What do you want to do?
3 use cases
-
Turn your Python functions into MCP tools
Wrap existing functions with FastMCP so any AI assistant that speaks MCP can call them.
View prompt
Using PrefectHQ/fastmcp, turn these Python functions into an MCP server: <list functions>. Add type hints and docstrings so the schemas are generated automatically, then connect it to my <MCP client> and test each tool.
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Call any MCP server from your own Python code
Use the FastMCP client to connect to a local or remote server by URL and call its tools programmatically.
View prompt
Using PrefectHQ/fastmcp's client, write a Python script that connects to <MCP server URL>, lists its tools, and calls <tool> with <arguments>. Use it as a smoke test I can run in CI.
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Have your coding agent build an MCP server for you
Point Claude Code or Cursor at FastMCP's llms.txt so it writes a server against current docs.
View prompt
Read https://gofastmcp.com/llms.txt and build me a FastMCP server (PrefectHQ/fastmcp) that exposes <capability> as tools. Use the current FastMCP API, add type hints and docstrings, and give me the exact steps to connect it to <MCP client>.
Quick start with Fastmcp
- Check you have what it needs: Python and uv (recommended) for installation; An MCP client to connect your server to, such as an AI assistant or coding agent; For TypeScript projects: the separate fastmcp-ts package.
- Open PrefectHQ/fastmcp on GitHub and read the README and license.
- Run
uv add fastmcpin your project - Create an instance with
mcp = FastMCP("Demo ๐")and decorate each function with @mcp.tool - Give each function type hints and a docstring; FastMCP builds the schema, validation and documentation from them
- Call mcp.run() under the main guard, as in the README example, and start the script
These steps come from our top use case, Turn your Python functions into MCP tools, which also has a copy-paste agent prompt.
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Get them freeAbout this repo
- Who it is forPython developers who want to give Claude, ChatGPT or any MCP client access to their own tools and data with minimal boilerplate.
- Why it is hot28k stars, talked about in 2 AI sources we track
- LanguagePython
- Sourcegithub.com/PrefectHQ/fastmcp ยท Back to Hot repos
Requirements
- Python and uv (recommended) for installation
- An MCP client to connect your server to, such as an AI assistant or coding agent
- For TypeScript projects: the separate fastmcp-ts package
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Questions about Fastmcp
What is Fastmcp?
FastMCP is a Python framework for building Model Context Protocol servers, clients and interactive apps. You declare a tool as an ordinary Python function and FastMCP generates the schema, validation and documentation; clients connect to any server by URL with transport, authentication and lifecycle handled. Apps give tools interactive UIs rendered inside the conversation, and there is an official TypeScript counterpart. It is an open-source project on GitHub: https://github.com/PrefectHQ/fastmcp.
How do I use Fastmcp?
Run uv add fastmcp in your project; then create an instance with mcp = FastMCP("Demo ๐") and decorate each function with @mcp.tool; give each function type hints and a docstring; FastMCP builds the schema, validation and documentation from them. The use cases on this page give the full steps and a copy-paste agent prompt for each job.
Who is Fastmcp for?
Python developers who want to give Claude, ChatGPT or any MCP client access to their own tools and data with minimal boilerplate.
What can I do with Fastmcp?
3 use cases so far, for example: Turn your Python functions into MCP tools; Call any MCP server from your own Python code; Have your coding agent build an MCP server for you. Each has steps and a copy-paste agent prompt.
What do I need to run Fastmcp?
Python and uv (recommended) for installation; An MCP client to connect your server to, such as an AI assistant or coding agent; For TypeScript projects: the separate fastmcp-ts package.
What are alternatives to Fastmcp?
Other hot AI repos in Software and DevOps: Deep Infer, Thinkrail, ECC, Instructor, Aider.
Is Fastmcp safe to run?
Deduped does not own, audit or vouch for it. Read the README and license, run it on your own systems first and review every command before you run it.