Langfuse MCP for AI Agents

Securely connect your AI agents and chatbots (Claude, ChatGPT, Cursor, etc) with Langfuse MCP or direct API to inspect traces, review evals, manage prompts, and analyze metrics through natural language.

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Api Key

Langfuse is an open source LLM engineering platform for traces, evals, prompt management, and metrics. It helps teams debug, monitor, and improve LLM applications with clear observability data.

10 Tools

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Type what you want done — sign in and watch it run live in the Tool Router playground.

TOOL ROUTER PLAYGROUND
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TOOLS

Supported Tools

Every Langfuse action and event your agent gets out of the box.

Create Score

Attach an evaluation score to exactly one Langfuse trace, session, or dataset run, optionally narrowing a trace score to an observation.

Get Prompt

Retrieve a Langfuse text or chat prompt by name, deployment label, or exact version, with optional dependency resolution.

List Annotation Queues

List annotation queues configured for human evaluation in the connected Langfuse project.

List Dataset Items

List dataset items, optionally scoped to a dataset, source trace or observation, or historical dataset version.

List Datasets

List datasets available to the connected Langfuse project.

List Experiments

List Langfuse experiments active in a required time range, optionally including metadata and directly attached scores.

List Models

List Langfuse-managed and project-custom model pricing definitions used for usage and cost calculation.

List Observations

Search Langfuse observations such as generations, spans, events, agents, and tool calls, selecting only the field groups needed.

List Scores

Search numeric, boolean, categorical, text, and correction scores with subject and annotation context.

Query Metrics

Run an aggregate Langfuse metrics query over observations or numeric, boolean, or categorical scores.

SETUP GUIDE

Connect Langfuse MCP Tool with your Agent

1

Install Composio

typescript
npm install @composio/core ai @ai-sdk/openai @ai-sdk/mcp
Install the Composio SDK for Python or TypeScript
2

Initialize Client and Create Tool Router Session

typescript
import { Composio } from '@composio/core';

const composio = new Composio({ apiKey: 'your-api-key' });
const session = await composio.create('your-user-id');
console.log(`Tool Router session created: ${session.mcp.url}`);
Import and initialize the Composio client, then create a Tool Router session for Langfuse
3

Connect to AI Agent

typescript
import { openai } from '@ai-sdk/openai';
import { experimental_createMCPClient as createMCPClient } from '@ai-sdk/mcp';
import { generateText } from 'ai';

const client = await createMCPClient({
  transport: {
    type: 'http',
    url: session.mcp.url,
    headers: {
      'x-api-key': 'your-composio-api-key',
    },
  },
});

const tools = await client.tools();
const { text } = await generateText({
  model: openai('gpt-4o'),
  tools,
  messages: [{
    role: 'user',
    content: 'List recent Langfuse traces with errors and summarize common failure patterns'
  }],
  maxSteps: 5,
});

console.log(`Agent: ${text}`);
Use the MCP server with your AI agent (Anthropic Claude or Mastra)
SETUP GUIDE

Connect Langfuse API Tool with your Agent

1

Install Composio

typescript
npm install @composio/openai
Install the Composio SDK
2

Initialize Composio and Create Tool Router Session

typescript
import OpenAI from 'openai';
import { Composio } from '@composio/core';
import { OpenAIResponsesProvider } from '@composio/openai';

const composio = new Composio({
  provider: new OpenAIResponsesProvider(),
});
const openai = new OpenAI({});
const session = await composio.create('your-user-id');
Import and initialize Composio client, then create a Tool Router session
3

Execute Langfuse Tools via Tool Router with Your Agent

typescript
const tools = session.tools;
const response = await openai.responses.create({
  model: 'gpt-4.1',
  tools: tools,
  input: [{
    role: 'user',
    content: 'List recent Langfuse traces with errors and summarize common failure patterns'
  }],
});
const result = await composio.provider.handleToolCalls(
  'your-user-id',
  response.output
);
console.log(result);
Get tools from Tool Router session and execute Langfuse actions with your Agent

Why Use Composio?

AI Native Langfuse Integration

  • Supports both Langfuse MCP and direct API based integrations
  • Structured, LLM-friendly schemas for reliable trace, eval, prompt, and metric workflows
  • Rich coverage for reading, writing, and querying your Langfuse observability data

Managed Auth

  • Secure API key handling so you don't have to hard-code Langfuse credentials
  • Central place to manage, scope, and revoke Langfuse access
  • Per user and per environment credentials for safer agent deployments

Agent Optimized Design

  • Tools are tuned for AI agents, so they can work with Langfuse traces and metrics more reliably
  • Clear execution logs show what your agent ran, when it ran, and on whose behalf
  • Less glue code, fewer brittle integrations, and faster debugging loops

Enterprise Grade Security

  • Fine-grained RBAC so you control which agents and users can access Langfuse
  • Scoped, least privilege access to Langfuse resources
  • Full audit trail of agent actions to support review, security checks, and compliance
FAQ

Frequently asked questions

Yes, Langfuse requires you to configure your own API key. Once set up, Composio handles secure credential storage and API request handling for you.

Yes! Composio's Tool Router enables agents to use multiple toolkits. Learn more.

Composio is SOC 2 and ISO 27001 compliant with all data encrypted in transit and at rest. Learn more.

Composio maintains and updates all toolkit integrations automatically, so your agents always work with the latest API versions.

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