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, scores, datasets, schema, observations and manage prompts. Full observability toolkit for LLM applications. (https://github.com/langfuse/langfuse)
MCP server providing comprehensive Datadog observability access for AI assistants. Features grep-like log search, APM trace filtering with duration/status/error queries, smart sampling modes for token efficiency, and cross-correlation between logs, traces, and metrics.