The Model Context Protocol (MCP) provides a standardized way to connect AI agents to tools and data. FastMCP makes it easy to build MCP applications with clean, Pythonic code:
from fastmcp import FastMCP
mcp = FastMCP("Demo π")
@mcp.tool
def add(a: int, b: int) -> int:
"""Add two numbers"""
return a + b
if __name__ == "__main__":
mcp.run()The Model Context Protocol (MCP) lets you give agents access to your tools and data. But building an effective MCP application is harder than it looks.
FastMCP handles all of it. Declare a tool with a Python function, and the schema, validation, and documentation are generated automatically. Connect to a server with a URL, and transport negotiation, authentication, and protocol lifecycle are managed for you. You focus on your logic, and the MCP part just works: with FastMCP, best practices are built in.
That's why FastMCP is the standard framework for working with MCP. FastMCP 1.0 was incorporated into the official MCP SDK in 2024. Today, the actively maintained standalone project is downloaded a million times a day, and some version of FastMCP powers 70% of MCP servers across all languages.
FastMCP has three pillars:
Servers Expose tools, resources, and prompts to LLMs. |
Apps Give your tools interactive UIs rendered directly in the conversation. |
Clients Connect to any MCP server β local or remote, programmatic or CLI. |
Servers wrap your Python functions into MCP-compliant tools, resources, and prompts. Clients connect to any server with full protocol support. And Apps give your tools interactive UIs rendered directly in the conversation.
Move fast and make things.
Note
FastMCP 3.0 is currently a release candidate. Install with: pip install fastmcp==3.0.0rc1
For production systems requiring stability, pin to v2: pip install 'fastmcp<3'
We recommend installing FastMCP with uv:
uv pip install fastmcpFor full installation instructions, including verification and upgrading, see the Installation Guide.
FastMCP's complete documentation is available at gofastmcp.com, including detailed guides, API references, and advanced patterns.
Documentation is also available in llms.txt format, which is a simple markdown standard that LLMs can consume easily:
llms.txtis essentially a sitemap, listing all the pages in the documentation.llms-full.txtcontains the entire documentation. Note this may exceed the context window of your LLM.
Community: Join our Discord server to connect with other FastMCP developers and share what you're building.
We welcome contributions! See the Contributing Guide for setup instructions, testing requirements, and PR guidelines.