Deployment

Deployment Options

plane-agent exposes its MCP server (console script plane-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": {
    "plane-mcp": {
      "command": "uvx",
      "args": ["--from", "plane-agent", "plane-mcp"],
      "env": {
        "PLANE_BASE_URL": "<your-plane_base_url>",
        "LLM_BASE_URL": "<your-llm_base_url>",
        "MCP_URL": "<your-mcp_url>"
      }
    }
  }
}

2. Streamable-HTTP (local process)

Run the server as a long-lived HTTP process:

uvx --from plane-agent plane-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": {
    "plane-mcp": {
      "command": "uvx",
      "args": ["--from", "plane-agent", "plane-mcp", "--transport", "streamable-http", "--port", "8000"],
      "env": {
        "TRANSPORT": "streamable-http",
        "HOST": "0.0.0.0",
        "PORT": "8000",
        "PLANE_BASE_URL": "<your-plane_base_url>",
        "LLM_BASE_URL": "<your-llm_base_url>",
        "MCP_URL": "<your-mcp_url>"
      }
    }
  }
}

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

{
  "mcpServers": {
    "plane-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": {
    "plane-mcp": {
      "command": "docker",
      "args": [
        "run", "-i", "--rm",
        "-e", "TRANSPORT=stdio",
        "-e", "PLANE_BASE_URL=<your-plane_base_url>",
        "-e", "LLM_BASE_URL=<your-llm_base_url>",
        "-e", "MCP_URL=<your-mcp_url>",
        "knucklessg1/plane-agent:latest"
      ]
    }
  }
}

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

docker run -d --name plane-mcp -p 8000:8000 \
  -e TRANSPORT=streamable-http \
  -e PORT=8000 \
  -e PLANE_BASE_URL="<your-plane_base_url>" \
  -e LLM_BASE_URL="<your-llm_base_url>" \
  -e MCP_URL="<your-mcp_url>" \
  knucklessg1/plane-agent:latest
# or, from a clone of this repo:
docker compose -f docker/mcp.compose.yml up -d

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

(c) From a local checkout with uv:

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

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

This page covers running plane-agent as a long-lived service: the transports, the optional A2A agent server, a Docker Compose stack, putting it behind a Caddy reverse proxy, and giving it a DNS name with Technitium. To provision the Plane platform it connects to, see Backing Platform.

plane-agent ships an MCP server (console script plane-mcp) and a separate A2A agent server (console script plane-agent). The MCP server is the typed, deterministic tool surface; the agent server is a Pydantic-AI agent that connects to the MCP server over MCP_URL and exposes the tools conversationally.

Run the MCP server

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

stdio (default)streamable-httpsse

plane-mcp

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

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

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

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

Health check (HTTP transports):

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

Configuration (environment)

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

Var	Default	Meaning
PLANE_BASE_URL	https://api.plane.so	Plane API base URL
PLANE_API_KEY	(unset)	Plane personal API key — required
PLANE_WORKSPACE_SLUG	(unset)	Target workspace slug — required
HOST	0.0.0.0	Bind address (HTTP transports)
PORT	8000	Bind port (HTTP transports)
TRANSPORT	stdio	stdio, streamable-http, or sse

Each Plane resource domain has its own tool toggle (default True) so you can register only the surface you need: PROJECTSTOOL, WORK_ITEMSTOOL, CYCLESTOOL, EPICSTOOL, MILESTONESTOOL, MODULESTOOL, STATESTOOL, USERSTOOL, WORKSPACESTOOL, INITIATIVESTOOL, INTAKETOOL, LABELSTOOL, PAGESTOOL.

The full set — including telemetry (OTEL), access governance (Eunomia), and the agent settings below — is documented in .env.example. Copy it to .env and fill in only what you use. The agent remains inactive when credentials are absent.

Backing Service

plane-agent connects to a Plane workspace. Plane is available both as a managed SaaS (Plane Cloud) and as a self-hostable platform. When using Plane Cloud only the connection configuration above is required; to deploy a local Plane instance, see Backing Platform.

Docker Compose

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

services:
  plane-agent-mcp:
    image: knucklessg1/plane-agent:latest
    container_name: plane-agent-mcp
    hostname: plane-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 PLANE_* values
docker compose -f docker/mcp.compose.yml up -d
docker compose -f docker/mcp.compose.yml logs -f

Run the agent server

When server_type is mcp+agent, the A2A agent server is exposed through the plane-agent console script and the docker/agent.compose.yml stack. The agent connects to the MCP server over MCP_URL and listens on port 9004:

# Locally — point the agent at a running MCP server
export MCP_URL=http://localhost:8000/mcp
export MODEL_ID=gpt-4o
export LLM_API_KEY=your_model_api_key
plane-agent --host 0.0.0.0 --port 9004

The agent.compose.yml stack runs both services together — the MCP server on :8000 and the agent on :9004, wired by container name:

services:
  plane-agent-mcp:
    image: knucklessg1/plane-agent:latest
    hostname: plane-agent-mcp
    env_file: [ ../.env ]
    environment:
      - TRANSPORT=streamable-http
      - HOST=0.0.0.0
      - PORT=8000
    ports: ["8000:8000"]

  plane-agent-agent:
    image: knucklessg1/plane-agent:latest
    depends_on: [ plane-agent-mcp ]
    command: [ "plane-agent" ]
    env_file: [ ../.env ]
    environment:
      - HOST=0.0.0.0
      - PORT=9004
      - MCP_URL=http://plane-agent-mcp:8000/mcp
      - MODEL_ID=${MODEL_ID:-gpt-4o}
    ports: ["9004:9004"]

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

Setting	Default	Meaning
MCP_URL	http://localhost:8000/mcp	MCP server the agent connects to
MODEL_ID	gpt-4o	Model the agent reasons with
LLM_API_KEY	(unset)	Credential for the model provider
LLM_BASE_URL	(unset)	Optional custom model endpoint
PORT	9004	Agent server port

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
plane-agent.arpa {
    tls internal
    reverse_proxy plane-agent-mcp:8000
}

# Public — automatic Let's Encrypt
plane-agent.example.com {
    reverse_proxy plane-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=plane-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 plane-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": {
    "plane-agent": {
      "command": "uv",
      "args": ["run", "plane-mcp"],
      "env": {
        "PLANE_BASE_URL": "https://api.plane.so",
        "PLANE_API_KEY": "your_plane_api_key",
        "PLANE_WORKSPACE_SLUG": "your-workspace"
      }
    }
  }
}

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