Docker MCP Server

Overview

The Docker MCP Server turns a running Docker daemon into an AI‑friendly service by exposing every Docker command as a Model Context Protocol (MCP) tool. Instead of writing custom adapters for each Docker operation, developers can simply point an MCP‑compatible assistant—such as Claude or a custom LLM client—to the server and invoke container actions with natural language. This approach solves the common pain point of integrating low‑level Docker APIs into conversational agents, eliminating boilerplate code and reducing the risk of security misconfigurations.

At its core, the server leverages the MCP Mediator framework to auto‑generate tools from a Docker client library. Each method in the underlying service can be annotated with to provide a human‑readable name and description, but the mediator also supports automatic inference for non‑annotated methods. This flexibility means that a full suite of Docker operations—such as , , , and —is available out of the box, with metadata that helps assistants discover and explain each tool to users.

Key capabilities include:

• Secure connectivity: TLS verification and certificate paths can be supplied to connect to remote Docker hosts safely.
• Scalable concurrency: The server allows configuration of maximum concurrent connections, enabling it to handle high‑volume workflows.
• Customizable metadata: By tweaking the mediator configuration, developers can tailor tool names, descriptions, and even expose only a subset of Docker commands.
• Native execution: A GraalVM native image can be built for low‑overhead, single‑file deployment on any platform that supports Docker.

Typical use cases span from continuous integration pipelines that spin up containers on demand, to chat‑based troubleshooting where an assistant can inspect logs or restart services with a single command. In data science workflows, analysts can query container statuses or retrieve environment snapshots without leaving their notebook or IDE. Because the server presents Docker commands as first‑class MCP tools, any LLM that understands the protocol can seamlessly incorporate container management into broader reasoning tasks.

By bridging Docker and MCP, this server gives developers a powerful, low‑friction path to embed container orchestration into AI assistants, unlocking new possibilities for automated deployment, monitoring, and rapid experimentation.