Can I use FastMCP with FastAPI?

Yes, FastMCP is designed to integrate seamlessly with ASGI frameworks like FastAPI and Starlette, allowing you to share server lifespans and application logic.

How do I run a FastMCP server?

You can run it as a standard Python script, use the FastMCP CLI for development mode, or deploy it as an HTTP service via transport flags.

What is FastMCP used for?

FastMCP is a framework used to build servers that follow the Model Context Protocol, allowing LLMs like Claude to securely use your custom Python tools, data resources, and prompts.

Does FastMCP support authentication?

Yes, it provides multiple patterns including JWT verification, OAuth Proxy for providers like GitHub and Google, and a full OAuth 2.0 provider implementation.

What storage backends are available?

It supports Memory, Disk (with Fernet encryption), Redis, DynamoDB, MongoDB, and several other databases for managing persistent state and token caches.

FastMCP Python Framework

Name: FastMCP Python Framework
Author: jezweb

byjezweb

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API開発

Builds high-performance Model Context Protocol (MCP) servers in Python to expose tools, resources, and prompts to LLMs.

概要

FastMCP is a robust Python framework designed for creating Model Context Protocol (MCP) servers that bridge the gap between Large Language Models and external data or functions. It provides a production-ready ecosystem featuring flexible storage backends like Redis and Disk, a modular middleware system for logging and rate limiting, and comprehensive OAuth authentication patterns. Whether you are building custom tools for Claude or deploying complex AI integrations via FastMCP Cloud, this skill provides the patterns and best practices needed to implement secure, scalable, and type-safe MCP servers with minimal boilerplate.

主な機能

Plug-and-play middleware for logging, rate limiting, and response caching
Automated OpenAPI specification integration and FastAPI conversion
Multiple storage backends for persistent state and token management
91 GitHub stars
Advanced authentication support including OAuth Proxy and JWT validation
Seamlessly expose Python functions as tools, resources, and prompts to LLMs

ユースケース

Building custom toolsets for Claude to interact with internal databases or APIs
Creating secure, authenticated MCP servers for enterprise-grade AI integrations
Rapidly prototyping and deploying MCP services using the FastMCP CLI

概要

主な機能

Plug-and-play middleware for logging, rate limiting, and response caching
Automated OpenAPI specification integration and FastAPI conversion
Multiple storage backends for persistent state and token management
91 GitHub stars
Advanced authentication support including OAuth Proxy and JWT validation
Seamlessly expose Python functions as tools, resources, and prompts to LLMs

ユースケース

Building custom toolsets for Claude to interact with internal databases or APIs
Creating secure, authenticated MCP servers for enterprise-grade AI integrations
Rapidly prototyping and deploying MCP services using the FastMCP CLI