.py --transport stdio" \
   --tool=create_collections \
   --json-args='{"collection_names":["my_collection"]}'
 ```
@@ -237,7 +237,7 @@ python nvidia_rag_mcp/mcp_client.py call \
 
 SSE:
 ```bash
-python nvidia_rag_mcp/mcp_client.py call \
+python examples/nvidia_rag_mcp/mcp_client.py call \
   --transport=sse --url=http://127.0.0.1:8000/sse \
   --tool=list_collections \
   --json-args='{}'
@@ -245,7 +245,7 @@ python nvidia_rag_mcp/mcp_client.py call \
 
 streamable_http:
 ```bash
-python nvidia_rag_mcp/mcp_client.py call \
+python examples/nvidia_rag_mcp/mcp_client.py call \
   --transport=streamable_http --url=http://127.0.0.1:8000/mcp \
   --tool=list_collections \
   --json-args='{}'
@@ -253,9 +253,9 @@ python nvidia_rag_mcp/mcp_client.py call \
 
 stdio:
 ```bash
-python nvidia_rag_mcp/mcp_client.py call \
+python examples/nvidia_rag_mcp/mcp_client.py call \
   --transport=stdio --command=python \
-  --args="nvidia_rag_mcp/mcp_server.py --transport stdio" \
+  --args="examples/nvidia_rag_mcp/mcp_server.py --transport stdio" \
   --tool=list_collections \
   --json-args='{}'
 ```
@@ -264,7 +264,7 @@ python nvidia_rag_mcp/mcp_client.py call \
 
 SSE:
 ```bash
-python nvidia_rag_mcp/mcp_client.py call \
+python examples/nvidia_rag_mcp/mcp_client.py call \
   --transport=sse --url=http://127.0.0.1:8000/sse \
   --tool=upload_documents \
   --json-args='{"collection_name":"my_collection","file_paths":["data/multimodal/woods_frost.pdf"],"blocking":true,"generate_summary":true,"split_options":{"chunk_size":512,"chunk_overlap":150}}'
@@ -272,7 +272,7 @@ python nvidia_rag_mcp/mcp_client.py call \
 
 streamable_http:
 ```bash
-python nvidia_rag_mcp/mcp_client.py call \
+python examples/nvidia_rag_mcp/mcp_client.py call \
   --transport=streamable_http --url=http://127.0.0.1:8000/mcp \
   --tool=upload_documents \
   --json-args='{"collection_name":"my_collection","file_paths":["data/multimodal/woods_frost.pdf"],"blocking":true,"generate_summary":true,"split_options":{"chunk_size":512,"chunk_overlap":150}}'
@@ -280,9 +280,9 @@ python nvidia_rag_mcp/mcp_client.py call \
 
 stdio:
 ```bash
-python nvidia_rag_mcp/mcp_client.py call \
+python examples/nvidia_rag_mcp/mcp_client.py call \
   --transport=stdio --command=python \
-  --args="nvidia_rag_mcp/mcp_server.py --transport stdio" \
+  --args="examples/nvidia_rag_mcp/mcp_server.py --transport stdio" \
   --tool=upload_documents \
   --json-args='{"collection_name":"my_collection","file_paths":["data/multimodal/woods_frost.pdf"],"blocking":true,"generate_summary":true,"split_options":{"chunk_size":512,"chunk_overlap":150}}'
 ```
@@ -291,7 +291,7 @@ python nvidia_rag_mcp/mcp_client.py call \
 
 SSE:
 ```bash
-python nvidia_rag_mcp/mcp_client.py call \
+python examples/nvidia_rag_mcp/mcp_client.py call \
   --transport=sse --url=http://127.0.0.1:8000/sse \
   --tool=get_documents \
   --json-args='{"collection_name":"my_collection"}'
@@ -299,7 +299,7 @@ python nvidia_rag_mcp/mcp_client.py call \
 
 streamable_http:
 ```bash
-python nvidia_rag_mcp/mcp_client.py call \
+python examples/nvidia_rag_mcp/mcp_client.py call \
   --transport=streamable_http --url=http://127.0.0.1:8000/mcp \
   --tool=get_documents \
   --json-args='{"collection_name":"my_collection"}'
@@ -307,9 +307,9 @@ python nvidia_rag_mcp/mcp_client.py call \
 
 stdio:
 ```bash
-python nvidia_rag_mcp/mcp_client.py call \
+python examples/nvidia_rag_mcp/mcp_client.py call \
   --transport=stdio --command=python \
-  --args="nvidia_rag_mcp/mcp_server.py --transport stdio" \
+  --args="examples/nvidia_rag_mcp/mcp_server.py --transport stdio" \
   --tool=get_documents \
   --json-args='{"collection_name":"my_collection"}'
 ```
@@ -318,7 +318,7 @@ python nvidia_rag_mcp/mcp_client.py call \
 
 SSE:
 ```bash
-python nvidia_rag_mcp/mcp_client.py call \
+python examples/nvidia_rag_mcp/mcp_client.py call \
   --transport=sse --url=http://127.0.0.1:8000/sse \
   --tool=update_documents \
   --json-args='{"collection_name":"my_collection","file_paths":["data/multimodal/woods_frost.pdf"],"blocking":true,"generate_summary":false,"split_options":{"chunk_size":512,"chunk_overlap":150}}'
@@ -326,7 +326,7 @@ python nvidia_rag_mcp/mcp_client.py call \
 
 streamable_http:
 ```bash
-python nvidia_rag_mcp/mcp_client.py call \
+python examples/nvidia_rag_mcp/mcp_client.py call \
   --transport=streamable_http --url=http://127.0.0.1:8000/mcp \
   --tool=update_documents \
   --json-args='{"collection_name":"my_collection","file_paths":["data/multimodal/woods_frost.pdf"],"blocking":true,"generate_summary":false,"split_options":{"chunk_size":512,"chunk_overlap":150}}'
@@ -334,9 +334,9 @@ python nvidia_rag_mcp/mcp_client.py call \
 
 stdio:
 ```bash
-python nvidia_rag_mcp/mcp_client.py call \
+python examples/nvidia_rag_mcp/mcp_client.py call \
   --transport=stdio --command=python \
-  --args="nvidia_rag_mcp/mcp_server.py --transport stdio" \
+  --args="examples/nvidia_rag_mcp/mcp_server.py --transport stdio" \
   --tool=update_documents \
   --json-args='{"collection_name":"my_collection","file_paths":["data/multimodal/woods_frost.pdf"],"blocking":true,"generate_summary":false,"split_options":{"chunk_size":512,"chunk_overlap":150}}'
 ```
@@ -345,7 +345,7 @@ python nvidia_rag_mcp/mcp_client.py call \
 
 SSE:
 ```bash
-python nvidia_rag_mcp/mcp_client.py call \
+python examples/nvidia_rag_mcp/mcp_client.py call \
   --transport=sse --url=http://127.0.0.1:8000/sse \
   --tool=delete_documents \
   --json-args='{"collection_name":"my_collection","document_names":["woods_frost.pdf"]}'
@@ -353,7 +353,7 @@ python nvidia_rag_mcp/mcp_client.py call \
 
 streamable_http:
 ```bash
-python nvidia_rag_mcp/mcp_client.py call \
+python examples/nvidia_rag_mcp/mcp_client.py call \
   --transport=streamable_http --url=http://127.0.0.1:8000/mcp \
   --tool=delete_documents \
   --json-args='{"collection_name":"my_collection","document_names":["woods_frost.pdf"]}'
@@ -361,9 +361,9 @@ python nvidia_rag_mcp/mcp_client.py call \
 
 stdio:
 ```bash
-python nvidia_rag_mcp/mcp_client.py call \
+python examples/nvidia_rag_mcp/mcp_client.py call \
   --transport=stdio --command=python \
-  --args="nvidia_rag_mcp/mcp_server.py --transport stdio" \
+  --args="examples/nvidia_rag_mcp/mcp_server.py --transport stdio" \
   --tool=delete_documents \
   --json-args='{"collection_name":"my_collection","document_names":["woods_frost.pdf"]}'
 ```
@@ -372,7 +372,7 @@ python nvidia_rag_mcp/mcp_client.py call \
 
 SSE:
 ```bash
-python nvidia_rag_mcp/mcp_client.py call \
+python examples/nvidia_rag_mcp/mcp_client.py call \
   --transport=sse --url=http://127.0.0.1:8000/sse \
   --tool=update_collection_metadata \
   --json-args='{"collection_name":"my_collection","description":"Updated description","tags":["tag1","tag2"],"owner":"owner@example.com","business_domain":"demo","status":"Active"}'
@@ -380,7 +380,7 @@ python nvidia_rag_mcp/mcp_client.py call \
 
 streamable_http:
 ```bash
-python nvidia_rag_mcp/mcp_client.py call \
+python examples/nvidia_rag_mcp/mcp_client.py call \
   --transport=streamable_http --url=http://127.0.0.1:8000/mcp \
   --tool=update_collection_metadata \
   --json-args='{"collection_name":"my_collection","description":"Updated description","tags":["tag1","tag2"],"owner":"owner@example.com","business_domain":"demo","status":"Active"}'
@@ -388,9 +388,9 @@ python nvidia_rag_mcp/mcp_client.py call \
 
 stdio:
 ```bash
-python nvidia_rag_mcp/mcp_client.py call \
+python examples/nvidia_rag_mcp/mcp_client.py call \
   --transport=stdio --command=python \
-  --args="nvidia_rag_mcp/mcp_server.py --transport stdio" \
+  --args="examples/nvidia_rag_mcp/mcp_server.py --transport stdio" \
   --tool=update_collection_metadata \
   --json-args='{"collection_name":"my_collection","description":"Updated description","tags":["tag1","tag2"],"owner":"owner@example.com","business_domain":"demo","status":"Active"}'
 ```
@@ -399,7 +399,7 @@ python nvidia_rag_mcp/mcp_client.py call \
 
 SSE:
 ```bash
-python nvidia_rag_mcp/mcp_client.py call \
+python examples/nvidia_rag_mcp/mcp_client.py call \
   --transport=sse --url=http://127.0.0.1:8000/sse \
   --tool=update_document_metadata \
   --json-args='{"collection_name":"my_collection","document_name":"woods_frost.pdf","description":"Updated description","tags":["tag1","tag2"]}'
@@ -407,7 +407,7 @@ python nvidia_rag_mcp/mcp_client.py call \
 
 streamable_http:
 ```bash
-python nvidia_rag_mcp/mcp_client.py call \
+python examples/nvidia_rag_mcp/mcp_client.py call \
   --transport=streamable_http --url=http://127.0.0.1:8000/mcp \
   --tool=update_document_metadata \
   --json-args='{"collection_name":"my_collection","document_name":"woods_frost.pdf","description":"Updated description","tags":["tag1","tag2"]}'
@@ -415,9 +415,9 @@ python nvidia_rag_mcp/mcp_client.py call \
 
 stdio:
 ```bash
-python nvidia_rag_mcp/mcp_client.py call \
+python examples/nvidia_rag_mcp/mcp_client.py call \
   --transport=stdio --command=python \
-  --args="nvidia_rag_mcp/mcp_server.py --transport stdio" \
+  --args="examples/nvidia_rag_mcp/mcp_server.py --transport stdio" \
   --tool=update_document_metadata \
   --json-args='{"collection_name":"my_collection","document_name":"woods_frost.pdf","description":"Updated description","tags":["tag1","tag2"]}'
 ```
@@ -426,7 +426,7 @@ python nvidia_rag_mcp/mcp_client.py call \
 
 SSE:
 ```bash
-python nvidia_rag_mcp/mcp_client.py call \
+python examples/nvidia_rag_mcp/mcp_client.py call \
   --transport=sse --url=http://127.0.0.1:8000/sse \
   --tool=delete_collections \
   --json-args='{"collection_names":["my_collection"]}'
@@ -434,7 +434,7 @@ python nvidia_rag_mcp/mcp_client.py call \
 
 streamable_http:
 ```bash
-python nvidia_rag_mcp/mcp_client.py call \
+python examples/nvidia_rag_mcp/mcp_client.py call \
   --transport=streamable_http --url=http://127.0.0.1:8000/mcp \
   --tool=delete_collections \
   --json-args='{"collection_names":["my_collection"]}'
@@ -442,9 +442,9 @@ python nvidia_rag_mcp/mcp_client.py call \
 
 stdio:
 ```bash
-python nvidia_rag_mcp/mcp_client.py call \
+python examples/nvidia_rag_mcp/mcp_client.py call \
   --transport=stdio --command=python \
-  --args="nvidia_rag_mcp/mcp_server.py --transport stdio" \
+  --args="examples/nvidia_rag_mcp/mcp_server.py --transport stdio" \
   --tool=delete_collections \
   --json-args='{"collection_names":["my_collection"]}'
 ```
diff --git a/examples/README.md b/examples/README.md
new file mode 100644
index 00000000..8290bb49
--- /dev/null
+++ b/examples/README.md
@@ -0,0 +1,29 @@
+# NVIDIA RAG Examples
+
+This directory contains example integrations and extensions for NVIDIA RAG.
+
+## Examples
+
+| Example | Description | Documentation |
+|---------|-------------|---------------|
+| [rag_react_agent](./rag_react_agent/) | Integration with [NeMo Agent Toolkit (NAT)](https://github.com/NVIDIA/NeMo-Agent-Toolkit) providing RAG query and search capabilities for agent workflows | [README](./rag_react_agent/README.md) |
+| [nvidia_rag_mcp](./nvidia_rag_mcp/) | MCP (Model Context Protocol) server and client for exposing NVIDIA RAG capabilities to MCP-compatible applications | [Documentation](../docs/nvidia-rag-mcp.md) |
+
+## rag_react_agent
+
+This plugin integrates NVIDIA RAG with [NeMo Agent Toolkit](https://github.com/NVIDIA/NeMo-Agent-Toolkit), enabling intelligent agents to use RAG tools for document retrieval and question answering. It demonstrates:
+
+- Creating custom NAT tools that wrap NVIDIA RAG functionality
+- Using the React Agent workflow for intelligent tool selection
+
+See the [rag_react_agent README](./rag_react_agent/README.md) for setup and usage instructions.
+
+## nvidia_rag_mcp
+
+This example provides an MCP server and client that exposes NVIDIA RAG and Ingestor capabilities as MCP tools. It supports multiple transport modes (SSE, streamable HTTP, stdio) and enables MCP-compatible applications to:
+
+- Generate answers using the RAG pipeline
+- Search the vector database for relevant documents
+- Manage collections and documents in the vector database
+
+See the [MCP documentation](../docs/nvidia-rag-mcp.md) for detailed setup and usage instructions.
diff --git a/nvidia_rag_mcp/__init__.py b/examples/nvidia_rag_mcp/__init__.py
similarity index 100%
rename from nvidia_rag_mcp/__init__.py
rename to examples/nvidia_rag_mcp/__init__.py
diff --git a/nvidia_rag_mcp/mcp_client.py b/examples/nvidia_rag_mcp/mcp_client.py
similarity index 95%
rename from nvidia_rag_mcp/mcp_client.py
rename to examples/nvidia_rag_mcp/mcp_client.py
index 6224b87f..db4a991d 100644
--- a/nvidia_rag_mcp/mcp_client.py
+++ b/examples/nvidia_rag_mcp/mcp_client.py
@@ -300,16 +300,16 @@ def main() -> None:
     Main entry point for the MCP client CLI.
     Examples:
       List tools (SSE):
-        python nvidia_rag_mcp/mcp_client.py list --transport=sse --url=http://127.0.0.1:8000/sse
+        python examples/nvidia_rag_mcp/mcp_client.py list --transport=sse --url=http://127.0.0.1:8000/sse
       List tools (stdio):
-        python nvidia_rag_mcp/mcp_client.py list --transport=stdio --command=python \
-          --args="-m nvidia_rag_mcp.mcp_server --transport stdio"
+        python examples/nvidia_rag_mcp/mcp_client.py list --transport=stdio --command=python \
+          --args="examples/nvidia_rag_mcp/mcp_server.py --transport stdio"
       Call generate (streamable_http):
-        python nvidia_rag_mcp/mcp_client.py call --transport=streamable_http --url=http://127.0.0.1:8000/mcp \
+        python examples/nvidia_rag_mcp/mcp_client.py call --transport=streamable_http --url=http://127.0.0.1:8000/mcp \
           --tool=generate --json-args='{"messages":[{"role":"user","content":"Hi"}]}'
       Call upload_documents (stdio):
-        python nvidia_rag_mcp/mcp_client.py call --transport=stdio --command=python \
-          --args="-m nvidia_rag_mcp.mcp_server --transport stdio" \
+        python examples/nvidia_rag_mcp/mcp_client.py call --transport=stdio --command=python \
+          --args="examples/nvidia_rag_mcp/mcp_server.py --transport stdio" \
           --tool=upload_documents \
           --json-args='{"collection_name":"my_collection","file_paths":["/abs/path/file.pdf"]}'
     """
diff --git a/nvidia_rag_mcp/mcp_server.py b/examples/nvidia_rag_mcp/mcp_server.py
similarity index 99%
rename from nvidia_rag_mcp/mcp_server.py
rename to examples/nvidia_rag_mcp/mcp_server.py
index 5b619dea..ca9d4dbb 100644
--- a/nvidia_rag_mcp/mcp_server.py
+++ b/examples/nvidia_rag_mcp/mcp_server.py
@@ -815,9 +815,9 @@ def main() -> None:
     Main entry point for the MCP server.
     Examples:
       SSE:
-        python nvidia_rag_mcp/mcp_server.py --transport sse
+        python examples/nvidia_rag_mcp/mcp_server.py --transport sse
       streamable_http:
-        python nvidia_rag_mcp/mcp_server.py --transport streamable_http
+        python examples/nvidia_rag_mcp/mcp_server.py --transport streamable_http
     """
     parser = argparse.ArgumentParser(description="NVIDIA RAG MCP server")
     parser.add_argument("--transport", choices=["sse", "streamable_http", "stdio"], help="Transport mode")
diff --git a/nvidia_rag_mcp/requirements.txt b/examples/nvidia_rag_mcp/requirements.txt
similarity index 100%
rename from nvidia_rag_mcp/requirements.txt
rename to examples/nvidia_rag_mcp/requirements.txt
diff --git a/examples/rag_react_agent/README.md b/examples/rag_react_agent/README.md
new file mode 100644
index 00000000..9bd3a5e8
--- /dev/null
+++ b/examples/rag_react_agent/README.md
@@ -0,0 +1,252 @@
+# Building Agentic RAG with NeMo Agent Toolkit
+
+This example demonstrates how to build intelligent agents that leverage **NVIDIA RAG** capabilities using [NeMo Agent Toolkit (NAT)](https://github.com/NVIDIA/NeMo-Agent-Toolkit). The agent can autonomously decide when and how to query your document knowledge base.
+
+## Overview
+
+This example shows how to:
+
+1. **Expose RAG as agent tools** - Wrap NVIDIA RAG query and search capabilities as tools that agents can use
+2. **Build a ReAct agent** - Use NAT's ReAct workflow to create an agent that reasons about when to use RAG
+
+The ReAct (Reason + Act) agent pattern enables the LLM to iteratively reason about which tools to use based on the user's query, making it ideal for building conversational AI applications with document retrieval capabilities.
+
+## Prerequisites
+
+- Python 3.11+
+- Access to NVIDIA AI endpoints (API key required)
+- **Data ingested into Milvus** - Complete the [rag_library_usage.ipynb](../../notebooks/rag_library_usage.ipynb) notebook to set up Milvus and ingest documents before running this example
+
+## Quick Start
+
+All commands should be run from the `examples/rag_react_agent/` directory.
+
+### 1. Set Environment Variables
+
+```bash
+# Required: NVIDIA API key for embeddings, reranking, and LLM
+export NVIDIA_API_KEY="your-nvidia-api-key"
+
+# Optional: If using custom endpoints
+# export NVIDIA_BASE_URL="https://integrate.api.nvidia.com/v1"
+```
+
+### 2. Configure Vector Database Endpoint
+
+By default, the example connects to Milvus at `http://localhost:19530`. You can configure this in two ways:
+
+**Option A: Environment Variable (takes precedence)**
+
+```bash
+# For standard Milvus server
+# export APP_VECTORSTORE_URL="http://localhost:19530"
+
+# Or for a remote Milvus instance
+# export APP_VECTORSTORE_URL="http://milvus-host:19530"
+```
+
+**Option B: Update config.yml**
+
+Edit `src/rag_react_agent/configs/config.yml` and update the `vdb_endpoint` field:
+
+```yaml
+functions:
+  rag_query:
+    vdb_endpoint: "http://localhost:19530"  # Your Milvus endpoint
+  rag_search:
+    vdb_endpoint: "http://localhost:19530"  # Your Milvus endpoint
+```
+
+> **Note**: If you have followed rag_library_lite_usage.ipynb notebook and have a setup using milvus-lite, provide an absolute path to the `.db` file (e.g., `/home/user/data/milvus.db`).
+
+### 3. Install Dependencies and Run the Agent
+
+```bash
+# From examples/rag_react_agent/ directory
+# Install all dependencies including nvidia-rag and NeMo Agent Toolkit
+uv sync
+
+# Activate the virtual environment
+source .venv/bin/activate
+```
+
+## Usage
+
+### Running the RAG Agent
+
+The example uses NAT's **ReAct Agent** workflow, which enables the LLM to reason about which RAG tools to use based on the user's query.
+
+```bash
+# From examples/rag_react_agent/ directory with .venv activated
+nat run --config_file src/rag_react_agent/configs/config.yml --input "what is giraffe doing?"
+```
+
+### Example Queries
+
+Try different queries to see how the agent decides which tool to use:
+
+```bash
+# Query that triggers rag_query (generates a response using retrieved documents)
+nat run --config_file src/rag_react_agent/configs/config.yml --input "Summarize the main themes of the documents"
+
+# Query that triggers rag_search (returns relevant document chunks)
+nat run --config_file src/rag_react_agent/configs/config.yml --input "Find all animals mentioned in documents"
+```
+
+### Expected Output
+
+When running successfully, you'll see the agent's reasoning process:
+
+```
+Configuration Summary:
+--------------------
+Workflow Type: react_agent
+Number of Functions: 3
+Number of LLMs: 1
+
+------------------------------
+[AGENT]
+Agent input: what is giraffe doing?
+Agent's thoughts: 
+Thought: I don't have any information about what giraffe is doing. 
+
+Action: rag_query 
+Action Input: {'query': 'giraffe current activity'}
+------------------------------
+
+------------------------------
+[AGENT]
+Calling tools: rag_query
+Tool's input: {'query': 'giraffe current activity'}
+Tool's response: 
+Driving a car at the beach
+------------------------------
+
+------------------------------
+[AGENT]
+Agent input: what is giraffe doing?
+Agent's thoughts: 
+Thought: I now know the final answer 
+Final Answer: Giraffe is driving a car at the beach.
+------------------------------
+
+--------------------------------------------------
+Workflow Result:
+['Giraffe is driving a car at the beach.']
+--------------------------------------------------
+```
+
+## Configuration
+
+The configuration file at `src/rag_react_agent/configs/config.yml` defines the RAG tools and agent workflow:
+
+```yaml
+functions:
+  # RAG Query Tool - Queries documents and returns LLM or VLM Generated response
+  rag_query:
+    _type: nvidia_rag_query
+    # Ensure collection_name matches with the collection name used in the rag library notebook.
+    collection_names: ["test_library"]    # Milvus collection names
+    vdb_endpoint: "http://localhost:19530" # Milvus endpoint URL
+
+  # RAG Search Tool - Searches for relevant document chunks
+  rag_search:
+    _type: nvidia_rag_search
+    collection_names: ["test_library"]
+    vdb_endpoint: "http://localhost:19530"
+    reranker_top_k: 3                     # Number of results after reranking
+    vdb_top_k: 20                         # Number of results from vector search
+
+  # Utility tool for date/time queries
+  current_datetime:
+    _type: current_datetime
+
+llms:
+  nim_llm:
+    _type: nim
+    model_name: meta/llama-3.1-70b-instruct
+    temperature: 0.0
+
+# ReAct Agent workflow - enables the LLM to reason about tool usage
+workflow:
+  _type: react_agent
+  tool_names:
+    - rag_query
+    - rag_search
+    - current_datetime
+  llm_name: nim_llm
+  verbose: true                           # Shows agent reasoning process
+```
+
+### RAG Tools
+
+| Tool | Type | Description |
+|------|------|-------------|
+| `rag_query` | `nvidia_rag_query` | Queries documents and returns an AI-generated response based on retrieved context |
+| `rag_search` | `nvidia_rag_search` | Searches for relevant document chunks without generating a response |
+
+### Tool Configuration Options
+
+#### `nvidia_rag_query`
+
+| Parameter | Description | Default |
+|-----------|-------------|---------|
+| `collection_names` | List of Milvus collection names to query | `[]` |
+| `vdb_endpoint` | Vector database endpoint URL or absolute path to Milvus Lite `.db` file | `"http://localhost:19530"` |
+
+#### `nvidia_rag_search`
+
+| Parameter | Description | Default |
+|-----------|-------------|---------|
+| `collection_names` | List of Milvus collection names to search | `[]` |
+| `vdb_endpoint` | Vector database endpoint URL or absolute path to Milvus Lite `.db` file | `"http://localhost:19530"` |
+| `reranker_top_k` | Number of results to return after reranking | `10` |
+| `vdb_top_k` | Number of results to retrieve before reranking | `100` |
+
+## Troubleshooting
+
+### Error: Function type `nvidia_rag_query` not found
+
+The tools are not registered. Ensure you've installed the package:
+
+```bash
+# From examples/rag_react_agent/ directory
+uv sync
+source .venv/bin/activate
+```
+
+### Error: Token limit exceeded
+
+If you encounter token limit errors, reduce the number of results:
+
+```yaml
+rag_search:
+  _type: nvidia_rag_search
+  reranker_top_k: 1    # Reduce from 3
+  vdb_top_k: 10        # Reduce from 20
+```
+
+This commonly occurs when documents contain large base64-encoded images.
+
+### Error: NVIDIA API key not set
+
+```bash
+export NVIDIA_API_KEY="your-api-key"
+```
+
+### Error: Connection to Milvus failed
+
+Ensure Milvus is running and accessible at the configured endpoint. If you followed the [rag_library_usage.ipynb](../../notebooks/rag_library_usage.ipynb) notebook, Milvus should be running at `http://localhost:19530`.
+
+```bash
+# Check if Milvus is running
+docker ps | grep milvus
+```
+
+## Learn More
+
+- [NeMo Agent Toolkit Documentation](https://docs.nvidia.com/nemo/agent-toolkit/latest/)
+
+## License
+
+Apache-2.0
diff --git a/examples/rag_react_agent/pyproject.toml b/examples/rag_react_agent/pyproject.toml
new file mode 100644
index 00000000..141a49e0
--- /dev/null
+++ b/examples/rag_react_agent/pyproject.toml
@@ -0,0 +1,58 @@
+[build-system]
+build-backend = "setuptools.build_meta"
+requires = ["setuptools >= 64", "setuptools-scm>=8"]
+
+
+[tool.setuptools.packages.find]
+where = ["src"]
+include = ["rag_react_agent*"]
+
+
+[tool.setuptools_scm]
+git_describe_command = "git describe --long --first-parent"
+root = "../.."
+
+
+[project]
+name = "rag-react-agent"
+dynamic = ["version"]
+dependencies = [
+  # Keep package version constraints as open as possible to avoid conflicts with other packages. Always define a minimum
+  # version when adding a new package. If unsure, default to using `~=` instead of `==`. Does not apply to nvidia-nat packages.
+  # Keep sorted!!!
+  "langgraph>=0.2",  # Required for react_agent workflow
+  "langchain_classic",
+  "nvidia-nat>=1.5.0a0,<2.0",  # Allow pre-release versions
+  "nvidia-nat-langchain>=1.5.0a0,<2.0",  # Allow pre-release versions
+  "nvidia-rag[rag]~=2.4",
+]
+requires-python = ">=3.11,<3.14"
+description = "RAG React Agent example using NVIDIA RAG with NeMo Agent Toolkit"
+keywords = ["ai", "rag", "agents"]
+license = { text = "Apache-2.0" }
+authors = [{ name = "NVIDIA Corporation" }]
+maintainers = [{ name = "NVIDIA Corporation" }]
+classifiers = [
+  "Programming Language :: Python",
+  "Programming Language :: Python :: 3.11",
+  "Programming Language :: Python :: 3.12",
+  "Programming Language :: Python :: 3.13",
+]
+
+[project.urls]
+documentation = "https://docs.nvidia.com/nemo/agent-toolkit/latest/"
+source = "https://github.com/NVIDIA/NeMo-Agent-Toolkit"
+
+
+[tool.uv]
+managed = true
+config-settings = { editable_mode = "compat" }
+prerelease = "allow"  # nvidia-nat packages are currently pre-release only
+
+
+[tool.uv.sources]
+nvidia-rag = { path = "../..", editable = true }
+
+
+[project.entry-points.'nat.components']
+nat_rag = "rag_react_agent.register"
diff --git a/examples/rag_react_agent/src/rag_react_agent/__init__.py b/examples/rag_react_agent/src/rag_react_agent/__init__.py
new file mode 100644
index 00000000..1312ed32
--- /dev/null
+++ b/examples/rag_react_agent/src/rag_react_agent/__init__.py
@@ -0,0 +1,16 @@
+# SPDX-FileCopyrightText: Copyright (c) 2025-2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""NVIDIA RAG integration for NeMo Agent Toolkit."""
diff --git a/examples/rag_react_agent/src/rag_react_agent/configs/config.yml b/examples/rag_react_agent/src/rag_react_agent/configs/config.yml
new file mode 100644
index 00000000..67bf99a1
--- /dev/null
+++ b/examples/rag_react_agent/src/rag_react_agent/configs/config.yml
@@ -0,0 +1,56 @@
+# SPDX-FileCopyrightText: Copyright (c) 2025-2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+# NVIDIA RAG Integration - Sample Configuration
+# This configuration demonstrates how to use NVIDIA RAG tools with NeMo Agent Toolkit
+
+# RAG configuration file path (used by nvidia_rag library)
+# Make sure this file exists and is properly configured for your environment
+# See: https://github.com/NVIDIA-AI-Blueprints/rag/blob/main/notebooks/config.yaml
+
+functions:
+  # RAG Query Tool - Query documents and get AI-generated responses
+  rag_query:
+    _type: nvidia_rag_query
+    collection_names: ["test_library"]
+    vdb_endpoint: "http://localhost:19530"
+
+  # RAG Search Tool - Search for relevant document chunks
+  rag_search:
+    _type: nvidia_rag_search
+    collection_names: ["test_library"]
+    vdb_endpoint: "http://localhost:19530"
+    reranker_top_k: 3  # Reduced to avoid token limit issues with large documents
+    vdb_top_k: 20
+
+  # Utility tool
+  current_datetime:
+    _type: current_datetime
+
+llms:
+  nim_llm:
+    _type: nim
+    model_name: meta/llama-3.1-70b-instruct
+    temperature: 0.0
+
+workflow:
+  _type: react_agent
+  tool_names:
+    - rag_query
+    - rag_search
+    - current_datetime
+  llm_name: nim_llm
+  verbose: true
+  parse_agent_response_max_retries: 3
diff --git a/examples/rag_react_agent/src/rag_react_agent/register.py b/examples/rag_react_agent/src/rag_react_agent/register.py
new file mode 100644
index 00000000..327d980e
--- /dev/null
+++ b/examples/rag_react_agent/src/rag_react_agent/register.py
@@ -0,0 +1,213 @@
+# SPDX-FileCopyrightText: Copyright (c) 2025-2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""NVIDIA RAG query and search functions for NeMo Agent Toolkit."""
+
+import json
+import logging
+import os
+
+from pydantic import Field
+
+from nat.builder.builder import Builder
+from nat.builder.function_info import FunctionInfo
+from nat.cli.register_workflow import register_function
+from nat.data_models.function import FunctionBaseConfig
+
+logger = logging.getLogger(__name__)
+
+def _configure_nvidia_rag_logging(level: int = logging.WARNING) -> None:
+    """Configure logging level for nvidia_rag package to reduce verbosity."""
+    for name in logging.root.manager.loggerDict:
+        if name == "nvidia_rag" or name.startswith("nvidia_rag."):
+            logging.getLogger(name).setLevel(level)
+
+class NvidiaRAGQueryConfig(FunctionBaseConfig, name="nvidia_rag_query"):
+    """
+    Tool that queries documents using NVIDIA RAG.
+    Sends a chat-style query to the RAG system using configured models and endpoints.
+    """
+
+    config_file: str = Field(
+        default="config.yaml",
+        description="Path to the NVIDIA RAG configuration YAML file.",
+    )
+    collection_names: list[str] = Field(
+        default_factory=list,
+        description="List of collection names to query from.",
+    )
+    vdb_endpoint: str = Field(
+        default="http://localhost:19530",
+        description="Vector database endpoint URL.",
+    )
+
+
+@register_function(config_type=NvidiaRAGQueryConfig)
+async def nvidia_rag_query(config: NvidiaRAGQueryConfig, builder: Builder):
+    """Register the NVIDIA RAG query tool."""
+
+    from nvidia_rag import NvidiaRAG
+    from nvidia_rag.utils.configuration import NvidiaRAGConfig
+
+    # Configure nvidia_rag logging to reduce verbosity
+    _configure_nvidia_rag_logging(logging.WARNING)
+
+    # Initialize RAG config - use defaults and override with NAT config values
+    rag_config = NvidiaRAGConfig()
+    rag_config.vector_store.url = os.environ.get("APP_VECTORSTORE_URL", config.vdb_endpoint)
+    logger.info(f"Vector store URL: {rag_config.vector_store.url}")
+    rag = NvidiaRAG(config=rag_config)
+
+    async def _nvidia_rag_query(query: str) -> str:
+        """Query documents using NVIDIA RAG and return a generated response.
+
+        This tool sends a query to the RAG system which retrieves relevant documents
+        from the vector database and uses an LLM to generate a response.
+
+        Args:
+            query: The question or query to ask the RAG system.
+
+        Returns:
+            The generated response from the RAG system based on retrieved documents.
+        """
+        try:
+            response = await rag.generate(
+                messages=[{"role": "user", "content": query}],
+                use_knowledge_base=True,
+                collection_names=config.collection_names,
+            )
+
+            if response.status_code != 200:
+                return f"Error: RAG query failed with status code {response.status_code}"
+
+            # Extract the response content from the streaming generator
+            full_response = []
+            async for chunk in response.generator:
+                if chunk.startswith("data: "):
+                    chunk = chunk[len("data: "):].strip()
+                if not chunk:
+                    continue
+                try:
+                    data = json.loads(chunk)
+                    choices = data.get("choices", [])
+                    if choices:
+                        delta = choices[0].get("delta", {})
+                        text = delta.get("content")
+                        if not text:
+                            message = choices[0].get("message", {})
+                            text = message.get("content", "")
+                        if text:
+                            full_response.append(text)
+                except json.JSONDecodeError:
+                    continue
+
+            return "".join(full_response) if full_response else "No response generated."
+
+        except Exception as e:
+            logger.error("RAG query failed: %s", str(e))
+            return f"Error querying RAG: {str(e)}"
+
+    yield FunctionInfo.from_fn(
+        _nvidia_rag_query,
+        description=_nvidia_rag_query.__doc__,
+    )
+
+
+class NvidiaRAGSearchConfig(FunctionBaseConfig, name="nvidia_rag_search"):
+    """
+    Tool that searches for relevant documents in the vector database using NVIDIA RAG.
+    """
+
+    config_file: str = Field(
+        default="config.yaml",
+        description="Path to the NVIDIA RAG configuration YAML file.",
+    )
+    collection_names: list[str] = Field(
+        default_factory=list,
+        description="List of collection names to search in.",
+    )
+    vdb_endpoint: str = Field(
+        default="http://localhost:19530",
+        description="Vector database endpoint URL.",
+    )
+    reranker_top_k: int = Field(
+        default=10,
+        description="Number of top results to return after reranking.",
+    )
+    vdb_top_k: int = Field(
+        default=100,
+        description="Number of top results to retrieve from vector database before reranking.",
+    )
+
+
+@register_function(config_type=NvidiaRAGSearchConfig)
+async def nvidia_rag_search(config: NvidiaRAGSearchConfig, builder: Builder):
+    """Register the NVIDIA RAG search tool."""
+
+    from nvidia_rag import NvidiaRAG
+    from nvidia_rag.utils.configuration import NvidiaRAGConfig
+
+    # Configure nvidia_rag logging to reduce verbosity
+    _configure_nvidia_rag_logging(logging.WARNING)
+
+    # Initialize RAG config - use defaults and override with NAT config values
+    rag_config = NvidiaRAGConfig()
+    rag_config.vector_store.url = os.environ.get("APP_VECTORSTORE_URL", config.vdb_endpoint)
+    logger.info(f"Vector store URL: {rag_config.vector_store.url}")
+    rag = NvidiaRAG(config=rag_config)
+
+    async def _nvidia_rag_search(query: str) -> str:
+        """Search for relevant documents in the vector database.
+
+        This tool performs a semantic search in the vector database collections
+        and returns relevant document chunks.
+
+        Args:
+            query: The search query to find relevant documents.
+
+        Returns:
+            A formatted string containing the search results with document names and content.
+        """
+        try:
+            citations = await rag.search(
+                query=query,
+                collection_names=config.collection_names,
+                reranker_top_k=config.reranker_top_k,
+                vdb_top_k=config.vdb_top_k,
+            )
+
+            if not citations or not hasattr(citations, "results") or not citations.results:
+                return "No documents found for the given query."
+
+            # Format the results
+            results = []
+            for idx, citation in enumerate(citations.results):
+                doc_name = getattr(citation, "document_name", f"Document {idx + 1}")
+                content = getattr(citation, "content", "")
+                doc_type = getattr(citation, "document_type", "text")
+                description = getattr(citation, "metadata", {}).description
+
+                results.append(f"**{doc_name}** (type: {doc_type}):\n{description}")
+
+            return "\n\n---\n\n".join(results)
+
+        except Exception as e:
+            logger.error("RAG search failed: %s", str(e))
+            return f"Error searching documents: {str(e)}"
+
+    yield FunctionInfo.from_fn(
+        _nvidia_rag_search,
+        description=_nvidia_rag_search.__doc__,
+    )
diff --git a/examples/rag_react_agent/uv.lock b/examples/rag_react_agent/uv.lock
new file mode 100644
index 00000000..1345d4db
--- /dev/null
+++ b/examples/rag_react_agent/uv.lock
@@ -0,0 +1,4713 @@
+version = 1
+revision = 3
+requires-python = ">=3.11, <3.14"
+resolution-markers = [
+    "python_full_version >= '3.13'",
+    "python_full_version == '3.12.*'",
+    "python_full_version < '3.12'",
+]
+
+[options]
+prerelease-mode = "allow"
+
+[[package]]
+name = "aioboto3"
+version = "15.5.0"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "aiobotocore", extra = ["boto3"] },
+    { name = "aiofiles" },
+]
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diff --git a/notebooks/mcp_server_usage.ipynb b/notebooks/mcp_server_usage.ipynb
index 24bb19c6..72aadcab 100644
--- a/notebooks/mcp_server_usage.ipynb
+++ b/notebooks/mcp_server_usage.ipynb
@@ -36,7 +36,7 @@
       "metadata": {},
       "outputs": [],
       "source": [
-        "# %pip install -qq -r ../nvidia_rag_mcp/requirements.txt\n"
+        "# %pip install -qq -r ../examples/nvidia_rag_mcp/requirements.txt\n"
       ]
     },
     {
@@ -94,7 +94,7 @@
         "try:\n",
         "\n",
         "    repo_root = os.path.abspath(os.path.join(os.getcwd(), \"..\"))\n",
-        "    server_path = os.path.join(repo_root, \"nvidia_rag_mcp\", \"mcp_server.py\")\n",
+        "    server_path = os.path.join(repo_root, \"examples\", \"nvidia_rag_mcp\", \"mcp_server.py\")\n",
         "    cmd = [\n",
         "        sys.executable,\n",
         "        server_path,\n",
@@ -142,7 +142,7 @@
         "\n",
         "SSE_URL = \"http://127.0.0.1:8000/sse\"\n",
         "repo_root = os.path.abspath(os.path.join(os.getcwd(), \"..\"))\n",
-        "client_path = os.path.join(repo_root, \"nvidia_rag_mcp\", \"mcp_client.py\")\n",
+        "client_path = os.path.join(repo_root, \"examples\", \"nvidia_rag_mcp\", \"mcp_client.py\")\n",
         "COLLECTION = \"my_collection\"\n",
         "pdf_path = os.path.join(repo_root, \"data\", \"multimodal\", \"woods_frost.pdf\")\n",
         "\n",
@@ -298,7 +298,7 @@
         "try:\n",
         "\n",
         "    repo_root = os.path.abspath(os.path.join(os.getcwd(), \"..\"))\n",
-        "    server_path = os.path.join(repo_root, \"nvidia_rag_mcp\", \"mcp_server.py\")\n",
+        "    server_path = os.path.join(repo_root, \"examples\", \"nvidia_rag_mcp\", \"mcp_server.py\")\n",
         "    cmd = [\n",
         "        sys.executable,\n",
         "        server_path,\n",
@@ -347,7 +347,7 @@
         "\n",
         "STREAMABLE_HTTP_URL = \"http://127.0.0.1:8000/mcp\"\n",
         "repo_root = os.path.abspath(os.path.join(os.getcwd(), \"..\"))\n",
-        "client_path = os.path.join(repo_root, \"nvidia_rag_mcp\", \"mcp_client.py\")\n",
+        "client_path = os.path.join(repo_root, \"examples\", \"nvidia_rag_mcp\", \"mcp_client.py\")\n",
         "COLLECTION = \"my_collection\"\n",
         "pdf_path = os.path.join(repo_root, \"data\", \"multimodal\", \"woods_frost.pdf\")\n",
         "\n",
@@ -483,8 +483,8 @@
         "import subprocess\n",
         "\n",
         "repo_root = os.path.abspath(os.path.join(os.getcwd(), \"..\"))\n",
-        "client_path = os.path.join(repo_root, \"nvidia_rag_mcp\", \"mcp_client.py\")\n",
-        "server_path = os.path.join(repo_root, \"nvidia_rag_mcp\", \"mcp_server.py\")\n",
+        "client_path = os.path.join(repo_root, \"examples\", \"nvidia_rag_mcp\", \"mcp_client.py\")\n",
+        "server_path = os.path.join(repo_root, \"examples\", \"nvidia_rag_mcp\", \"mcp_server.py\")\n",
         "\n",
         "STDIO_CMD = sys.executable\n",
         "STDIO_ARGS = f\"{server_path} --transport stdio\"\n",
diff --git a/notebooks/nat_mcp_integration.ipynb b/notebooks/nat_mcp_integration.ipynb
index 125876a0..a60dbeca 100644
--- a/notebooks/nat_mcp_integration.ipynb
+++ b/notebooks/nat_mcp_integration.ipynb
@@ -30,7 +30,7 @@
         "# Optional: ensure MCP dependencies are installed in this environment.\n",
         "# You can skip this cell if you've already installed them.\n",
         "# Uncomment and run the next line if needed:\n",
-        "# %pip install -r ../nvidia_rag_mcp/requirements.txt"
+        "# %pip install -r ../examples/nvidia_rag_mcp/requirements.txt"
       ]
     },
     {
@@ -55,7 +55,7 @@
         "MCP_HOST = \"127.0.0.1\"\n",
         "\n",
         "repo_root = os.path.abspath(os.path.join(os.getcwd(), \"..\"))\n",
-        "server_path = os.path.join(repo_root, \"nvidia_rag_mcp\", \"mcp_server.py\")\n",
+        "server_path = os.path.join(repo_root, \"examples\", \"nvidia_rag_mcp\", \"mcp_server.py\")\n",
         "\n",
         "cmd = [\n",
         "    sys.executable,\n",
@@ -96,7 +96,7 @@
         "\n",
         "STREAMABLE_HTTP_URL = \"http://127.0.0.1:9902/mcp\"\n",
         "repo_root = os.path.abspath(os.path.join(os.getcwd(), \"..\"))\n",
-        "client_path = os.path.join(repo_root, \"nvidia_rag_mcp\", \"mcp_client.py\")\n",
+        "client_path = os.path.join(repo_root, \"examples\", \"nvidia_rag_mcp\", \"mcp_client.py\")\n",
         "\n",
         "COLLECTION = \"my_collection\"\n",
         "pdf_path = os.path.join(repo_root, \"data\", \"multimodal\", \"product_catalog.pdf\")\n",
@@ -232,7 +232,7 @@
         "\n",
         "STREAMABLE_HTTP_URL = \"http://127.0.0.1:9902/mcp\"\n",
         "repo_root = os.path.abspath(os.path.join(os.getcwd(), \"..\"))\n",
-        "client_path = os.path.join(repo_root, \"nvidia_rag_mcp\", \"mcp_client.py\")\n",
+        "client_path = os.path.join(repo_root, \"examples\", \"nvidia_rag_mcp\", \"mcp_client.py\")\n",
         "\n",
         "COLLECTION = \"my_collection\"\n",
         "\n",
diff --git a/tests/integration/test_cases/nvidia_rag_mcp.py b/tests/integration/test_cases/nvidia_rag_mcp.py
index 74528975..385be8a1 100644
--- a/tests/integration/test_cases/nvidia_rag_mcp.py
+++ b/tests/integration/test_cases/nvidia_rag_mcp.py
@@ -110,7 +110,7 @@ def _start_sse_server(self) -> None:
         except Exception:
             pass
         repo_root = os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "..", ".."))
-        server_path = os.path.join(repo_root, "nvidia_rag_mcp", "mcp_server.py")
+        server_path = os.path.join(repo_root, "examples", "nvidia_rag_mcp", "mcp_server.py")
         cmd = [sys.executable, server_path, "--transport", "sse"]
         logger.info("Launching SSE MCP server: %s", " ".join(shlex.quote(c) for c in cmd))
         try:
@@ -126,7 +126,7 @@ def _start_streamable_http_server(self) -> None:
         except Exception:
             pass
         repo_root = os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "..", ".."))
-        server_path = os.path.join(repo_root, "nvidia_rag_mcp", "mcp_server.py")
+        server_path = os.path.join(repo_root, "examples", "nvidia_rag_mcp", "mcp_server.py")
         cmd = [sys.executable, server_path, "--transport", "streamable_http"]
         logger.info("Launching streamable_http MCP server: %s", " ".join(shlex.quote(c) for c in cmd))
         try:
@@ -192,7 +192,7 @@ def _run_mcp_client(self, args: list[str], timeout: float = 60.0) -> tuple[int,
             - `timeout` guards against hung transports or server bugs.
         """
         repo_root = os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "..", ".."))
-        client_path = os.path.join(repo_root, "nvidia_rag_mcp", "mcp_client.py")
+        client_path = os.path.join(repo_root, "examples", "nvidia_rag_mcp", "mcp_client.py")
         mcp_client_cmd = [sys.executable, client_path]
         proc = subprocess.run(mcp_client_cmd + args, capture_output=True, text=True, timeout=timeout)
         return proc.returncode, proc.stdout, proc.stderr
@@ -334,7 +334,7 @@ async def _sse_list_tools(self) -> bool:
 
         The expectation is that both Retriever tools and all Ingestor tools are
         registered with FastMCP, matching the server implementation in
-        `nvidia_rag_mcp/mcp_server.py`.
+        `examples/nvidia_rag_mcp/mcp_server.py`.
         """
         logger.info("\n=== Test 89: SSE: List Tools ===")
         start = time.time()
@@ -840,7 +840,7 @@ async def _stdio_ingestor_create_collections(self) -> bool:
         start = time.time()
         try:
             repo_root = os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "..", ".."))
-            server_path = os.path.join(repo_root, "nvidia_rag_mcp", "mcp_server.py")
+            server_path = os.path.join(repo_root, "examples", "nvidia_rag_mcp", "mcp_server.py")
             payload = {"collection_names": [self.collection]}
             args = [
                 "call",
@@ -879,7 +879,7 @@ async def _stdio_ingestor_upload_documents(self) -> bool:
         start = time.time()
         try:
             repo_root = os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "..", ".."))
-            server_path = os.path.join(repo_root, "nvidia_rag_mcp", "mcp_server.py")
+            server_path = os.path.join(repo_root, "examples", "nvidia_rag_mcp", "mcp_server.py")
             pdf_path = os.path.join(repo_root, "data", "multimodal", "woods_frost.pdf")
             payload = {
                 "collection_name": self.collection,
@@ -931,7 +931,7 @@ async def _stdio_list_tools(self) -> bool:
         missing = []
         try:
             repo_root = os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "..", ".."))
-            server_path = os.path.join(repo_root, "nvidia_rag_mcp", "mcp_server.py")
+            server_path = os.path.join(repo_root, "examples", "nvidia_rag_mcp", "mcp_server.py")
             args = [
                 "list",
                 "--transport",
@@ -971,7 +971,7 @@ async def _stdio_call_generate(self) -> bool:
                 "collection_names": [self.collection],
             }
             repo_root = os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "..", ".."))
-            server_path = os.path.join(repo_root, "nvidia_rag_mcp", "mcp_server.py")
+            server_path = os.path.join(repo_root, "examples", "nvidia_rag_mcp", "mcp_server.py")
             args = [
                 "call",
                 "--transport",
@@ -1013,7 +1013,7 @@ async def _stdio_call_search(self) -> bool:
                 "collection_names": [self.collection],
             }
             repo_root = os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "..", ".."))
-            server_path = os.path.join(repo_root, "nvidia_rag_mcp", "mcp_server.py")
+            server_path = os.path.join(repo_root, "examples", "nvidia_rag_mcp", "mcp_server.py")
             args = [
                 "call",
                 "--transport",
@@ -1058,7 +1058,7 @@ async def _stdio_call_get_summary(self) -> bool:
                 "timeout": 60,
             }
             repo_root = os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "..", ".."))
-            server_path = os.path.join(repo_root, "nvidia_rag_mcp", "mcp_server.py")
+            server_path = os.path.join(repo_root, "examples", "nvidia_rag_mcp", "mcp_server.py")
             args = [
                 "call",
                 "--transport",
@@ -1097,7 +1097,7 @@ async def _stdio_ingestor_delete_collections(self) -> bool:
         start = time.time()
         try:
             repo_root = os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "..", ".."))
-            server_path = os.path.join(repo_root, "nvidia_rag_mcp", "mcp_server.py")
+            server_path = os.path.join(repo_root, "examples", "nvidia_rag_mcp", "mcp_server.py")
             payload = {"collection_names": [self.collection]}
             args = [
                 "call",
diff --git a/tests/unit/test_mcp/test_mcp_client.py b/tests/unit/test_mcp/test_mcp_client.py
index d15602e4..17d44ec6 100644
--- a/tests/unit/test_mcp/test_mcp_client.py
+++ b/tests/unit/test_mcp/test_mcp_client.py
@@ -65,7 +65,7 @@ def __init__(
 
 
 _install_fake_mcp_session()
-mcp_client = importlib.import_module("nvidia_rag_mcp.mcp_client")
+mcp_client = importlib.import_module("examples.nvidia_rag_mcp.mcp_client")
 
 
 def test_to_jsonable_with_model_dump():
diff --git a/tests/unit/test_mcp/test_mcp_server.py b/tests/unit/test_mcp/test_mcp_server.py
index d0afd770..1ca19420 100644
--- a/tests/unit/test_mcp/test_mcp_server.py
+++ b/tests/unit/test_mcp/test_mcp_server.py
@@ -15,7 +15,7 @@
 import pytest
 
 try:
-    import nvidia_rag_mcp.mcp_server as mcp_server
+    import examples.nvidia_rag_mcp.mcp_server as mcp_server
 
     MCP_AVAILABLE = True
 except ImportError:  # pragma: no cover - optional dependency