notes-mcp-server
Provides MCP tools to create and retrieve notes stored in memory.
README
FastAPI + MCP + LangGraph Demo
This is a very small learning project.
One app exposes the same note operations in two ways:
- REST API with FastAPI
- MCP tools for AI clients and agents
What is included
POST /notesto create a noteGET /notes/{note_id}to read a note- MCP tools:
create_noteget_note
mcp_client_demo.pyto call the MCP server directlylanggraph_agent_demo.pyto give a LangGraph agent access to the MCP tools
Install
.venv/bin/pip install -e .
Run the server
.venv/bin/uvicorn main:app --reload
Open:
- FastAPI docs:
http://127.0.0.1:8000/docs - MCP endpoint:
http://127.0.0.1:8000/mcp/
Try the REST API
Create:
curl -X POST http://127.0.0.1:8000/notes \
-H "content-type: application/json" \
-d '{"title":"hello","content":"from fastapi"}'
Read:
curl http://127.0.0.1:8000/notes/1
Try the MCP client
Start the server first, then run:
.venv/bin/python mcp_client_demo.py
Try the LangGraph agent
Start the server first, then set your OpenAI key:
export OPENAI_API_KEY=your_key_here
Optional model override:
export OPENAI_MODEL=gpt-4.1-mini
Run the demo:
.venv/bin/python langgraph_agent_demo.py
Without OPENAI_API_KEY, the script will still show that LangGraph can load the MCP tools, but it will skip the actual agent run.
Notes
- Data is stored only in memory.
- Restarting the server clears all notes.
- This is intentionally minimal for learning.
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