A step-by-step guide to instrumenting Model Context Protocol (MCP) servers using OpenLIT and visualizing telemetry in Grafana Cloud. Covers why MCP observability matters (latency, silent failures, cross-service visibility, context window usage), the architecture (agent → MCP server → external tools → OpenLIT → Grafana Cloud), and the setup process: installing the AI Observability integration, adding OpenLIT via pip, instrumenting server and client with a single openlit.init() call or zero-code CLI wrapper, configuring OTLP environment variables, and exploring pre-built dashboards for tool performance, protocol health, resource usage, and error tracking.
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