Use this guide to learn how to instrument MCP servers using OpenLIT and how to analyze those servers in Grafana Cloud.

Grafana is an open-source analytics and monitoring platform that allows users to visualize and analyze metrics from various data sources. The Grafana blog covers topics such as data visualization, monitoring best practices, and new features in Grafana software. Developers and data engineers can learn how to leverage Grafana for monitoring infrastructure, analyzing performance metrics, and creating interactive dashboards for data-driven decision-making.

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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.

Monitor Model Context Protocol (MCP) servers with OpenLIT and Grafana Cloud

Benefits of MCP observability in Grafana Cloud