Deployment

Deployment Options

servicenow-api exposes its MCP server (console script servicenow-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": {
    "servicenow-mcp": {
      "command": "uvx",
      "args": ["--from", "servicenow-api", "servicenow-mcp"],
      "env": {
        "SERVICENOW_USERNAME": "<your-servicenow_username>"
      }
    }
  }
}

2. Streamable-HTTP (local process)

Run the server as a long-lived HTTP process:

uvx --from servicenow-api servicenow-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": {
    "servicenow-mcp": {
      "command": "uvx",
      "args": ["--from", "servicenow-api", "servicenow-mcp", "--transport", "streamable-http", "--port", "8000"],
      "env": {
        "TRANSPORT": "streamable-http",
        "HOST": "0.0.0.0",
        "PORT": "8000",
        "SERVICENOW_USERNAME": "<your-servicenow_username>"
      }
    }
  }
}

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

{
  "mcpServers": {
    "servicenow-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": {
    "servicenow-mcp": {
      "command": "docker",
      "args": [
        "run", "-i", "--rm",
        "-e", "TRANSPORT=stdio",
        "-e", "SERVICENOW_USERNAME=<your-servicenow_username>",
        "knucklessg1/servicenow-api:latest"
      ]
    }
  }
}

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

docker run -d --name servicenow-mcp -p 8000:8000 \
  -e TRANSPORT=streamable-http \
  -e PORT=8000 \
  -e SERVICENOW_USERNAME="<your-servicenow_username>" \
  knucklessg1/servicenow-api:latest
# or, from a clone of this repo:
docker compose -f docker/mcp.compose.yml up -d

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

(c) From a local checkout with uv:

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

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

This page covers running servicenow-api as a long-lived server: the transports, a Docker Compose stack, the companion A2A agent server, putting it behind a Caddy reverse proxy, and giving it a DNS name with Technitium.

servicenow-api ships an MCP server (console script servicenow-mcp) and a companion A2A agent server (console script servicenow-agent). The MCP server is a typed, deterministic tool surface a policy router / agent calls; the agent server is a Pydantic-AI graph agent that consumes those tools.

Run the MCP server

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

stdio (default)streamable-httpsse

servicenow-mcp

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

servicenow-mcp --transport streamable-http --host 0.0.0.0 --port 8000

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

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

Health check (HTTP transports):

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

Configuration (environment)

servicenow-api is configured entirely from the environment. The required set to connect to ServiceNow:

Var	Default	Meaning
SERVICENOW_INSTANCE	https://dev350360.service-now.com	ServiceNow instance URL
SERVICENOW_USERNAME	admin	User id (basic auth)
SERVICENOW_PASSWORD	(unset)	Password (basic auth)
SERVICENOW_CLIENT_ID	(unset)	OAuth client id (optional)
SERVICENOW_CLIENT_SECRET	(unset)	OAuth client secret (optional)
SERVICENOW_SSL_VERIFY	True	Verify TLS
HOST / PORT / TRANSPORT	0.0.0.0 / 8000 / stdio	HTTP transport binding

Each ServiceNow tool domain (incidents, change management, CMDB, DevOps, …) is gated by its own *TOOL toggle (for example INCIDENTSTOOL, CMDBTOOL, CHANGE_MANAGEMENTTOOL), all defaulting to True. The full set, including telemetry (ENABLE_OTEL) and access-governance (EUNOMIA_*) variables, is documented in .env.example. Copy it to .env and populate only what you use.

Backing Service (ServiceNow)

ServiceNow is a managed SaaS platform — there is no local backing system to provision. Point SERVICENOW_INSTANCE at your tenant (for example a personal developer instance from the ServiceNow Developer Program) and supply credentials via the variables above. Because the backing system is hosted, only connection configuration is required; no platform.md recipe applies.

Docker Compose

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

services:
  servicenow-api-mcp:
    image: knucklessg1/servicenow-api:latest
    container_name: servicenow-api-mcp
    hostname: servicenow-api-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 SERVICENOW_* values
docker compose -f docker/mcp.compose.yml up -d
docker compose -f docker/mcp.compose.yml logs -f

A2A agent server

servicenow-api also ships a Pydantic-AI agent server (console script servicenow-agent). It consumes the MCP tool surface over MCP_URL, exposes an A2A / web interface on port 9004, and is published in the same image. docker/agent.compose.yml runs the MCP server and the agent together:

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

  servicenow-api-agent:
    image: knucklessg1/servicenow-api:latest
    container_name: servicenow-api-agent
    hostname: servicenow-api-agent
    restart: always
    depends_on:
      - servicenow-api-mcp
    env_file:
      - ../.env
    command: [ "servicenow-agent" ]
    environment:
      - PYTHONUNBUFFERED=1
      - HOST=0.0.0.0
      - PORT=9004
      - MCP_URL=http://servicenow-api-mcp:8000/mcp
      - PROVIDER=${PROVIDER:-openai}
      - MODEL_ID=${MODEL_ID:-gpt-4o}
      - ENABLE_WEB_UI=True
    ports:
      - "9004:9004"

docker compose -f docker/agent.compose.yml up -d
curl -s http://localhost:9004/health        # {"status":"OK"}

The agent reaches the MCP server by container name through MCP_URL; set PROVIDER and MODEL_ID to select the backing LLM.

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
servicenow-api.arpa {
    tls internal
    reverse_proxy servicenow-api-mcp:8000
}

# Public — automatic Let's Encrypt
servicenow-api.example.com {
    reverse_proxy servicenow-api-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=servicenow-api.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 servicenow-api.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": {
    "servicenow-api": {
      "command": "uv",
      "args": ["run", "--with", "servicenow-api", "servicenow-mcp"],
      "env": {
        "SERVICENOW_INSTANCE": "https://your-instance.service-now.com",
        "SERVICENOW_USERNAME": "admin",
        "SERVICENOW_PASSWORD": "your_password"
      }
    }
  }
}

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