MCP Server for langfuse

by z9905080

MCP Server for langfuse

A Model Context Protocol (MCP) server implementation for integrating AI assistants with Langfuse workspaces.

Overview

This package provides an MCP server that enables AI assistants to interact with Langfuse workspaces. It allows AI models to:

  • Query LLM Metrics by Time Range

Installation

# Install from npm npm install shouting-mcp-langfuse # Or install globally npm install -g shouting-mcp-langfuse

You can find the package on npm: shouting-mcp-langfuse

Prerequisites

Before using the server, you need to create a Langfuse project and obtain your project's public and private keys. You can find these keys in the Langfuse dashboard.

  1. set up a Langfuse project
  2. get the public and private keys
  3. set the environment variables

Configuration

The server requires the following environment variables:

  • LANGFUSE_DOMAIN: The Langfuse domain (default: https://api.langfuse.com)
  • LANGFUSE_PUBLIC_KEY: Your Langfuse Project Public Key
  • LANGFUSE_PRIVATE_KEY: Your Langfuse Project Private Key

Usage

Running as a CLI Tool

# Set environment variables export LANGFUSE_DOMAIN="https://api.langfuse.com" export LANGFUSE_PUBLIC_KEY="your-public-key" export LANGFUSE_PRIVATE_KEY="your-private # Run the server mcp-server-langfuse

Using in Your Code

import { Server } from "@modelcontextprotocol/sdk/server/index.js"; import { langfuseClient } from "shouting-mcp-langfuse"; // Initialize the server and client const server = new Server({...}); const langfuseClient = new LangfuseClient(process.env.LANGFUSE_DOMAIN, process.env.LANGFUSE_PUBLIC_KEY, process.env.LANGFUSE_PRIVATE_KEY); // Register your custom handlers // ...

Available Tools

The server provides the following langfuse integration tools:

  • getLLMMetricsByTimeRange: Get LLM Metrics by Time Range

License

ISC

Author

shouting.hsiao@gmail.com

Repository

https://github.com/z9905080/mcp-langfuse

-
security - not tested
A
license - permissive license
-
quality - not tested

remote-capable server

The server can be hosted and run remotely because it primarily relies on remote services or has no dependency on the local environment.

An MCP server implementation that integrates AI assistants with Langfuse workspaces, allowing models to query LLM metrics by time range.

  1. Overview
    1. Installation
      1. Prerequisites
        1. Configuration
          1. Usage
            1. Running as a CLI Tool
            2. Using in Your Code
          2. Available Tools
            1. License
              1. Author
                1. Repository

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