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.
Leverage AI-driven observability, security, and automation to analyze anomalies, logs, traces, events, metrics.
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
Quality signal
37/100 (Emerging)
45/100 (Fair)
Install path
npx · high
npx · high
Engagement
2 0 0 133
1 0 0 11
Tools
Natural language to DQL query translationBrowser-based OAuth authentication with token cachingAccess to Dynatrace metrics, events, logs, and tracesSupport for local development environments (VS Code, Cursor, Claude)Token storage in OS keychain or file system for headless use
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
