ckreiling/mcp-server-docker

What it solves

This project provides a way to manage Docker environments using natural language. It allows users to deploy, debug, and manage containers, images, networks, and volumes without needing to manually write Docker commands or Compose files.

How it works

It is implemented as a Model Context Protocol (MCP) server. By connecting an LLM to this server, the AI can interact with the Docker daemon (locally or via SSH) using a set of provided tools. The server exposes tools for listing, creating, running, and removing Docker resources, as well as resource templates for accessing container logs and stats.

Who it’s for

• Server administrators who want to manage remote Docker engines and public-facing websites.
• Tinkerers experimenting with open-source apps locally.
• AI enthusiasts looking to extend the capabilities of LLMs.

Highlights

• Natural Language Composition: Uses a plan+apply loop where the LLM proposes a deployment plan based on a project name and description, which the user then approves or refines.
• Remote Management: Supports connecting to remote Docker daemons over SSH.
• Comprehensive Toolset: Includes tools for managing containers, images, networks, and volumes.
• Introspection: Provides direct access to container logs and stats via resource templates.
• Safety Constraints: Prevents the use of sensitive Docker options like --privileged or --cap-add to protect the host machine.