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 /notes to create a note
• GET /notes/{note_id} to read a note
• MCP tools:
  • create_note
  • get_note
• mcp_client_demo.py to call the MCP server directly
• langgraph_agent_demo.py to 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.