Docker MCP Server

@supernova123/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 — 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	✅ No API keys, no paid plan	✅	❌ Requires Docker Hub auth
Last updated	Active	Jun 2025 (stale)	Active
Health checks	✅ HTTP/TCP/exec probes	❌	❌
Auto-restart	✅ set_restart_policy	❌	❌
Compose lifecycle	✅ up/down/ps/logs/restart	❌	❌
Log streaming	✅ tail + timestamp filter	Basic	Basic
Fleet monitoring	✅ 6 fleet tools (status, stats, events, logs, thresholds, dashboard)	❌	❌
Agent positioning	✅ 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 — 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()  → see all containers, health states, uptime
5. Watch:       watch_events(window=60)  → 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 — 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 — it keeps them running.

Blog Posts

Real data from building and running this server:

• I Cut My Docker MCP Server From 50 to 12 Tools — why fewer tools = better agent UX
• MCP Server Performance Optimization — benchmarking tool execution latency
• Building an MCP Server From Scratch — the full development process
• What 6,000 npm Downloads Taught Me — distribution and growth data
• The MCP Server Naming Playbook — how naming affects discoverability

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 — 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