Deployment¶
Deployment Options¶
listmonk-api exposes its MCP server (console script listmonk-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": {
"listmonk-mcp": {
"command": "uvx",
"args": ["--from", "listmonk-api", "listmonk-mcp"],
"env": {
"LISTMONK_URL": "<your-listmonk_url>",
"LISTMONK_TOKEN": "<your-listmonk_token>"
}
}
}
}
2. Streamable-HTTP (local process)¶
Run the server as a long-lived HTTP process:
uvx --from listmonk-api listmonk-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": {
"listmonk-mcp": {
"command": "uvx",
"args": ["--from", "listmonk-api", "listmonk-mcp", "--transport", "streamable-http", "--port", "8000"],
"env": {
"TRANSPORT": "streamable-http",
"HOST": "0.0.0.0",
"PORT": "8000",
"LISTMONK_URL": "<your-listmonk_url>",
"LISTMONK_TOKEN": "<your-listmonk_token>"
}
}
}
}
…or connect to the already-running process by URL:
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": {
"listmonk-mcp": {
"command": "docker",
"args": [
"run", "-i", "--rm",
"-e", "TRANSPORT=stdio",
"-e", "LISTMONK_URL=<your-listmonk_url>",
"-e", "LISTMONK_TOKEN=<your-listmonk_token>",
"knucklessg1/listmonk-api:latest"
]
}
}
}
(b) Run a local streamable-http container, then connect by URL:
docker run -d --name listmonk-mcp -p 8000:8000 \
-e TRANSPORT=streamable-http \
-e PORT=8000 \
-e LISTMONK_URL="<your-listmonk_url>" \
-e LISTMONK_TOKEN="<your-listmonk_token>" \
knucklessg1/listmonk-api:latest
# or, from a clone of this repo:
docker compose -f docker/mcp.compose.yml up -d
(c) From a local checkout with uv:
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:
Caddy reverse-proxies http://listmonk-mcp.arpa to the container's :8000
streamable-http listener; http://listmonk-mcp.arpa/health returns
{"status":"OK"} when the service is live.
This page covers running listmonk-api as a long-lived service: the transports, the
companion A2A agent, a Docker Compose stack, putting it behind a Caddy reverse proxy,
and giving it a DNS name with Technitium. To provision the Listmonk instance it
connects to, see Backing Platform.
listmonk-apiships both an MCP server (console scriptlistmonk-mcp) and an A2A agent server (console scriptlistmonk-agent). The MCP server is the typed, deterministic tool surface; the agent server is a Pydantic-AI graph that calls those tools over an MCP connection.
Run the MCP server¶
The transport is selected with --transport (or the TRANSPORT env var):
Health check (HTTP transports):
Configuration (environment)¶
listmonk-api is configured entirely from the environment. The required connection
set:
| Var | Default | Meaning |
|---|---|---|
LISTMONK_URL |
http://localhost:8080 |
Base URL of the Listmonk instance |
LISTMONK_TOKEN |
"" |
Bearer / API token for authorization |
LISTMONK_USERNAME |
"" |
Username for basic auth (when token is empty) |
LISTMONK_PASSWORD |
"" |
Password for basic auth (when token is empty) |
HOST |
0.0.0.0 |
Bind address (HTTP transports) |
PORT |
8000 |
Bind port (HTTP transports) |
TRANSPORT |
stdio |
stdio, streamable-http, or sse |
Each tool module can be toggled with LISTMONK_<MODULE>TOOL (for example
LISTMONK_CAMPAIGNSTOOL, LISTMONK_SUBSCRIBERSTOOL), all enabled by default. The full
set — including telemetry (OTEL) and access-governance (Eunomia / OIDC) variables — is
documented in
.env.example.
Copy it to .env and populate only what you use.
Docker Compose¶
The repo ships docker/mcp.compose.yml.
It reads a sibling .env and publishes the HTTP server:
services:
listmonk-api-mcp:
image: knucklessg1/listmonk-api:latest
container_name: listmonk-api-mcp
hostname: listmonk-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 LISTMONK_* values
docker compose -f docker/mcp.compose.yml up -d
docker compose -f docker/mcp.compose.yml logs -f
Run the A2A agent server¶
The agent server (console script listmonk-agent) is a Pydantic-AI graph that connects
to the MCP server and exposes an optional web interface (AG-UI) and terminal interface.
It is published on port 9004 by convention and is wired to the MCP server with
MCP_URL.
export LISTMONK_URL=https://listmonk.yourdomain.com
export LISTMONK_TOKEN=your-bearer-token
# Point the agent at a running MCP server
listmonk-agent \
--provider openai --model-id gpt-4o \
--host 0.0.0.0 --port 9004 \
--mcp-url http://listmonk-api-mcp:8000/mcp
The repo ships
docker/agent.compose.yml,
which runs the MCP server and the agent together on one network so the agent reaches the
MCP server by container name:
services:
listmonk-api-mcp:
image: knucklessg1/listmonk-api:latest
container_name: listmonk-api-mcp
hostname: listmonk-api-mcp
restart: always
env_file:
- ../.env
environment:
- PYTHONUNBUFFERED=1
- HOST=0.0.0.0
- PORT=8000
- TRANSPORT=streamable-http
ports:
- "8000:8000"
listmonk-api-agent:
image: knucklessg1/listmonk-api:latest
container_name: listmonk-api-agent
hostname: listmonk-api-agent
restart: always
depends_on:
- listmonk-api-mcp
env_file:
- ../.env
command: ["listmonk-agent"]
environment:
- PYTHONUNBUFFERED=1
- HOST=0.0.0.0
- PORT=9004
- MCP_URL=http://listmonk-api-mcp:8000/mcp
- PROVIDER=${PROVIDER:-openai}
- MODEL_ID=${MODEL_ID:-gpt-4o}
- ENABLE_WEB_UI=True
- ENABLE_OTEL=True
ports:
- "9004:9004"
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
listmonk-api.arpa {
tls internal
reverse_proxy listmonk-api-mcp:8000
}
Reload Caddy:
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=listmonk-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 listmonk-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": {
"listmonk-api": {
"command": "uvx",
"args": ["--from", "listmonk-api", "listmonk-mcp"],
"env": {
"LISTMONK_URL": "https://listmonk.yourdomain.com",
"LISTMONK_TOKEN": "your-bearer-token"
}
}
}
}
For a remote HTTP server, point the client at http://listmonk-api.arpa/mcp instead.