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Langfuse MCP Server

Langfuse includes a native Model Context Protocol (MCP) server that enables AI assistants and agents to interact with your Langfuse data programmatically.

Currently, the MCP server is available for Prompt Management and will be extended to the rest of the Langfuse data platform in the future. If you have feedback or ideas for new tools, please share them on GitHub.

This is the authenticated MCP server for the Langfuse data platform. There is also a public MCP server for the Langfuse documentation (docs).

Configuration

The Langfuse MCP server uses a stateless architecture where each API key is scoped to a specific project. Use the following configuration to connect to the MCP server:

  • Endpoint: https://cloud.langfuse.com/api/public/mcp
  • Transport: streamableHttp
  • Authentication: Basic Auth via authorization header

Available Tools

The MCP server provides five tools for comprehensive prompt management.

⚠️

Both read and write tools are available by default. If you only want to use read-only tools, configure your MCP client with an allowlist to restrict access to write operations (createTextPrompt, createChatPrompt, updatePromptLabels).

Read Operations

  • getPrompt - Fetch a specific prompt by name with optional label or version

    • Supports filtering by production/staging labels
    • Returns compiled prompt with metadata
    • Read-only operation (auto-approved by clients)

  • listPrompts - List all prompts in the project

    • Optional filtering by name, tag, or label
    • Cursor-based pagination support
    • Returns prompt metadata and available versions

Write Operations

  • createTextPrompt - Create a new text prompt version

    • Supports template variables with {{variable}} syntax
    • Optional labels, config, tags, and commit message
    • Automatic version incrementing

  • createChatPrompt - Create a new chat prompt version

    • OpenAI-style message format (role + content)
    • Supports system, user, and assistant roles
    • Template variables in message content

  • updatePromptLabels - Manage labels across prompt versions

    • Add or move labels between versions
    • Labels are unique (auto-removed from other versions)
    • Cannot modify the auto-managed latest label

Set up

Get Authentication Header

  1. Navigate to your project settings and create or copy a project-scoped API key:
    • Public Key: pk-lf-...
    • Secret Key: sk-lf-...
  2. Encode the credentials to base64 format:
    your-base64-token
    echo -n "pk-lf-your-public-key:sk-lf-your-secret-key" | base64

Client Setup

  1. Register the Langfuse MCP server with a single command, replace {your-base64-token} with your encoded credentials:

    terminal
    # Langfuse Cloud (EU)
claude mcp add --transport http langfuse https://cloud.langfuse.com/api/public/mcp \
    --header "Authorization: Basic {your-base64-token}"
 
# Langfuse Cloud (US)
claude mcp add --transport http langfuse https://us.langfuse.com/api/public/mcp \
    --header "Authorization: Basic {your-base64-token}"
 
# Self-Hosted (HTTPS required)
claude mcp add --transport http langfuse https://your-domain.com/api/public/mcp \
    --header "Authorization: Basic {your-base64-token}"
 
# Local Development
claude mcp add --transport http langfuse http://localhost:3000/api/public/mcp \
    --header "Authorization: Basic {your-base64-token}"

  2. Verify the connection by asking Claude Code to list all prompts in the project. Claude Code should use the listPrompts tool to return the list of prompts.

Use Cases

The MCP server enables powerful workflows for AI-assisted prompt management:

  • Prompt Creation: “Create a new chat prompt for customer support with system instructions and example messages”
  • Version Management: “Update the staging label to point to version 3 of the email-generation prompt”
  • Prompt Discovery: “List all prompts tagged with ‘production’ and show their latest versions”
  • Iterative Development: “Create a new version of the code-review prompt with improved instructions”

Feedback

We’d love to hear about your experience with the Langfuse MCP server. Share your feedback, ideas, and use cases in our GitHub Discussion.

Related Documentation

Export for Fine-TuningPublic API
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