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실행과정

실행과정

Local
github.com/ArmdiriProductivity0Updated 79w ago
Repository

About 실행과정

실행과정 is a Korean build log for setting up a Python MCP server intended for office automation. It outlines planned daily schedule, weather, email, and Jira checks, alongside setup, Docker, logging, and test commands.

Key features

  1. 01Python MCP server setup steps
  2. 02Docker build and server operation
  3. 03structlog installation
  4. 04pytest unit test commands

Use cases

  1. 01Following a Python MCP server setup
  2. 02Running the server with Docker Compose
  3. 03Running individual or full test suites

MCP support

The README describes building an MCP server for office automation but does not specify its MCP tools or client-facing interface.

#mcp#automation#server

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

No install method listed yet

We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.

Repository

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README
MCP 서버 구축기

계획

사무자동화를 위한 방법

  • 매일 오전 출근을 하게 되면 나의 스케쥴을 체크 한다.
  • 하루의 날씨를 체크해서 알려준다.
  • 메일에서 회신을 해야 하는 메일이 필요하다면 목록을 알려준다.
  • 협업툴 지라에서 나에게 할당된 티켓중에서 아직 완료되지 않은 티켓을 나열한다.

실행과정

# uv 설치 
brew install uv

uv init [mcp-server-name] --python 3.12 #원하는 버전 
cd [mcp-server-name]
uv venv #.venv 가상환경 설치 
source .venv/bin/activate
uv add "mcp[cli]"

# toml 파일 설치 (패키지)
cat pyproject.toml

# server.py 파일 만들기 
touch server.py

# cursor open
brew install --cask cursor
cursor .

## cursor app command execure 
cursor app -> cmd + shift + p -> Shell Command : Install 'cursor' command

# cursor docs add 
Cursor Setting -> Features -> Docs > +Add new doc 클릭 -> 
MCP https://modelcontextprotocol.io/
MCP llm.txt ( https://modelcontextprotocol.io/llms-full.txt )
MCP Python SDK ( https://github.com/modelcontextprotocol/python-sdk )

#cursor Rules
https://cursor.directory/fastapi-python-microservices-serverless-cursor-rules
-> npx copied (npx cursor-directory rules add fastapi-python-microservices-serverless-cursor-rules)
-> Terminal execute

## 자체실행 
mcp dev server.py
mcp install server.py (실행이후 에이전트 cursor, claude 확인 가능 )

Docker (서버로써 구독할때 사용)

# 이미지 빌드 및 컨테이너 시작 및 백그라운드
$ docker compose up -d --build

# 로그 확인 (백그라운드 실행 시)
$ docker compose logs -f

# 서버 중지
$ docker compose down

# 동시 실행
$ docker compose down & docker compose up -d --build & docker compose logs -f

structlog

uv pip install structlog

UNIT TEST

uv pip install python-dotenv
uv pip install pytest requests

# 개별로 테스트 실행 할때 
pytest test/test_github_tool.py
# 모든 테스트 실행
pytest -v -s

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New to MCP?

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An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.