MCP ConfigsMay 12, 2026·3 min read

langfuse-mcp — Query Langfuse Traces via MCP

Connect Langfuse observability to Claude Code/Codex via MCP: fetch traces, prompts, and datasets (37 tools). Works with Langfuse Cloud or self-hosted.

Agent ready

This asset can be read and installed directly by agents

TokRepo exposes a universal CLI command, install contract, metadata JSON, adapter-aware plan, and raw content links so agents can judge fit, risk, and next actions.

Native · 94/100Policy: allow
Agent surface
Any MCP/CLI agent
Kind
Mcp
Install
Uvx
Trust
Trust: Established
Entrypoint
uvx langfuse-mcp --help
Universal CLI install command
npx tokrepo install 71f97e34-fa9c-5c0b-8c21-69d6570cb21f
Intro

langfuse-mcp turns Langfuse into agent-queryable context: your assistant can pull real traces and prompts to debug, evaluate, and iterate on agent behavior with evidence.

Best for: Agent observability, prompt debugging, evaluation workflows, and incident postmortems

Works with: Langfuse Cloud or self-hosted; MCP clients (Claude Code/Codex); API keys via env

Setup time: 10–15 minutes

Key facts (verified)

  • README lists 37 tools across traces, observations, sessions, prompts, datasets, and more.
  • Supports selective tool loading via --tools traces,prompts (README).
  • GitHub: 87 stars · 23 forks; pushed 2026-05-06 (GitHub API verified).

Main

A good “observability loop” with langfuse-mcp:

  1. Ask your agent to reproduce a bug with tracing enabled.
  2. Use MCP tools to fetch the trace and identify the failing observation span.
  3. Pull the exact prompt version used (and labels), then patch the prompt and re-run.

If you want safer access in shared environments, enable read-only mode (--read-only) first.

README excerpt (verbatim)

Langfuse MCP Server

PyPI Downloads Python 3.10–3.14 License: MIT

Model Context Protocol server for Langfuse observability. Query traces, debug errors, analyze sessions, manage prompts.

Why langfuse-mcp?

Comparison with official Langfuse MCP (as of Jan 2026):

langfuse-mcp Official
Traces & Observations Yes No
Sessions & Users Yes No
Exception Tracking Yes No
Prompt Management Yes Yes
Dataset Management Yes No
Annotation Queues Yes No
Scores (v2) Yes No
Selective Tool Loading Yes No

This project provides a full observability toolkit — traces, observations, sessions, exceptions, prompts, datasets, annotation queues, and scores — while the official MCP focuses on prompt management.

Tools (37 total)

Category Tools
Traces fetch_traces, fetch_trace
Observations fetch_observations, fetch_observation
Sessions fetch_sessions, get_session_details, get_user_sessions

FAQ

Q: How does it authenticate? A: README shows LANGFUSE_PUBLIC_KEY / LANGFUSE_SECRET_KEY and LANGFUSE_HOST via env vars.

Q: Can I restrict what loads? A: Use --tools to load only the groups you need.

Q: Is there a safe mode? A: README documents --read-only / LANGFUSE_MCP_READ_ONLY=true.

🙏

Source & Thanks

Source: https://github.com/avivsinai/langfuse-mcp > License: MIT > GitHub stars: 87 · forks: 23

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