AI-powered Kubernetes diagnostics that analyzes pod crashes, logs, and cluster health to provide root cause analysis and actionable solutions for common issues like CrashLoopBackOff, OOM kills, and connection errors.
An MCP server exposing Kubernetes-style diagnostic tools to an LLM agent, with a safety approval gate for destructive actions, all backed by a mock cluster for local testing.
Enables AI agents to safely observe and troubleshoot Kubernetes workloads, with limited recovery actions like pod deletion and Helm rollbacks, while preventing dangerous modifications.
MCP server that connects LLMs to Kubernetes clusters for troubleshooting, scanning failing pods, diagnosing root causes, and applying guarded fixes or generating manifests via natural language.