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A FastMCP-based MCP server for DevOps

Project description

DevOps MCP Server

A FastMCP-based MCP server providing DevOps tools and integrations.

This a conservative MCP server. It does not add, update or delete anything in your system, does not run any job. Basically, it is read-only. It only retrieves data for analysis, display the information.

So it is safe for DevOps.

Features

  • GitHub repository search and management
  • File content retrieval from repositories
  • Issue tracking and management
  • Code search functionality

Installation

To install the package, use the following command:

pip install devops-mcps

Usage

Run the MCP server:

devops-mcps

Configuration

Environment Variables

Set the required environment variable for GitHub API access:

export GITHUB_PERSONAL_ACCESS_TOKEN=your_token_here

UVX Configuration

Install UVX tools:

uvx install

Run with UVX:

uvx devops-mcps

Transport Configuration

The MCP server supports two transport types:

  • stdio (default): Standard input/output communication
  • sse: Server-Sent Events for HTTP-based communication

Local Usage

# Default stdio transport
devops-mcps

# SSE transport
devops-mcps --transport sse

UVX Usage

# Default stdio transport
uvx run devops-mcps

# SSE transport
uvx run devops-mcps-sse

Docker Configuration

Build the Docker image:

docker build -t devops-mcps .

Run the container:

docker run -p 8000:8000 devops-mcps

VSCode Configuration

To use this MCP server in vs code copilot, there are 2 ways to configure it in VSCode settings.json with different transport types:

UVX Configuration

stdio Transport (default)

"devops-mcps": {
  "type": "stdio",
  "command": "uvx",
  "args": ["devops-mcps"],
  "env": {
    "GITHUB_PERSONAL_ACCESS_TOKEN": "ghp_xxxxxxxxxxxxxxxxxxxxxxxxxCe"
  }
}

SSE Transport

"devops-mcps": {
  "type": "sse",
  "command": "uvx",
  "args": ["devops-mcps-sse"],
  "env": {
    "GITHUB_PERSONAL_ACCESS_TOKEN": "ghp_xxxxxxxxxxxxxxxxxxxxxxxxxCe"
  }
}

Docker Configuration

stdio Transport (default)

"devops-mcps": {
  "command": "docker",
  "args": [
    "run",
    "-i",
    "huangjien/devops-mcps:latest"
  ],
  "env": {
    "GITHUB_PERSONAL_ACCESS_TOKEN": "ghp_xxxxxxxxxxxxxxxxxxxxxxxxx2Ce"
  }
}

SSE Transport (MCP Server Deployed in Remote Docker Container)

"devops-mcps": {
  "type": "sse",
  "url": "http://[remote ip address]:8000/sse",
  "env": {
    "GITHUB_PERSONAL_ACCESS_TOKEN": "ghp_xxxxxxxxxxxxxxxxxxxxxxxxx2Ce"
  }
}

Note: The docker should start like:

docker run -p 8000:8000 -e TRANSPORT_TYPE=sse -i huangjien/devops-mcps:latest

Development

Install development dependencies:

uv pip install -e .[dev]

or

uv sync

Recommend to install vs code extension: ruff

Or do it in command line:

To lint (check):

uvx ruff check

To format:

uvx ruff format

Run mcp inspector to test or debug:

npx @modelcontextprotocol/inspector uv run devops-mcps

CI/CD Pipeline

GitHub Actions workflow will automatically:

  1. Build and publish Python package to PyPI
  2. Build and push Docker image to Docker Hub

Required Secrets

Set these secrets in your GitHub repository:

  • PYPI_API_TOKEN: Your PyPI API token
  • DOCKER_HUB_USERNAME: Your Docker Hub username
  • DOCKER_HUB_TOKEN: Your Docker Hub access token

Workflow triggers on push to main branch.

Packaging and Publishing

Install tools

pip install -U twine build  

Build the package

python -m build

Upload to PyPI

  1. Create a ~/.pypirc file with your API token:

    [pypi]
    username = __token__
    password = your_pypi_api_token_here
    
  2. Upload the package:

    twine upload dist/*
    

Important Notes

  • Ensure all classifiers in pyproject.toml are valid PyPI classifiers
  • Remove deprecated license classifiers in favor of SPDX license expressions
  • The package will be available at: https://pypi.org/project/devops-mcps/
  • Update the version everytime, or when you push, it will show an error: already exists.

License

MIT

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