langfuse-agent¶

Langfuse observability MCP Server + A2A Agent for the agent-utilities ecosystem — typed, deterministic access to the Langfuse tracing, evaluation, prompt, and dataset APIs.

Official documentation

This site is the canonical reference for langfuse-agent, maintained alongside every release.

Overview¶

langfuse-agent wraps the Langfuse REST surface with typed, deterministic MCP tools and a Pydantic-AI agent server. It provides:

LangfuseApi — a requests-based REST facade over the Langfuse API, organized by domain (observability, datasets, prompts/models, management, annotation queues).
87 MCP tools across 26 categories (langfuse-mcp console script): traces, observations, scores, sessions, datasets, prompts, models, projects, organizations, SCIM, and the OpenTelemetry export surface.
An A2A agent server (langfuse-agent console script) that auto-discovers the MCP tools and routes requests through the agent-utilities graph engine.

The connector remains inactive when credentials are absent; reads require only a Langfuse base URL and an API key pair.

Explore the documentation¶

Installation — pip, source, extras, and the prebuilt Docker image.
Deployment — run the MCP and agent servers, Docker Compose, Caddy + Technitium.
Usage — the MCP tools, the LangfuseApi client, and the CLI.
Backing Platform — deploy Langfuse with Docker.
Overview — the full tool surface and ecosystem role.
Concepts — the CONCEPT:LF-* registry.

Quick start¶

pip install langfuse-agent
langfuse-mcp                       # stdio MCP server (default transport)

Connect it to a Langfuse instance:

export LANGFUSE_BASE_URL=http://localhost:3000
export LANGFUSE_PUBLIC_KEY=pk-...
export LANGFUSE_SECRET_KEY=sk-...
langfuse-mcp --transport streamable-http --host 0.0.0.0 --port 8004

See Installation and Deployment for the full matrix (PyPI extras, Docker image, all transports, the agent server, reverse proxy, DNS).