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 your Spanlens LLM observability from any MCP client. 7 read tools for request logs, agent traces, cost stats, anomalies, model-savings, and per-user analytics across OpenAI, Anthropic, and Gemini. Open source, self-hostable. npx -y @spanlens/mcp-server
Sentry.io integration for error tracking and performance monitoring
Quality signal
45/100 (Fair)
39/100 (Emerging)
Install path
npx · high
npx · high
Engagement
0 0 0 11
2 0 0 805
Tools
Request logging with full prompt, response, cost, and latency dataAgent tracing for multi-step and tool-based LLM callsCost tracking and model usage analytics across providersAnomaly detection and PII scanningPrompt versioning and A/B experiment supportSelf-hostable with a single Docker command and open source MIT license
Remote MCP server proxying Sentry API callsSupports AI-powered natural language search with LLM providersConfigurable for self-hosted or SaaS Sentry environmentsAbility to disable unsupported skills for custom deploymentsSupports OAuth and token-based authentication forwardingIncludes MCP Inspector tool for testing and debugging
