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.
AI agent cost intelligence — track spend across providers, optimize model selection, manage budgets with enforcement, detect cost leaks, and prove ROI. 23 tools across 10 domains.
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
48/100 (Fair)
45/100 (Fair)
Install path
npx · high
npx · high
Engagement
2 0 0 2
0 0 0 11
Tools
Comprehensive cost dashboards per agent, model, and providerAI-powered optimization recommendations and one-click applicationBudget management with hard, soft, and monitor enforcement modesAlerts and predictive failure notifications for agent fleetsCost leak scanning with multi-check auditsAttribution tools linking tasks to revenue and ROI reports
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
