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CbetaMCP

by tendayspace
GitHub
Python
MIT License
2
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🧠 MCP 聚合工具服务 / MCP Aggregated Tool Service

License Python FastAPI Dockerized

一个基于 FastAPI + fastapi_mcp 实现的多工具统一接入平台，支持模块化、自动注册与异步扩展。适用于将多个 AI 工具或微服务聚合为一个统一接口服务，支持标准化输入输出格式，便于前端集成或 LLM 系统调用。

A modular, extensible and FastAPI-based MCP (Multi-Component Platform) tool aggregation service. Easily connect and expose independent tools through standardized APIs. Perfect for frontend integration or large language model (LLM) orchestration.

🌟 功能特点 / Features

  • ✅ 支持多工具自动注册（基于目录扫描）

  • ✅ 所有接口统一 POST 方式 + BaseModel 校验

  • ✅ 支持异步 httpx 接口调用

  • ✅ 标准化 JSON 响应格式（success/error）

  • ✅ Docker 一键部署支持

  • ✅ 配套开发说明文档，便于扩展工具模块

📁 项目结构 / Project Structure

. ├── main.py # FastAPI 主程序，含 MCP 注册逻辑 ├── tools/ # 工具目录，每个文件一个功能 ├── Dockerfile # 构建镜像用 ├── docker-compose.yml # 一键部署支持 ├── mcp_tool_开发说明.md # 开发者使用规范文档（中文） └── README.md

🚀 快速开始 / Quick Start

🧰 依赖要求 / Requirements

  • Python 3.8+

  • pip

  • Docker / Docker Compose（可选）

📦 本地运行 / Local Dev

# 安装依赖 pip install -r requirements.txt # 启动服务 python main.py

默认服务地址：http://localhost:8000/mcp

🐳 使用 Docker 部署 / Docker Deployment

# 构建 & 运行 docker-compose up --build -d # 访问 MCP 工具服务 http://localhost:8000/mcp

🧱 工具模块开发规范 / Tool Module Guidelines

每个工具应放置于 tools/ 目录下（可多层嵌套），并包含：

  1. 使用 pydantic.BaseModel 定义参数；

  2. 使用 @__mcp_server__.tool() 注册工具函数；

  3. 返回 success_response() 或 error_response()；

  4. （可选）异步调用外部接口 + 缓存结果。

示例参考：

from pydantic import BaseModel from main import __mcp_server__, success_response class MyParams(BaseModel): name: str @__mcp_server__.tool() async def hello_tool(params: MyParams): return success_response({"message": f"Hello {params.name}!"})

🔗 接口说明 / API Usage

所有工具接口统一通过 /mcp 路径访问，自动根据模块注册。

请求方式：POST
请求格式：application/json
响应格式：

{ "status": "success", "result": { ... } }

📚 文档参考 / Docs

📄 License

MIT License © 2025 [your-name]

This server cannot be installed

-
security - not tested
A
license - permissive license
-
quality - not tested

How are these scores calculated?

remote-capable server

The server can be hosted and run remotely because it primarily relies on remote services or has no dependency on the local environment.

A modular, extensible FastAPI-based platform that aggregates multiple AI tools and microservices into a unified interface with standardized I/O formats, perfect for frontend integration or LLM system orchestration.

  1. 🌟 功能特点 / Features
    1. 📁 项目结构 / Project Structure
      1. 🚀 快速开始 / Quick Start
        1. 🧰 依赖要求 / Requirements
        2. 📦 本地运行 / Local Dev
        3. 🐳 使用 Docker 部署 / Docker Deployment
      2. 🧱 工具模块开发规范 / Tool Module Guidelines
        1. 🔗 接口说明 / API Usage
          1. 📚 文档参考 / Docs
            1. 📄 License

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