devops-mcps 0.3.3

A FastMCP-based MCP server for DevOps

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

JSON Configuration

Create a config.json file:

{
  "github": {
    "access_token": "your_token_here",
    "api_url": "https://api.github.com"
  },
  "server": {
    "port": 8000,
    "debug": false
  }
}

UVX Configuration

Install UVX tools:

uvx install

Run with UVX:

uvx run 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"
  }
}

Development

Install development dependencies:

pip install -e .[dev]

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