Skip to content

Deployment

Deployment Options

wger-agent exposes its MCP server (console script wger-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. Replace the <your-…> placeholders with the values from the Configuration / Environment Variables 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": {
    "wger-mcp": {
      "command": "uvx",
      "args": ["--from", "wger-agent", "wger-mcp"],
      "env": {
        "WGER_URL": "<your-wger_url>",
        "WGER_API_KEY": "<your-wger_api_key>"
      }
    }
  }
}

2. Streamable-HTTP (local process)

Run the server as a long-lived HTTP process:

uvx --from wger-agent wger-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": {
    "wger-mcp": {
      "command": "uvx",
      "args": ["--from", "wger-agent", "wger-mcp", "--transport", "streamable-http", "--port", "8000"],
      "env": {
        "TRANSPORT": "streamable-http",
        "HOST": "0.0.0.0",
        "PORT": "8000",
        "WGER_URL": "<your-wger_url>",
        "WGER_API_KEY": "<your-wger_api_key>"
      }
    }
  }
}

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

{
  "mcpServers": {
    "wger-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": {
    "wger-mcp": {
      "command": "docker",
      "args": [
        "run", "-i", "--rm",
        "-e", "TRANSPORT=stdio",
        "-e", "WGER_URL=<your-wger_url>",
        "-e", "WGER_API_KEY=<your-wger_api_key>",
        "knucklessg1/wger-agent:latest"
      ]
    }
  }
}

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

docker run -d --name wger-mcp -p 8000:8000 \
  -e TRANSPORT=streamable-http \
  -e PORT=8000 \
  -e WGER_URL="<your-wger_url>" \
  -e WGER_API_KEY="<your-wger_api_key>" \
  knucklessg1/wger-agent:latest
# or, from a clone of this repo:
docker compose -f docker/mcp.compose.yml up -d
{
  "mcpServers": {
    "wger-mcp": { "url": "http://localhost:8000/mcp" }
  }
}

(c) From a local checkout with uv:

uv run wger-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": {
    "wger-mcp": { "url": "http://wger-mcp.arpa/mcp" }
  }
}

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

This page covers running wger-agent as long-lived servers: the transports, a Docker Compose stack, the optional graph agent, putting it behind a Caddy reverse proxy, and giving it a DNS name with Technitium. To provision the Wger platform it connects to, see Backing Platform.

wger-agent ships two console scripts: an MCP server (wger-mcp) and a Pydantic-AI graph agent (wger-agent). The MCP server is a typed, deterministic tool surface; the agent server orchestrates those tools behind the Agent Control Protocol and the Agent Web UI.

Run the MCP server

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

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

wger-mcp --transport streamable-http --host 0.0.0.0 --port 8000
A network server with a /health endpoint and /mcp route.

wger-mcp --transport sse --host 0.0.0.0 --port 8000

Health check (HTTP transports):

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

Configuration (environment)

wger-agent is configured entirely from the environment. The required set:

Var Default Meaning
WGER_URL https://wger.de Wger instance base URL
WGER_API_KEY (none) Wger API token
WGER_DEFAULT_EMAIL (none) Default account email
WGER_DEFAULT_PASSWORD (none) Default account password
TRANSPORT stdio stdio, streamable-http, or sse
HOST 0.0.0.0 Bind address (HTTP transports)
PORT 8000 Bind port (HTTP transports)

Each tool domain is registered through a toggle variable — ROUTINETOOL, ROUTINECONFIGTOOL, EXERCISETOOL, WORKOUTTOOL, NUTRITIONTOOL, BODYTOOL, USERTOOL (all default True). Telemetry (ENABLE_OTEL, OTLP exporter settings) and access governance (EUNOMIA_TYPE, EUNOMIA_POLICY_FILE) are configured the same way. The full set is documented in .env.example. Copy it to .env and populate only what you use; the connector remains inactive when credentials are absent.

Docker Compose

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

services:
  wger-agent-mcp:
    image: knucklessg1/wger-agent:latest
    container_name: wger-agent-mcp
    hostname: wger-agent-mcp
    restart: always
    env_file:
      - ../.env
    environment:
      - PYTHONUNBUFFERED=1
      - HOST=0.0.0.0
      - PORT=8000
      - TRANSPORT=streamable-http
    ports:
      - "8000:8000"
    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 WGER_* values
docker compose -f docker/mcp.compose.yml up -d
docker compose -f docker/mcp.compose.yml logs -f

Agent server

To run the integrated Pydantic-AI graph agent, use the wger-agent console script. It connects to the MCP server over MCP_URL, exposes the Agent Control Protocol and the Agent Web UI on its own port (9004 by convention), and routes each request to the relevant tool domain.

export WGER_URL=https://your-wger:8000
export WGER_API_KEY=your_api_key
export MCP_URL=http://wger-agent-mcp:8000/mcp

wger-agent --provider openai --model-id gpt-4o

The repo ships docker/agent.compose.yml, which deploys the MCP server and the agent together on one network so the agent reaches the MCP server by container name:

services:
  wger-agent-mcp:
    image: knucklessg1/wger-agent:latest
    container_name: wger-agent-mcp
    hostname: wger-agent-mcp
    restart: always
    env_file:
      - ../.env
    environment:
      - PYTHONUNBUFFERED=1
      - HOST=0.0.0.0
      - PORT=8000
      - TRANSPORT=streamable-http
    ports:
      - "8000:8000"

  wger-agent-agent:
    image: knucklessg1/wger-agent:latest
    container_name: wger-agent-agent
    hostname: wger-agent-agent
    restart: always
    depends_on:
      - wger-agent-mcp
    env_file:
      - ../.env
    command: ["wger-agent"]
    environment:
      - PYTHONUNBUFFERED=1
      - HOST=0.0.0.0
      - PORT=9004
      - MCP_URL=http://wger-agent-mcp:8000/mcp
      - PROVIDER=${PROVIDER:-openai}
      - MODEL_ID=${MODEL_ID:-gpt-4o}
      - ENABLE_WEB_UI=True
      - ENABLE_OTEL=True
    ports:
      - "9004:9004"
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
wger-agent.arpa {
    tls internal
    reverse_proxy wger-agent-mcp:8000
}
# Public — automatic Let's Encrypt
wger-agent.example.com {
    reverse_proxy wger-agent-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=wger-agent.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 wger-agent.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:

{
  "mcpServers": {
    "wger-agent": {
      "command": "uvx",
      "args": ["--from", "wger-agent", "wger-mcp"],
      "env": {
        "WGER_URL": "https://your-wger:8000",
        "WGER_API_KEY": "your_api_key"
      }
    }
  }
}

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