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FastMCP

Python framework for building MCP servers and clients, generating tool schemas and validation from function signatures

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01 / Summary

About FastMCP.

FastMCP is a Python framework for building Model Context Protocol (MCP) servers, clients, and interactive apps. You declare a tool as an ordinary Python function with a decorator, and FastMCP derives its schema, validates inputs and outputs, generates documentation, and exposes it over MCP. On the client side, you connect to a server by URL and FastMCP handles transport negotiation, authentication, and the protocol lifecycle.

The framework has three parts. Servers wrap Python functions, data, and instructions as MCP tools, resources, and prompts. Clients connect to any local or remote MCP server from Python, the command line, or another MCP application. Apps let tools return forms, tables, charts, and other interactive interfaces rendered directly in the conversation, alongside ordinary MCP results.

FastMCP 1.0 was incorporated into the official MCP Python SDK in 2024, and the standalone project continues separately, with upgrade guides for code written against the MCP SDK. FastMCP for TypeScript is a counterpart with the same concepts. Prefect Horizon, from the same team, is a separate MCP gateway for deploying, registering, securing, and governing FastMCP servers across an organization.

  • Decorator-based tools: a Python function becomes an MCP tool with generated schema, validation, and documentation
  • Servers: expose tools, resources, and prompts to LLMs
  • Clients: connect to local or remote MCP servers with full protocol support, from code or the command line
  • Apps: tools return interactive UIs such as forms, tables, and charts inside the conversation
  • Transport and auth handling: manages transport negotiation, authentication, and connection lifecycle
  • TypeScript counterpart: FastMCP for TypeScript follows the same servers, clients, and apps model
  • Upgrade guides: migration paths from earlier FastMCP versions and from the MCP SDK
  • LLM-readable docs: documentation published as llms.txt and llms-full.txt

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