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.
Provides access to OpenTelemetry traces and metrics through Logfire
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
36/100 (Emerging)
45/100 (Fair)
Install path
Remote · high
npx · high
Engagement
0 0 0 162
0 0 0 11
Tools
OpenTelemetry trace accessOpenTelemetry metric accessSTDIO-based MCP server implementation
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
