Installation

camunda-mcp is a standard Python package and a prebuilt container image. Pick the path that matches how you want to run it.

Requirements

• Python 3.11 – 3.14.
• A reachable Camunda 7 Engine REST endpoint and/or a Camunda 8 cluster (Zeebe / Operate / Tasklist REST) — see Backing Platform to deploy one locally.

From PyPI (recommended)

pip install camunda-mcp

Optional extras

The base install is intentionally minimal. Install the extra for what you need:

Extra	Install	Pulls in
mcp	pip install "camunda-mcp[mcp]"	FastMCP MCP-server runtime (agent-utilities[mcp])
agent	pip install "camunda-mcp[agent]"	Pydantic-AI agent + Logfire tracing (agent-utilities[agent,logfire])
all	pip install "camunda-mcp[all]"	Everything above
test	pip install "camunda-mcp[test]"	pytest, pytest-asyncio, pytest-cov, pytest-xdist

# Typical: run the MCP server and the A2A agent server
pip install "camunda-mcp[all]"

From source

git clone https://github.com/Knuckles-Team/camunda-mcp.git
cd camunda-mcp
pip install -e ".[all]"          # editable install with every extra

With uv:

uv pip install -e ".[all]"
uv run camunda-mcp

Prebuilt Docker image

A multi-stage, slim image is published on every release (entrypoint camunda-mcp):

docker pull knucklessg1/camunda-mcp:latest

docker run --rm -i \
  -e CAMUNDA_PLATFORM=7 \
  -e CAMUNDA7_URL=http://your-camunda:8080/engine-rest \
  knucklessg1/camunda-mcp:latest        # stdio transport (default)

For an HTTP server with a published port, see Deployment.

Verify the install

camunda-mcp --help
python -c "import camunda_mcp; print(camunda_mcp.__version__)"

Next steps

• Deployment — run it as a long-lived MCP server and agent behind Caddy + DNS.
• Usage — call the tools, the Api client, and the CLI.
• Configuration — every environment variable.