MCP Docker Server
Enables secure Docker command execution from isolated environments like containers through MCP protocol. Provides tools for managing Docker containers, images, and Docker Compose services with security validation and async operation support.
README
MCP Docker Server
A Python-based MCP (Model Context Protocol) server that provides secure Docker command execution for language models or other clients running in isolated environments like containers.
Overview
This MCP server runs on a host system and provides access to its Docker daemon via the MCP protocol. It implements security filtering and command validation to ensure safe operation, only allowing docker and docker-compose commands to be executed.
Features
- Docker Command Execution: Executes
dockeranddocker-composecommands on the host. - Docker Compose Support: Handles both legacy
docker-composeand moderndocker composesyntax. - Security Validation: An explicit allowlist restricts executable commands to
dockeranddocker-composeonly. - Async I/O: Built with
asynciofor non-blocking command execution. - Multiple Transports: Supports
stdio,sse, andstreamable-httpMCP transports. - Rich Toolset: Provides specific tools for common operations like listing containers, images, and checking system info.
- Error Handling: Returns detailed error messages for failed commands.
Architecture
┌─────────────────┐ MCP Protocol ┌──────────────┐
│ Client │ ─────────────────► │ MCP Server │
│ (e.g. Container)│ │ (Host) │
│ │ ◄───────────────── │ │
│ - Calls Tools │ Command Results │ - Docker CLI │
└─────────────────┘ │ - Security │
└──────────────┘
│
▼
┌──────────────┐
│ Docker Daemon│
│ (Host) │
└──────────────┘
Installation
- Python: Requires Python 3.12 or newer.
- Docker: Docker must be installed and the daemon must be running on the host system.
- Dependencies: Install the required Python packages using
uvorpipfrompyproject.toml.# Using uv uv pip install -r requirements.txt # Or directly from the pyproject.toml uv pip install .
Usage
Starting the Server
The server can be started with different MCP transports.
# Start with the default stdio transport
uv run main.py
# Start with the Streamable HTTP transport
uv run main.py streamable-http
# Start with the SSE (Server-Sent Events) transport
uv run main.py sse
Environment Variables
Configure the server's network binding with these environment variables.
FASTMCP_HOST: Server bind address (default:0.0.0.0for container access).FASTMCP_PORT: Server port (default:3000).
You can create a .env file to manage these variables:
FASTMCP_HOST=0.0.0.0
FASTMCP_PORT=3000
Then run the server with:
# Example with a custom .env file
uv run --env-file=.env main.py streamable-http
MCP Protocol
The server uses the mcp library to expose tools. The available transports are stdio, sse, and streamable-http.
Available Methods (Tools)
The following tools are exposed by the server:
-
execute_docker_command(command: str, working_directory: str = None) -> str- Description: Executes a general Docker or Docker Compose command. The command is validated against an allowlist.
- Example:
session.call_tool("execute_docker_command", {"command": "docker ps -a"})
-
docker_system_info() -> str- Description: Retrieves Docker version and system disk usage information.
- Example:
session.call_tool("docker_system_info", {})
-
list_containers(all: bool = False) -> str- Description: Lists Docker containers.
- Args:
all(boolean) - If true, shows all containers (including stopped ones). Defaults toFalse. - Example:
session.call_tool("list_containers", {"all": True})
-
list_images(all: bool = False) -> str- Description: Lists Docker images.
- Args:
all(boolean) - If true, shows all images (including intermediate ones). Defaults toFalse. - Example:
session.call_tool("list_images", {})
-
docker_compose_status(working_directory: str = None) -> str- Description: Gets the status of services defined in a
docker-compose.ymlfile. - Args:
working_directory(string) - The path to the directory containing the compose file. - Example:
session.call_tool("docker_compose_status", {"working_directory": "/path/to/project"})
- Description: Gets the status of services defined in a
Security Features
Command Validation
The server uses an allowlist-based approach for security. The is_allowed_command method in main.py ensures that only commands beginning with docker or docker-compose (including docker compose) are processed. All other commands are rejected.
Error Handling
If a command fails to execute, the server captures stdout, stderr, and the exit code, returning a detailed error message to the client. The execute_command function contains a try...except block to handle exceptions during subprocess execution.
Troubleshooting
Common Issues
-
Docker Not Available:
- Ensure Docker is installed:
docker --version - Check that the Docker daemon is running:
docker info - Verify your user has permissions to access the Docker socket.
- Ensure Docker is installed:
-
Port Already in Use:
- If you see an error like
address already in use, the port (default3000) is occupied. - Change the port using the
FASTMCP_PORTenvironment variable. - Find the process using the port:
lsof -i :3000ornetstat -tulnp | grep 3000.
- If you see an error like
-
Permission Denied (Docker Socket):
- If you get a "permission denied" error when running Docker commands, add your user to the
dockergroup:sudo usermod -aG docker $USER. - You will need to start a new shell session for this change to take effect.
- If you get a "permission denied" error when running Docker commands, add your user to the
-
Connection Refused:
- Verify the MCP server is running and listening on the correct host and port.
- Check for firewall rules that might be blocking the connection.
- Ensure your client configuration matches the server's
FASTMCP_HOSTandFASTMCP_PORT.
Development
Project Structure
/workspace/mcp_docker/
├── .python-version
├── main.py # Main server implementation
├── pyproject.toml # Project metadata and dependencies
├── README.md # This documentation
└── test/
└── test_client.py # Example client for testing
Testing
Run the example test client to connect to a running server, list its tools, and execute a sample command.
# Make sure the server is running in another terminal
# Then run the client
uv run test/test_client.py
License
This project is open-source and available for modification and distribution.
Support
For issues and questions:
- Check the Troubleshooting section.
- Verify your Docker installation and permissions.
- Review the server logs for error details.
- Test connectivity with simple commands first (e.g.,
docker_system_info).
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