🚀 FastMCP Server & Client in Python – A Tiny MCP Tutorial (Model Context Protocol)

Description

🎯 What you’ll learn What FastMCP is and why the Model Context Protocol (MCP) is a game‑changer for AI‑driven tools. How to build a minimal server in a single file using @mcp.tool to expose a Python function. How to run the server with mcp.run() and let it accept async connections. How to connect a client locally with Client("./server.py") and call the exposed tool. How to call a remote MCP service (e.g., https://gofastmcp.com/mcp) from a Python script. Key concepts – async/await, tool calling, and keeping your code clean and maintainable. 🔑 Why FastMCP? - Zero‑boilerplate – expose any Python function as an MCP tool with a single decorator. - Async‑first – built on asyncio, so you get high concurrency out‑of‑the‑box. - Remote‑friendly – connect to a server over HTTP/WS or a local file path. - Perfect for AI agents – feed the MCP tools directly into language‑model pipelines (e.g., ChatGPT, Claude, etc.). 📌 Quick steps to try it yourself - Install FastMCP: pip install fastmcp - Save the server.py snippet above. - Run the server: python server.py (it will listen on a default port). - Run the client.py (local) to see the greeting printed. - Swap in client_remote.py to query a public MCP endpoint. 📚 Resources FastMCP Docs: https://gofastmcp.com/getting-started/welcome 💡 Got ideas? Drop a comment with the MCP tool you’d love to see next – maybe a file‑fetcher, DB query, or image‑processing wrapper! 👍 Like if this helped you get started, Subscribe for more async Python tutorials, and hit the 🔔 to never miss a new video.