A comprehensive, AI-powered performance analysis and monitoring platform for OpenShift/Kubernetes clusters. This project provides Model Context Protocol (MCP) servers for analyzing etcd, network, and OVN-Kubernetes components with deep performance insights, automated root cause analysis, and actionable recommendations.
Enables diagnostics and troubleshooting of OpenShift clusters through storage analysis, resource monitoring, GPU utilization tracking, and pod health checks using Prometheus metrics and the oc CLI.
Monitors and analyzes Precision Time Protocol (PTP) systems in OpenShift clusters, enabling configuration analysis, real-time log monitoring, and health checks.
Enables real-time Kubernetes cluster observability and debugging through standardized MCP interface. Provides access to pods, services, nodes, events, and includes built-in tools for cluster health analysis and issue identification.
