Side-by-side comparison of two Model Context Protocol servers — install paths, tools, quality signals, and directory engagement so you can pick the right one for Claude, Cursor, and other MCP clients.
Query Langfuse traces, debug exceptions, analyze sessions, and manage prompts. Full observability toolkit for LLM applications.
MCP-native agent evaluation and observability server with trace logging, output quality evaluation, cost tracking, 12 built-in eval rules, real-time dashboard, and PII detection.
Quality signal
47/100 (Fair)
48/100 (Fair)
Install path
uvx · high
npx · high
Engagement
3 0 0 102
0 0 0 7
Tools
Query and inspect Langfuse traces and observationsFind and triage exceptions and error countsAnalyze sessions and user activity detailsManage prompts, datasets, annotation queues, and scoresIncludes an agent skill with ready-made debugging playbooksSupports local deployment with token and output control
Hierarchical span trace logging with latency, token usage, and cost13 built-in evaluation rules including PII and prompt injection detectionCost aggregation and budget threshold alertsReal-time dark-mode web dashboard for trace and evaluation visualizationSQLite storage for instant querying of trace dataCustom evaluation rules via Zod schemas