Langfuse MCP

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The Langfuse MCP is a server that facilitates integration with Langfuse, providing tools for AI agents to access trace, observation, session, and exception data for enhanced debugging and observability.
Added on:
Created by:
Apr 01 2025
Langfuse MCP

Langfuse MCP

0 Reviews
2
0
Langfuse MCP
The Langfuse MCP is a server that facilitates integration with Langfuse, providing tools for AI agents to access trace, observation, session, and exception data for enhanced debugging and observability.
Added on:
Created by:
Apr 01 2025
avivsinai
Featured

What is Langfuse MCP?

This MCP server for Langfuse allows AI agents and developers to query detailed trace data, observations, session information, and errors. It supports functionalities such as fetching traces by criteria, retrieving specific trace details, finding exceptions, and monitoring interactions within the system. This enhances debugging, error tracking, and understanding of user activities, thereby improving system reliability and analysis capabilities. Easy setup with environment configuration and support for output customization makes it suitable for integration into various development and monitoring workflows.

Who will use Langfuse MCP?

  • AI developers
  • System administrators
  • QA engineers
  • Developers integrating Langfuse
  • Monitoring teams

How to use the Langfuse MCP?

  • Step1: Install the uv package and the langfuse-mcp library
  • Step2: Obtain your Langfuse credentials (public key, secret key, host URL)
  • Step3: Run the server using uvx with your credentials
  • Step4: Configure your clients or tools to connect to the MCP server using the provided setup instructions
  • Step5: Use the available tools to query traces, sessions, observations, and exceptions

Langfuse MCP's Core Features & Benefits

The Core Features
  • fetch_traces
  • fetch_trace
  • fetch_observations
  • fetch_observation
  • fetch_sessions
  • get_session_details
  • get_user_sessions
  • find_exceptions
  • find_exceptions_in_file
  • get_exception_details
  • get_error_count
  • get_data_schema
The Benefits
  • Enhances debugging with detailed trace and error data
  • Provides comprehensive monitoring and observation capabilities
  • Supports integration with AI agents for automated analysis
  • Simplifies access to session and user activity data
  • Facilitates error tracking and system reliability improvements

Langfuse MCP's Main Use Cases & Applications

  • AI debugging and troubleshooting
  • Application performance monitoring
  • Error and exception analysis
  • User session tracking
  • System activity audits

FAQs of Langfuse MCP

Developer

  • avivsinai

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