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
All-in-one homelab management MCP server. Monitor system resources, manage Docker containers, Wake-on-LAN, scan networks, check open ports, and run alerts — across multiple servers via SSH. Single 10MB binary, zero dependencies.
Quality signal
45/100 (Fair)
48/100 (Fair)
Install path
npx · high
npx · high
Engagement
0 0 0 11
1 0 0 181
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
Multi-server monitoring and management via SSHOne-command installation of popular self-hosted appsBackup verification by booting backups in isolated containersDoctor checks for resource pressure, stopped containers, and backup hygieneOutputs both human-readable summaries and machine-readable JSONNo daemon or database required; single Go binary with zero dependencies
