FastMCP
A fast, Pythonic framework for building MCP servers and clients.
FastMCP 🚀
Move fast and make things.
Made with 💙 by Prefect
The Model Context Protocol (MCP) connects LLMs to tools and data. FastMCP gives you everything you need to go from prototype to production:
from fastmcp import FastMCP
mcp = FastMCP("Demo 🚀")
@mcp.tool
def add(a: int, b: int) -> int:
"""Add two numbers"""
return a + b
if __name__ == "__main__":
mcp.run()
Why FastMCP
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 Python 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 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.
Ready to build? Start with the installation guide or jump straight to the quickstart. When you're ready to deploy, Prefect Horizon offers free hosting for FastMCP users.
Installation
We recommend installing FastMCP with uv:
uv pip install fastmcp
For full installation instructions, including verification and upgrading, see the Installation Guide.
Upgrading? We have guides for:
📚 Documentation
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.
Contributing
We welcome contributions! See the Contributing Guide for setup instructions, testing requirements, and PR guidelines.
Related Servers
Scout Monitoring MCP
sponsorPut performance and error data directly in the hands of your AI assistant.
Alpha Vantage MCP Server
sponsorAccess financial market data: realtime & historical stock, ETF, options, forex, crypto, commodities, fundamentals, technical indicators, & more
Deepseek Thinker
Provides Deepseek's reasoning capabilities to AI clients, supporting both the Deepseek API and local Ollama server modes.
Remote MCP Server (Authless)
An example of a remote MCP server deployable on Cloudflare Workers, without authentication.
Context7 Python
A Python server for searching libraries and retrieving documentation, with support for HTTP/HTTPS proxies.
Civil 3D MCP
An MCP server for interacting with Autodesk Civil 3D, requiring a companion plugin and Node.js 18+.
MCP Startup Framework
A framework for building MCP servers on Cloudflare Workers with OAuth, PostgreSQL, and Stripe.
Shopify Dev
A command-line tool for interacting with Shopify's Admin GraphQL API, Functions, and Polaris Web Components.
oclif MCP Server Plugin
An oclif CLI plugin that automatically discovers and serves commands via the Model Context Protocol (MCP).
MCP RAG Server
A lightweight Python server for Retrieval-Augmented Generation (RAG) using AWS Lambda. It retrieves knowledge from external data sources like arXiv and PubMed.
Docker Hub README MCP Server
Search for Docker images and retrieve their READMEs and metadata from Docker Hub.
Nereid - Mermaid charts
Create and explore Mermaid diagrams in collaboration with AI agents