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TODO MCP CLI 和服务器

该存储库包含待办事项列表应用程序的最小模型上下文协议 (MCP) 实现,包括:

  • FastAPI 服务器server/ ):公开一个用于工具发现的/tools端点和一个用于 JSON-RPC 调用的/rpc端点来对任务执行操作。

  • CLI 客户端client/cli.py ):一个 Python 命令行界面,可与 LLM(通过 OpenAI)和 MCP 服务器交互,以使用函数调用来创建、列出和完成任务。


特征

  • 添加带有标题、内容和可选截止日期的任务

  • 列出所有任务

  • 将任务标记为已完成

  • 服务器端任务ID生成

  • 工具调用符合 JSON-RPC 2.0 标准


先决条件

  • Python 3.10+

  • 用于虚拟环境的pipenvvenv

  • OpenAI API 密钥


安装

  1. 克隆仓库:

    git clone https://github.com/oseni99/todo-mcp cd todo-mcp
  2. 创建并激活虚拟环境:

    python3 -m venv .venv source .venv/bin/activate
  3. 安装依赖项:

    pip install -r requirements.txt
  4. 在项目根目录中创建一个.env

    OPENAI_API_KEY=sk-... MCP_SERVER=http://127.0.0.1:8000

目录结构

todoMCP/ ├── client/ # CLI client code │ └── cli.py # Main entrypoint for the MCP-CLI ├── server/ # FastAPI server code │ ├── handlers.py # Business logic for add, list, complete │ ├── tools.py # JSON-Schema tool manifest │ └── main.py # FastAPI app with /tools and /rpc ├── .env # Environment variables (not committed) ├── requirements.txt # Python dependencies └── README.md # This file

运行服务器

fastapi dev server/main.py

运行 CLI

从项目根目录:

python -m client.cli

在提示符下输入自然语言命令,例如:

> Create a task titled "Write blog post" with content "Outline first draft" due 2025-05-20 > List my tasks > Mark the first task as done > Thanks! > exit

CLI 将打印工具调用和 LLM 响应。


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security - not tested
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license - not found
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