More than just a fully featured MCP server that lets AI agents manage Docker — containers, images, networks, volumes, swarm services, secrets, configs, nodes, plugins, etc., it helps you create workflows to easily manage your Docker environments.
For simple cases, you can just install and go with no configuration required - once loaded it will discover your local Docker socket and expose the full command surface to your AI agent. For more advanced users it can manage multiple Docker daemons, e.g. both your local dev environment and also a remote production environment over TCP, TLS or SSH in a single session. It can also be configured to mark some daemons as read-only, so you can monitor them without the risk of making accidental changes.
The MCP server also exposes things like logs and stats as resources so that you can monitor and triage, enabling you to answer questions like 'why did my container crash?', 'what is the state of my swarm?', 'am I suffering memory pressure?', 'what is the disk usage of my volumes?', 'what differences are there between my test and production systems?', and more...
docker-mcp-server is optimized to work efficiently with the new generation of MCP clients that support lazy tool loading. For clients that still eagerly load all tools, the server can optionally be configured to exclude tools from a subset of domains (e.g. exclude 'swarm' and 'scout' tools) to reduce the tool list size. It's also possible to put the MCP server into 'read-only' or 'no-destructive' modes that prevent any tools with write or destructive capabilities from being registered, which again reduces the footprint.
The server runs entirely on your machine, either natively, as an mcpb bundle, or containerized, and sends no telemetry. You are entirely in control — see the Privacy Policy.
Server Config
{
"mcpServers": {
"docker-mcp-server": {
"command": "uvx",
"args": [
"docker-mcp-server"
],
"env": {}
}
}
}