How I Monitor MCP Servers in Production — Tools and Lessons Learned

Three months ago, one of my MCP servers crashed at 2 AM on a Friday. I didn't find out until Monday morning when a customer opened a support ticket. By then, 60+ API calls had failed silently, and I'd lost two days of data. That's when I realized: MCP servers have no built-in observability. They fail quietly. There's no error dashboard, no alerts, no uptime tracking. I spent 8 weeks building a monitoring stack for MCP servers. Here's what I learned. The Problem Unlike traditional SaaS APIs, MCP servers often: Run on VPS with minimal logging Don't have native error tracking Fail gracefully but return garbage responses Have no built-in health check endpoints Don't expose metrics in standardized format What to Monitor After my 2 AM incident, I identified five critical metrics: Uptime & Availability — Is the server actually handling requests? Error Rates — What percentage fail? I set 2% threshold. Response Times — p50, p95, p99 latency Token Usage — MCP servers burn tokens fast Resource Ut