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langfuse

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Debug AI traces with Langfuse MCP.

Software Engineering#MCP#debug#observability#prompts#Langfuse#traces
Authoravivsinai
Version1.0.0
Installs0

System Documentation

What problem does it solve?

Langfuse MCP provides end-to-end observability to debug AI systems by centralizing traces, observations, sessions, exceptions, and prompts for rapid diagnosis and remediation.

Core Features & Use Cases

  • Centralized observability: debug traces, find exceptions, analyze sessions, and manage prompts through Langfuse MCP.
  • MCP setup and configuration: guided setup steps for Claude Code and Codex CLI workflows, including read-only mode for safe experimentation.
  • Dataset and prompt management: list, create, and upsert datasets and prompts, with versioned prompts and labels.

Quick Start

Get started with Langfuse MCP by obtaining API keys and installing MCP via uvx. Use claude mcp add or codex mcp add to configure credentials, then verify with /mcp or codex mcp list. For a safe, read-only session, enable LANGFUSE_MCP_READ_ONLY.

Dependency Matrix

Required Modules

None required

Components

references

💻 Claude Code Installation

Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.

Please help me install this Skill:
Name: langfuse
Download link: https://github.com/avivsinai/langfuse-mcp/archive/main.zip#langfuse

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
View Source Repository

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