Installation¶

langfuse-agent 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 Langfuse instance (self-hosted or Langfuse Cloud) — see Backing Platform to deploy one locally.

From PyPI (recommended)¶

pip install langfuse-agent

Optional extras¶

The base install ships the MCP server runtime. Install the extra for what you need:

Extra	Install	Pulls in
(base)	`pip install langfuse-agent`	FastMCP MCP-server runtime (`agent-utilities[mcp]`) + `langfuse`
`agent`	`pip install "langfuse-agent[agent]"`	Pydantic-AI agent server + Logfire tracing
`all`	`pip install "langfuse-agent[all]"`	The MCP server, the agent server, and tracing
`test`	`pip install "langfuse-agent[test]"`	`pytest`, `pytest-asyncio`, `pytest-cov`, `pytest-xdist`

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

From source¶

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

With uv:

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

Prebuilt Docker image¶

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

docker pull knucklessg1/langfuse-agent:latest

docker run --rm -i \
  -e LANGFUSE_BASE_URL=http://your-langfuse:3000 \
  -e LANGFUSE_PUBLIC_KEY=pk-... \
  -e LANGFUSE_SECRET_KEY=sk-... \
  knucklessg1/langfuse-agent:latest        # stdio transport (default)

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

Verify the install¶

langfuse-mcp --help
python -c "import langfuse_agent; print(langfuse_agent.__version__)"

Next steps¶

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