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Ticktick Mcp Tool

Created By
Code-MonkeyZhang16 days ago
Content

TickTick MCP Logo

滴答清单 MCP 服务器

Python 3.10+ License: MIT

一个 Model Context Protocol (MCP) 服务器,允许大语言模型管理你的滴答清单/TickTick 待办事项。

🔗 API 文档: 滴答清单官方 OpenAPI


🛠️ 准备工作

  • Python 3.10+
  • 已安装 uv (推荐)
  • 滴答清单或 TickTick 账号
  • API 凭证 (Client ID, Client Secret)

🔑 认证设置

滴答清单开发者中心(国内用户)或 TickTick Developer Center 注册一个应用。

  1. 点击 "New App"
  2. 保存你的 Client IDClient Secret
  3. 设置 Redirect URI
    • 推荐使用: http://localhost:8000/callback
    • 自定义: 如果你修改了此项,请相应地设置 TICKTICK_REDIRECT_URI 环境变量。

🚀 快速开始

1. 克隆代码库

git clone https://github.com/Code-MonkeyZhang/ticktick-mcp-enhanced
cd ticktick-mcp-enhanced

2. 配置 MCP 客户端

Claude Desktop (claude_desktop_config.json) 为例:

{
  "mcpServers": {
    "ticktick": {
      "command": "/path/to/uv",
      "args": [
        "run",
        "--directory",
        "/项目/的/绝对路径/ticktick-mcp-enhanced",
        "ticktick-mcp",
        "run"
      ],
      "env": {
        "TICKTICK_ACCOUNT_TYPE": "china", // "china" 或 "global" 选择你滴答清单账户的区域
        "TICKTICK_CLIENT_ID": "你的_client_id",
        "TICKTICK_CLIENT_SECRET": "你的_client_secret",
        "TICKTICK_REDIRECT_URI": "http://localhost:8000/callback", // 这里填写上一步中你在开发者平台注册的URL
        "MCP_LOG_ENABLE": "false" // 可选:开启MCP日志记录功能
      }
    }
  }
}

3. 授权并使用

  1. 重启你的 MCP 客户端。
  2. 问 AI:“查看我今天的任务”。
  3. 首次授权:AI 将提供一个授权链接。点击链接 -> 登录 -> 将弹出一个授权页面,显示授权已完成。
  4. 你可以返回 LLM 客户端并使用此 MCP 访问滴答清单。

你的授权 Token 将存储在项目文件夹下的 .ticktick_token.json 中。

🧰 可用工具

此 MCP 向你的 LLM 客户端公开以下工具。

类别工具名称功能描述
认证ticktick_status检查当前的连接和授权状态。
start_authentication生成登录链接并启动本地回调监听。
清单get_all_projects获取所有清单列表。
get_project_info查看特定清单及其中的任务。
create_project创建一个新的项目。
delete_projects删除项目。
任务create_tasks创建任务(支持智能时间识别)。
update_tasks修改任务标题、内容、日期或优先级。
complete_tasks将任务标记为完成。
delete_tasks批量删除任务。
create_subtasks为任务添加子任务。
查询query_tasks高级清单查询(支持日期范围、优先级、搜索词)。

📂 项目结构

ticktick-mcp-enhanced/
├── ticktick_mcp/
│   ├── src/
│   │   ├── server.py          # MCP 服务入口
│   │   ├── auth.py            # OAuth 逻辑与回调服务器
│   │   ├── tools/             # 各类工具实现
│   │   └── utils/             # 格式化与校验工具
│   └── __main__.py            # CLI 启动项
├── pyproject.toml             # 项目配置与依赖
└── README_en.md               # 英文文档

Server Config

{
  "mcpServers": {
    "ticktick": {
      "command": "/path/to/uv",
      "args": [
        "run",
        "--directory",
        "/absolute/path/to/ticktick-mcp-enhanced",
        "ticktick-mcp",
        "run"
      ]
    }
  }
}
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