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.
A local MCP server for Kubernetes that applies RBAC-style, context-scoped access control to constrain AI agents, with tools for common Kubernetes operations.
An open source MCP server empowering SREs with intelligent observability, predictive analytics, and AI-driven automation across Kubernetes, OpenShift, and Tekton environments.
An MCP server designed to help AI models refactor Kubernetes configurations by analyzing Kustomize dependencies and rendering manifest diffs across environments. It provides tools for computing file dependencies, rendering overlays, and comparing configuration changes through a checkpointing system.
An MCP server that helps engineers investigate service incidents using semantic log search, error aggregation, RAG-based diagnosis, and runbook recommendations.
An MCP server for autonomous Kubernetes troubleshooting and remediation. It enables continuous cluster monitoring, local AI-powered diagnosis via Ollama, and automated kubectl-based fixes.