Installation¶

lgtm-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 Grafana instance and/or Prometheus Alertmanager — see Backing Platform to deploy the LGTM stack locally.

From PyPI (recommended)¶

pip install lgtm-mcp

Optional extras¶

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

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

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

From source¶

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

With uv:

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

Prebuilt Docker image¶

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

docker pull knucklessg1/lgtm-mcp:latest

docker run --rm -i \
  -e GRAFANA_URL=http://your-grafana:3000 \
  -e ALERTMANAGER_URL=http://your-alertmanager:9093 \
  -e LGTM_TOKEN=your_grafana_api_token \
  knucklessg1/lgtm-mcp:latest        # stdio transport (default)

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

Verify the install¶

lgtm-mcp --help
python -c "import lgtm_mcp; print(lgtm_mcp.__version__)"

Next steps¶

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