Daily Work MCP Server
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Daily Work MCP Serverrecord today's work: reviewed PR #123 and fixed login bug"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Daily Work MCP Server
一个用于记录、查询和总结每日工作内容的本地 MCP Server,基于 FastAPI + FastMCP + SQLite 实现。
运行前准备
安装依赖:
conda create -n daily-work-mcp python=3.11 -y conda activate daily-work-mcp pip install -r requirements.txt初始化数据库(首次运行必须执行):
python scripts/init_db.py
启动方式
启动 HTTP API(可选)
uvicorn app.main:app --reload默认监听 http://127.0.0.1:8000,包含以下 REST 接口:
POST /entries:新增工作内容GET /entries:按daily/weekly查询GET /entries/search:全文搜索GET /entries/export:导出 JSON 或 CSVGET /entries/summary:最近 N 天标签聚合GET /entries/reminder:检查今日是否已有记录GET /tags/POST /tags:标签管理
启动 MCP Server
python scripts/run_mcp_server.py默认以 STDIO transport 运行;如果需要通过 HTTP/Streamable HTTP 暴露端口,可改用:
python scripts/run_mcp_server.py --transport streamable-http --host 127.0.0.1 --port 8888脚本在 HTTP/Streamable 模式下会自动启用 stateless HTTP,即 /mcp 端点无需任何 Session/Cookie 即可访问,方便 IDE 直接连到 http://127.0.0.1:8888/mcp。
手工调试时记得同时声明 Accept: application/json, text/event-stream,例如:
curl -N \
-H "Accept: application/json, text/event-stream" \
-H "Content-Type: application/json" \
-d '{"jsonrpc":"2.0","id":"1","method":"ping","params":{}}' \
http://127.0.0.1:8888/mcp该脚本会调用 app/mcp/server.py 中的 mcp.run() 并注册全部工具:
record_work_entry:新增条目list_work_entries:按日/周查询search_work_entries:关键字检索summarize_recent_work:标签汇总check_today_recorded:今日提醒状态list_tags/create_tag:标签列表与新增
MCP 客户端连接该进程后即可直接调用上述工具。
使用示例
新增条目(REST):
curl -X POST http://127.0.0.1:8000/entries \ -H "Content-Type: application/json" \ -d '{"description":"排查登录问题","tags":["infra/login"]}'查询本周条目(REST):
curl "http://127.0.0.1:8000/entries?range=weekly"MCP 调用:在支持 MCP 的客户端中,将
scripts/run_mcp_server.py作为 Server 入口,即可在会话中调用record_work_entry、list_work_entries等工具。
更多需求说明见 requirements.md。
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