실행과정 MCP Server

@Armdiri

代码仓库

基本信息

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其他

传输方式

stdio

作者

Armdiri

关于 실행과정 MCP Server

暂无概览

#mcp #automation #server

실행과정 MCP Server 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "mcp_autojob_server": {
      "command": "uv",
      "args": [
        "init",
        "[mcp-server-name]",
        "--python",
        "3.12",
        "#원하는",
        "버전"
      ]
    }
  }
}

실행과정 MCP Server 工具

工具列表暂未提供

当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is 실행과정?

실행과정 is an MCP server that automates a developer's daily morning routine. It checks the user's schedule, provides the day's weather, lists emails requiring a reply, and enumerates incomplete JIRA tickets assigned to the user. It is built with the MCP Python SDK and targets knowledge workers seeking office automation.

How to use 실행과정?

Install uv, create a Python 3.12 project, add the mcp[cli] package, create a server.py file, then run mcp dev server.py for local development or mcp install server.py to integrate with Cursor and Claude. A Docker Compose file is provided for deployment as a server.

Key features of 실행과정

Daily schedule check
Weather report for the day
Email reply reminders
Incomplete JIRA ticket listing
Built with MCP Python SDK
Docker Compose support for server deployment
Unit testing with pytest
Structured logging with structlog

Use cases of 실행과정

Automate the start of a workday by retrieving schedule, weather, and tasks
Get a quick summary of pending email replies
Track incomplete JIRA tickets without opening the board
Integrate with Cursor or Claude as an agent for daily planning

常见问题

What Python version is required?

Python 3.12 is used in the setup steps.

How do I run the server locally?

Use `mcp dev server.py` to start a development server, or `mcp install server.py` to make it available as an agent in Cursor and Claude.

Does it require external services?

The plan mentions checking weather and JIRA, but specific API details are not provided in the README.

How do I deploy it as a server?

Use Docker Compose: `docker compose up -d --build` to build and run in the background.

What are the main dependencies?

`uv`, `mcp[cli]`, `structlog`, `python-dotenv`, `pytest`, `requests`, and optionally Docker.

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