@avivsinai
基本情報
A Model Context Protocol (MCP) server for Langfuse, enabling AI agents to query Langfuse trace data for enhanced debugging and observability
以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。
{
"mcpServers": {
"langfuse-mcp": {
"command": "npx",
"args": [
"skills",
"add",
"avivsinai/langfuse-mcp",
"-g",
"-y"
]
}
}
}ツール一覧はまだありません
この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。
上のボタンで一時的なサンドボックスでこのサーバーを実行し、ツール一覧を取得できます。
Langfuse MCP is an agent-facing Model Context Protocol server and skill for Langfuse observability. It lets AI agents query traces, inspect generations, debug exceptions, analyze sessions, manage prompts, browse datasets, and understand what agents did in production.
Install via uvx langfuse-mcp with Python 3.10+ and the uv runtime. Set environment variables LANGFUSE_PUBLIC_KEY, LANGFUSE_SECRET_KEY, and LANGFUSE_HOST (defaults to Langfuse Cloud). Add the server to an MCP client (Claude Code, Codex, Cursor) using the provided configuration commands or JSON files. Start the MCP client, then invoke tools directly or use the included agent skill for ready‑made debugging playbooks.
--tools flag to reduce token overhead.--read-only) disables all write operations.--default-output-mode) for compact, full JSON string, or file output.Authorization header.Langfuse MCP is a local, debugging‑first server with compact trace inspection, exception triage, session analysis, and route‑decision tools. It does not mirror every native MCP tool; the native MCP is a hosted endpoint with a broader API surface.
Python 3.10–3.14 and the `uv` package runner (for `uvx`). The server is verified on CI for those Python versions.
Yes. Use `langfuse-mcp --tools traces,prompts` to load only the tool groups you need. Available groups include traces, observations, routing, sessions, exceptions, prompts, datasets, annotation_queues, scores, metrics, and schema.
Yes. Start with `langfuse-mcp --read-only` or set `LANGFUSE_MCP_READ_ONLY=true` to disable all write operations (e.g., creating prompts, datasets, annotation queue items).
Run the server in HTTP transport mode with `--transport streamable-http`. Each MCP client passes its project credentials as a `Basic` `Authorization` header (base64(public_key:secret_key)). An absent header falls back to the server’s startup environment credentials.
B2B competitive intelligence, live sales battlecards, 5-axis ICP prospect fit scoring, and tech stack teardowns over MCP and REST with cited public-web evidence.
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🚀 The fast, Pythonic way to build MCP servers and clients.
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