Docker MCP Server
Provides Docker management tools for Claude Code, enabling container, image, network, and volume operations.
README
Docker MCP Server
A Model Context Protocol (MCP) server providing Docker management tools for Claude Code.
Overview
This MCP server exposes Docker functionality through MCP tools, allowing Claude to interact with Docker containers, images, networks, and volumes.
Features
Tools for Docker operations including:
- Container management (list, start, stop, inspect)
- Image management (list, pull, build)
- Network operations
- Volume management
- Docker Compose integration
Installation
Prerequisites
- Python 3.11 or higher
- Docker installed and running
uvpackage manager (recommended) orpip
Setup
# Install dependencies
uv sync
# Or with pip
pip install -e .
Usage
Option 1: Run with Docker (Recommended)
Build and Run with Docker Compose
# Build and start the container
docker-compose up -d
# View logs
docker-compose logs -f
# Stop the container
docker-compose down
Build and Run with Docker CLI
# Build the image
docker build -t docker-mcp-server .
# Run the container (Linux/macOS)
docker run -it --rm \
-v /var/run/docker.sock:/var/run/docker.sock \
docker-mcp-server
# Run the container (Windows)
docker run -it --rm \
-v //var/run/docker.sock:/var/run/docker.sock \
docker-mcp-server
Important: The -v flag mounts the Docker socket, allowing the container to manage the host's Docker daemon.
Configure with Claude Code (Docker)
# Add the Docker-based server
claude mcp add --transport stdio docker -- docker run -i --rm \
-v /var/run/docker.sock:/var/run/docker.sock \
docker-mcp-server
Or configure in .mcp.json:
{
"mcpServers": {
"docker": {
"command": "docker",
"args": [
"run", "-i", "--rm",
"-v", "/var/run/docker.sock:/var/run/docker.sock",
"docker-mcp-server"
]
}
}
}
Option 2: Run with Python (Local Development)
Add the server to your Claude Code configuration:
claude mcp add --transport stdio docker -- python /path/to/custom-docker-mcp-server/server.py
Or configure in .mcp.json:
{
"mcpServers": {
"docker": {
"command": "python",
"args": ["/absolute/path/to/server.py"]
}
}
}
Standalone Testing
Test the server using MCP Inspector:
# With Docker
docker run -i --rm \
-v /var/run/docker.sock:/var/run/docker.sock \
docker-mcp-server | mcp-inspector
# With Python
mcp-inspector -- python server.py
Available Tools
list_containers
Lists all running Docker containers with detailed information.
Parameters: None
Returns:
- Container ID (short form)
- Container name
- Image name/tag
- Status
- Port mappings
Example usage:
User: "Show me all running containers"
Claude: Uses list_containers tool
Result: Displays formatted list of running containers
Development
Project Structure
custom-docker-mcp-server/
├── src/ # Business logic
│ ├── __init__.py # Package initialization
│ └── containers.py # Container operations
├── server.py # Main MCP server implementation
├── pyproject.toml # Project configuration
├── Dockerfile # Docker image definition
├── docker-compose.yml # Docker Compose configuration
├── .dockerignore # Docker build exclusions
├── README.md # This file
└── .gitignore # Git ignore rules
Adding New Tools
Tools are implemented using the FastMCP framework with business logic separated in the src/ directory:
- Add business logic in appropriate module under
src/(e.g.,src/containers.py) - Define the MCP tool in
server.pyusing@mcp.tool()decorator - Import and call the business logic from the tool
See server.py and src/containers.py for examples.
Requirements
- Docker Engine API access
- Appropriate permissions to manage Docker resources
License
MIT License
Contributing
Contributions are welcome! Please feel free to submit issues or pull requests.
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