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在AI Agent和MCP（Model Context Protocol）生态快速发展的今天，越来越多优秀的MCP工具涌现出来。今天为大家推荐一个值得关注的项目——fastapi_mcp。
项目简介：Expose your FastAPI endpoints as Model Context Protocol (MCP) tools, with Auth!
技术信息：主要语言：Python | GitHub Stars：11,860 | 标签：ai, authentication, authorization, claude, cursor
📖 项目详情
Expose your FastAPI endpoints as Model Context Protocol (MCP) tools, with Auth!
该项目主要使用Python开发。
相关领域：人工智能, authentication, authorization, claude, cursor
以下是项目原始介绍（英文）：
Built by Tadata
FastAPI-MCP
Expose your FastAPI endpoints as Model Context Protocol (MCP) tools, with Auth!
Features
• Authentication built in, using your existing FastAPI dependencies!
• FastAPI-native: Not just another OpenAPI -> MCP converter
• Zero/Minimal configuration required – just point it at your FastAPI app and it works
• Preserving schemas of your request models and response models
• Preserve documentation of all your endpoints, just as it is in Swagger
• Flexible deployment – Mount your MCP server to the same app, or deploy separately
• ASGI transport – Uses FastAPI’s ASGI interface directly for efficient communication
Hosted Solution
If you prefer a managed hosted solution check out tadata.com.
Installation
We recommend using uv, a fast Python package installer:
uv add fastapi-mcpAlternatively, you can install with pip:
pip install fastapi-mcpBasic Usage
The simplest way to use FastAPI-MCP is to add an MCP server directly to your FastAPI application:
from fastapi import FastAPI
from fastapi_mcp import FastApiMCP
app = FastAPI()
mcp = FastApiMCP(app)
# Mount the MCP server directly to your FastAPI app
mcp.mount()That’s it! Your auto-generated MCP server is now available at https://app.base.url/mcp.
Documentation, Examples and Advanced Usage
FastAPI-MCP provides [comprehensive doc
…(更多内容请访问项目主页)
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