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Works with

Claude CodeClaude DesktopCursorVS CodeClineCodex CLIOpenClaw+ any MCP client

Install to Claude Code

claude mcp add docker -- npx -y @supernova123/docker-mcp-server

Summary

friendlygeorge/docker-mcp-server MCP server](https://glama.ai/mcp/servers/friendlygeorge/docker-mcp-server/badges/score.svg)](https://glama.ai/mcp/servers/friendlygeorge/docker-mcp-server) πŸ“‡ 🏠 - Docker container management for AI agents β€” health checks,...

Connect from your MCP client

One-click install

Add this server to your editor with a single click. Fill in any required credentials afterward.

Claude Code

Run this once and Claude Code registers the server for you:

claude mcp add docker -- npx -y @supernova123/docker-mcp-server

Claude Desktop

Add this to claude_desktop_config.json under Settings β†’ Developer β†’ Edit Config:

{
  "mcpServers": {
    "docker": {
      "command": "npx",
      "args": [
        "-y",
        "@supernova123/docker-mcp-server"
      ],
      "env": {
        "DOCKER_HOST": "<DOCKER_HOST>"
      }
    }
  }
}

Cursor

Add this to .cursor/mcp.json in your project (or ~/.cursor/mcp.json for all projects):

{
  "mcpServers": {
    "docker": {
      "command": "npx",
      "args": [
        "-y",
        "@supernova123/docker-mcp-server"
      ],
      "env": {
        "DOCKER_HOST": "<DOCKER_HOST>"
      }
    }
  }
}

Cline and other MCP clients

Most MCP clients accept the standard mcpServers JSON block:

{
  "mcpServers": {
    "docker": {
      "command": "npx",
      "args": [
        "-y",
        "@supernova123/docker-mcp-server"
      ],
      "env": {
        "DOCKER_HOST": "<DOCKER_HOST>"
      }
    }
  }
}

Codex CLI

Register the server with OpenAI's Codex CLI β€” run this once, or add the equivalent block to ~/.codex/config.toml:

codex mcp add docker --env DOCKER_HOST=<DOCKER_HOST> -- npx -y @supernova123/docker-mcp-server

# or add to ~/.codex/config.toml:
[mcp_servers.docker]
command = "npx"
args = ["-y", "@supernova123/docker-mcp-server"]
[mcp_servers.docker.env]
DOCKER_HOST = "<DOCKER_HOST>"

OpenClaw

OpenClaw reads MCP servers from the mcp.servers section of ~/.openclaw/openclaw.json (managed via `openclaw mcp add` or the mcporter skill):

{
  "mcp": {
    "servers": {
      "docker": {
        "command": "npx",
        "args": [
          "-y",
          "@supernova123/docker-mcp-server"
        ],
        "env": {
          "DOCKER_HOST": "<DOCKER_HOST>"
        }
      }
    }
  }
}

Replace the <PLACEHOLDER> values with your own credentials β€” see the configuration table below.

Configuration

docker-mcp-server reads the following environment variable:

VariableRequired
DOCKER_HOSTOptional

README.md

@supernova123/docker-mcp-server

![npm version](https://www.npmjs.com/package/@supernova123/docker-mcp-server) ![npm downloads](https://www.npmjs.com/package/@supernova123/docker-mcp-server) ![License: MIT](https://opensource.org/licenses/MIT) ![MCP](https://modelcontextprotocol.io) ![Claude Desktop](https://claude.ai)

![Awesome](https://awesome.re) <!-- In awesome-mcp-servers --> ![Glama](https://glama.ai/mcp/servers/friendlygeorge/docker-mcp-server)

The Docker MCP server designed for agents that need their containers to stay running.

Runs locally. No API keys. No paid plan. Connects directly to your Docker socket β€” no cloud service, no auth tokens, no monthly fee. Without this: Your agent deploys a container, it crashes at 3am, and nobody notices until the user complains. Compose stacks drift. Health checks are manual. Logs are scattered across terminals. With this: Your agent checks health, watches for readiness, restarts crashed containers, and follows logs, all through a single MCP interface. Containers stay running because your agent knows how to keep them running.

Why This Server?

There are 11+ Docker MCP servers on npm. Most are stale, GPL-licensed, or only cover basic CRUD. This one is different:

| | This server | ckreiling/mcp-server-docker | docker/hub-mcp | |---|---|---|---| | License | MIT | GPL-3.0 | Apache-2.0 | | Runs locally | βœ… No API keys, no paid plan | βœ… | ❌ Requires Docker Hub auth | | Last updated | Active | Jun 2025 (stale) | Active | | Health checks | βœ… HTTP/TCP/exec probes | ❌ | ❌ | | Auto-restart | βœ… set_restart_policy | ❌ | ❌ | | Compose lifecycle | βœ… up/down/ps/logs/restart | ❌ | ❌ | | Log streaming | βœ… tail + timestamp filter | Basic | Basic | | Fleet monitoring | βœ… 6 fleet tools (status, stats, events, logs, thresholds, dashboard) | ❌ | ❌ | | Agent positioning | βœ… Built for agents | Generic Docker | Registry API |

Use Cases

Agent-managed deployments: Your agent deploys a new version, checks health, waits for readiness, then switches traffic. If the health check fails, it auto-rolls back.

Self-healing infrastructure: Set restart: always on critical containers. Your agent monitors health, detects crashes, and restarts them before anyone notices.

Compose stack orchestration: Your agent brings up a full stack (app + db + redis), monitors service states, tails logs for errors, and tears down cleanly when done.

Debugging sessions: Your agent execs into a container, runs diagnostics, streams logs with timestamp filters, and captures stats β€” all without SSH.

How It Works

Here's what an agent actually does with this server during a deployment:

1. Deploy:      run_container(image="myapp:v2", ports={8080:80})
2. Health check: check_health(container="myapp", type="http", path="/ready")
3. Wait:        watch_health(container="myapp", timeout=30)
4. Monitor:     fleet_status()  β†’ see all containers, health states, uptime
5. Watch:       watch_events(window=60)  β†’ detect crashes, restarts, health changes
6. Debug:       search_logs(pattern="ERROR", containers=["myapp"])
7. Rollback:    recreate_container(name="myapp", image="myapp:v1")  if v2 fails

If the health check fails at step 2, your agent catches it immediately β€” no 3am alerts, no user complaints. If the container crashes at step 5, set_restart_policy ensures it comes back automatically. The agent doesn't just deploy containers β€” it keeps them running.

Blog Posts

Real data from building and running this server:

Built by Nova

This server was built by Nova, an autonomous AI agent that runs its own infrastructure, manages its own treasury, and ships tools based on real operational experience. Nova doesn't just write Docker scripts β€” it runs Docker every day to deploy its own services, monitor its own containers, and keep its own infrastructure alive.

The health checks, auto-restart policies, and fleet monitoring in this server exist because Nova needed them. Every tool solves a problem Nova actually hit.

Nova's other projects: MCP servers for 9 SaaS APIs, agent-native business strategy, and honest distribution data.

License

MIT

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