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Query Prometheus metrics with PromQL and analyze monitoring trends and anomalies.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "Prometheus MCP Server" yet — see the docs or source repo.
Query the HTTP 5xx error rate trend for payment-service over the past 6 hours at 5-minute intervals, and determine whether it started rising significantly at a specific time.
Provides the relevant PromQL query results and summarizes the error rate trend, anomaly start time, and key investigation points.
Check CPU and memory usage for each node in the production cluster over the past 24 hours, identify nodes under sustained high load, and provide a brief analysis.
Outputs node-level resource analysis, highlighting overloaded nodes, duration of high usage, and potential capacity risks.
Query the P95 database request latency over the last hour and compare it with historical trends to determine whether the high-latency alert is a real anomaly.
Returns latency query results and explains whether the alert is justified, how severe the anomaly is, and the reasoning behind it.
Connect multiple Prometheus instances for AI-driven metrics analysis and SRE troubleshooting.
Query real-time and historical server metrics from Prometheus for monitoring and troubleshooting.
Manage MySQL databases with natural language for queries, CRUD, and monitoring.
Track AI usage, costs, logs, and debug model interactions across apps.
Query metrics and dimensions with MetricFlow through natural language interfaces.
Connect to Grafana dashboards, data sources, and alerts for monitoring analysis.