Langfuse

MIT

observabilityllm-tracingprompt-managementevaluationremote-mcp

Summary

Langfuse's own MCP server for LLM observability — read traces and observations, manage prompt versions, run datasets and evaluators, and query cost and latency metrics from inside your agent.

Features

Query traces and observations with schema and filter discovery built in
Create and label prompt versions without leaving the agent
Datasets, experiments, evaluators and evaluation rules
queryMetrics for cost, latency and usage analysis
Regional cloud endpoints plus self-hosted, authenticated with project-scoped keys

Installation

Set up this MCP server in your favorite AI agent — copy a ready-made configuration below.

Any MCP-compatible agent

Most agents (Claude, Cursor, Windsurf, VS Code, and more) read a standard mcpServers configuration.

Open your agent's MCP configuration file.
Merge the snippet below into it, filling in the environment variables with your own values.
Restart the agent — the "Langfuse" tools will be available.

{
  "mcpServers": {
    "langfuse": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-remote",
        "https://cloud.langfuse.com/api/public/mcp",
        "--header",
        "Authorization: Basic ${LANGFUSE_BASIC_TOKEN}"
      ],
      "env": {
        "LANGFUSE_BASIC_TOKEN": "base64(public-key:secret-key)"
      }
    }
  }
}

Claude Code

Add the server with a single CLI command.

claude mcp add langfuse -e LANGFUSE_BASIC_TOKEN=base64(public-key:secret-key) -- npx -y mcp-remote https://cloud.langfuse.com/api/public/mcp --header Authorization: Basic ${LANGFUSE_BASIC_TOKEN}

Claude Desktop

Add the server to claude_desktop_config.json (Settings → Developer → Edit Config).

{
  "mcpServers": {
    "langfuse": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-remote",
        "https://cloud.langfuse.com/api/public/mcp",
        "--header",
        "Authorization: Basic ${LANGFUSE_BASIC_TOKEN}"
      ],
      "env": {
        "LANGFUSE_BASIC_TOKEN": "base64(public-key:secret-key)"
      }
    }
  }
}

Claude Code, native HTTP transport

{
  "command": "claude",
  "args": [
    "mcp",
    "add",
    "--transport",
    "http",
    "langfuse",
    "https://cloud.langfuse.com/api/public/mcp",
    "--header",
    "Authorization: Basic <your-base64-token>"
  ]
}

Description

Langfuse is an open-source platform for tracing, evaluating and improving LLM applications. Its MCP server puts that whole surface behind an agent, which changes the debugging loop: instead of switching to a dashboard to find out why last night's run went wrong, the agent queries the traces itself, forms a hypothesis, and can write the fix back as a new prompt version.

What it exposes

Traces and observations — listObservations, getObservation, plus schema-discovery tools (getObservationFieldSchema, getObservationFilterSchema, getObservationFilterValues) so an agent can work out what is filterable before it filters.
Prompt management — getPrompt, listPrompts, createTextPrompt, createChatPrompt, updatePromptLabels, and getPromptUnresolved for the raw content before dependency resolution.
Datasets and experiments — upsert datasets and items, create dataset run items, list and inspect runs.
Evaluation — listEvaluators, upsertEvaluator, and evaluation rules that attach an LLM judge or code evaluator to incoming observations.
Scores and score configs — record and query quality signals with typed definitions.
Metrics and models — queryMetrics for usage, cost, latency and performance; custom model definitions for cost tracking.
Annotation queues, comments, dashboards and alerts — the human-review and reporting side of the platform.

Connecting

Remote, region-scoped endpoints: https://cloud.langfuse.com/api/public/mcp (EU), https://us.cloud.langfuse.com/api/public/mcp (US), https://jp.cloud.langfuse.com/api/public/mcp (Japan), https://hipaa.cloud.langfuse.com/api/public/mcp (HIPAA US), or https://your-domain.com/api/public/mcp if you self-host. Authentication is Basic auth with a base64-encoded project-scoped public/secret key pair.

Langfuse also runs a separate documentation MCP with searchLangfuseDocs, getLangfuseDocsPage and getLangfuseOverview.

Worth knowing

Write tools are enabled by default, so an agent can create prompts, scores, evaluators and dashboards — not just read them. Scope the API key to the project you want touched, and treat prompt-version writes as production changes.

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