Deployment¶

Deployment Options¶

container-manager-mcp exposes its MCP server (console script container-manager-mcp) four ways. Pick the row that matches where the server runs relative to your MCP client, then copy the matching mcp_config.json below. Add the service-connection environment variables documented in the Configuration section.

#	Option	Transport	Where it runs	`mcp_config.json` key
1	stdio	`stdio`	client launches a subprocess	`command`
2	Streamable-HTTP (local)	`streamable-http`	a local network port	`command` or `url`
3	Local container / uv	`stdio` or `streamable-http`	Docker / Podman / uv on this host	`command` or `url`
4	Remote URL	`streamable-http`	a remote host behind Caddy	`url`

1. stdio (local subprocess)¶

The client launches the server over stdio via uvx — best for local IDEs (Cursor, Claude Desktop, VS Code):

{
  "mcpServers": {
    "container-manager-mcp": {
      "command": "uvx",
      "args": ["--from", "container-manager-mcp", "container-manager-mcp"]
    }
  }
}

2. Streamable-HTTP (local process)¶

Run the server as a long-lived HTTP process:

uvx --from container-manager-mcp container-manager-mcp --transport streamable-http --host 0.0.0.0 --port 8000
curl -s http://localhost:8000/health        # {"status":"OK"}

Then either let the client launch it:

{
  "mcpServers": {
    "container-manager-mcp": {
      "command": "uvx",
      "args": ["--from", "container-manager-mcp", "container-manager-mcp", "--transport", "streamable-http", "--port", "8000"],
      "env": {
        "TRANSPORT": "streamable-http",
        "HOST": "0.0.0.0",
        "PORT": "8000"
      }
    }
  }
}

…or connect to the already-running process by URL:

{
  "mcpServers": {
    "container-manager-mcp": { "url": "http://localhost:8000/mcp" }
  }
}

3. Local container / uv¶

(a) Launch a container directly from mcp_config.json (stdio over the container — no ports to manage). Swap docker for podman for a daemonless runtime:

{
  "mcpServers": {
    "container-manager-mcp": {
      "command": "docker",
      "args": [
        "run", "-i", "--rm",
        "-e", "TRANSPORT=stdio",
        "knucklessg1/container-manager-mcp:latest"
      ]
    }
  }
}

(b) Run a local streamable-http container, then connect by URL:

docker run -d --name container-manager-mcp -p 8000:8000 \
  -e TRANSPORT=streamable-http \
  -e PORT=8000 \
  knucklessg1/container-manager-mcp:latest
# or, from a clone of this repo:
docker compose -f docker/mcp.compose.yml up -d

{
  "mcpServers": {
    "container-manager-mcp": { "url": "http://localhost:8000/mcp" }
  }
}

(c) From a local checkout with uv:

uv run container-manager-mcp --transport streamable-http --port 8000

4. Remote URL (deployed behind Caddy)¶

When the server is deployed remotely (e.g. as a Docker service) and published through Caddy on the internal *.arpa zone, connect with the "url" key — no local process or image required:

{
  "mcpServers": {
    "container-manager-mcp": { "url": "http://container-manager-mcp.arpa/mcp" }
  }
}

Caddy reverse-proxies http://container-manager-mcp.arpa to the container's :8000 streamable-http listener; http://container-manager-mcp.arpa/health returns {"status":"OK"} when the service is live.

This page covers running container-manager-mcp as a long-lived server: the transports, a Docker Compose stack, the companion agent server, putting it behind a Caddy reverse proxy, and giving it a DNS name with Technitium.

container-manager-mcp ships two console scripts: the MCP server (container-manager-mcp) and an A2A graph agent (container-manager-agent). The MCP server is a typed, deterministic tool surface; the agent server adds a conversational Pydantic-AI front end and Agent Web UI.

Run the MCP server¶

The transport is selected with --transport (or the TRANSPORT env var):

stdio (default)streamable-httpsse

container-manager-mcp

For IDE / desktop MCP clients that launch the server as a subprocess.

container-manager-mcp --transport streamable-http --host 0.0.0.0 --port 8000

A network server with a /health endpoint and /mcp route.

container-manager-mcp --transport sse --host 0.0.0.0 --port 8000

Health check (HTTP transports):

curl -s http://localhost:8000/health        # {"status":"OK"}

Configuration (environment)¶

container-manager-mcp is configured entirely from the environment. The required runtime set:

Var	Default	Meaning
`HOST`	`0.0.0.0`	Bind address for HTTP transports
`PORT`	`8000`	Listen port for HTTP transports
`TRANSPORT`	`stdio`	`stdio`, `streamable-http`, or `sse`
`ENABLE_OTEL`	`True`	Export OpenTelemetry traces / metrics
`EUNOMIA_TYPE`	`none`	Authorization mode: `none`, `embedded`, `remote`

Tool modules are individually togglable (each defaults to True): INFOTOOL, IMAGETOOL, CONTAINERTOOL, VOLUMETOOL, NETWORKTOOL, SWARMTOOL, SYSTEMTOOL, COMPOSETOOL, MISCTOOL. The complete variable set, grouped by area, is documented in .env.example. Copy it to .env and adjust only what you use.

Docker Compose¶

The repo ships docker/mcp.compose.yml. It reads a sibling .env and publishes the HTTP server on :8000:

services:
  container-manager-mcp-mcp:
    image: knucklessg1/container-manager-mcp:latest
    container_name: container-manager-mcp-mcp
    hostname: container-manager-mcp-mcp
    restart: always
    env_file:
      - ../.env
    environment:
      - PYTHONUNBUFFERED=1
      - HOST=0.0.0.0
      - PORT=8000
      - TRANSPORT=streamable-http
    ports:
      - "8000:8000"
    volumes:
      - /var/run/docker.sock:/var/run/docker.sock
    healthcheck:
      test: ["CMD", "python3", "-c", "import urllib.request; urllib.request.urlopen('http://localhost:8000/health')"]
      interval: 30s
      timeout: 10s
      retries: 3

cp .env.example .env          # then edit values
docker compose -f docker/mcp.compose.yml up -d
docker compose -f docker/mcp.compose.yml logs -f

The server needs access to a container engine. Mount the host Docker socket (/var/run/docker.sock) as shown, or point it at a remote host over SSH via the multi-host inventory.

Agent server¶

The companion agent exposes a Pydantic-AI graph agent over the Agent Control Protocol (ACP) with an optional Agent Web UI. It is launched with the container-manager-agent console script and listens on port 9019 by default, connecting to the MCP server through MCP_URL.

container-manager-agent --provider openai --model-id gpt-4o

The repo ships docker/agent.compose.yml, which runs the MCP server and the agent together and wires the agent to the MCP server by container name:

  container-manager-mcp-agent:
    image: knucklessg1/container-manager-mcp:latest
    container_name: container-manager-mcp-agent
    restart: always
    depends_on:
      - container-manager-mcp-mcp
    env_file:
      - ../.env
    command: [ "container-manager-agent" ]
    environment:
      - HOST=0.0.0.0
      - PORT=9019
      - MCP_URL=http://container-manager-mcp-mcp:8000/mcp
      - PROVIDER=${PROVIDER:-openai}
      - MODEL_ID=${MODEL_ID:-gpt-4o}
      - ENABLE_WEB_UI=True
    ports:
      - "9019:9019"

docker compose -f docker/agent.compose.yml up -d

Behind a Caddy reverse proxy¶

Expose the HTTP server on a hostname with automatic TLS. Add to your Caddyfile:

# Internal (self-signed) — homelab .arpa zone
container-manager-mcp.arpa {
    tls internal
    reverse_proxy container-manager-mcp-mcp:8000
}

# Public — automatic Let's Encrypt
container-manager-mcp.example.com {
    reverse_proxy container-manager-mcp-mcp:8000
}

Reload Caddy:

docker compose -f services/caddy/compose.yml exec caddy caddy reload --config /etc/caddy/Caddyfile

DNS with Technitium¶

Point the hostname at the host running Caddy. Via the Technitium API:

curl -s "http://technitium.arpa:5380/api/zones/records/add" \
  --data-urlencode "token=$TECHNITIUM_DNS_TOKEN" \
  --data-urlencode "domain=container-manager-mcp.arpa" \
  --data-urlencode "zone=arpa" \
  --data-urlencode "type=A" \
  --data-urlencode "ipAddress=10.0.0.10" \
  --data-urlencode "ttl=3600"

…or add an A record container-manager-mcp.arpa → <caddy-host-ip> in the Technitium web console (http://technitium.arpa:5380). The ecosystem technitium-dns-mcp automates this as a tool.

Register with an MCP client¶

Add to your client's mcp_config.json (multiplexer nickname cnt):

{
  "mcpServers": {
    "container-manager-mcp": {
      "command": "uv",
      "args": ["run", "container-manager-mcp"],
      "env": {
        "CONTAINERTOOL": "True",
        "IMAGETOOL": "True",
        "COMPOSETOOL": "True",
        "SWARMTOOL": "True"
      }
    }
  }
}

For a remote HTTP server, point the client at http://container-manager-mcp.arpa/mcp instead.