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Connect multiple Prometheus instances for AI-driven metrics analysis and SRE troubleshooting.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "Proms MCP Server" yet — see the docs or source repo.
Connect to the available Prometheus instances and inspect payment-service P95 latency, error rate, and request volume over the last 6 hours. Identify when the anomaly started and summarize likely causes.
A troubleshooting summary with key metric changes, anomaly timing, and likely root causes.
Compare CPU, memory, and pod restarts over the last 24 hours between production and staging clusters across multiple Prometheus instances, and identify the services with the largest differences.
A cross-cluster resource comparison highlighting services with the most significant differences.
Query the metrics behind the 'high node disk usage' alert, review the last 12 hours of trends, determine whether the alert is persistent and business-impacting, and provide handling recommendations.
An assessment of alert validity, impact, and recommended next steps.
Query Prometheus metrics with PromQL and analyze monitoring trends and anomalies.
Improve model outputs to expert-level quality through iterative creative direction.
Create, manage, and compose AI agents for MCP-compatible clients and tools.
Connect to the mcp API via MCP to extend AI tool capabilities.
Use one MCP server for filesystem, database, web, and system operations.
Test all MCP protocol features when building and validating clients.