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Docker MCP Server

by ckreiling

An MCP server for managing Docker with natural language. It allows users to compose containers, introspect running containers, and manage persistent data using natural language commands.

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What is Docker MCP Server?

The Docker MCP server is a tool that enables users to manage Docker containers using natural language commands. It leverages an LLM to translate natural language instructions into Docker operations.

How to use Docker MCP Server?

The server can be installed using PyPi with uv or with Docker. After installation, configure your MCP servers file to point to the installed server. Then, use natural language prompts to compose, manage, and debug Docker containers.

Key features of Docker MCP Server

  • Compose containers with natural language

  • Introspect & debug running containers

  • Manage persistent data with Docker volumes

  • Supports a plan+apply loop for container deployment

Use cases of Docker MCP Server

  • Server administrators managing remote Docker engines

  • Tinkerers experimenting with open-source Docker apps

  • AI enthusiasts pushing the limits of LLMs

  • Deploying and managing web applications like WordPress with natural language

FAQ from Docker MCP Server

How do I install the Docker MCP server?

You can install it using PyPi with uv or by building and running it in a Docker container. Refer to the Quickstart section in the README for detailed instructions.

How do I use natural language to compose containers?

Use the docker_compose prompt, providing a project name and a description of the desired containers. The LLM will generate a plan, which you can then apply or provide feedback on.

What resources are available for each container?

The server provides access to container stats (CPU, memory, etc.) and logs.

What tools are available for managing Docker resources?

The server provides tools for managing containers, images, networks, and volumes, including listing, creating, running, stopping, and removing resources.

What are the security considerations when using this server?

Do not configure containers with sensitive data, as any data exchanged with the LLM is inherently compromised. Always review the containers created by the LLM, as Docker is not a secure sandbox.