Netdata
Verified · 13 days agoReal-time infrastructure monitoring with metrics, logs, alerts, and ML-based anomaly detection.
Kubernetes MCP server with RBAC-style, context-scoped guardrails for AI agents.
claude mcp add kubeleash -- docker run -i --rm ghcr.io/kubeleash/kubeleash:0.3.0
A Kubernetes MCP server built around policy guardrails instead of simply handing an agent the full kubeconfig. It exposes generic list/get/apply/delete/logs/exec-style cluster tools with context-scoped policy, dry-run/audit behavior, and Go tests around the MCP limits. Very young project with almost no community signal, but the safety model is the point and the implementation is present.
Real-time infrastructure monitoring with metrics, logs, alerts, and ML-based anomaly detection.
Kubernetes port forwarding for local development with automatic /etc/hosts entries.
Cloudflare MCP servers
All Azure MCP tools to create a seamless connection between AI agents and Azure services.
Kubernetes visibility for AI agents: query workloads, events, logs, topology, and Helm releases.
A Model Context Protocol (MCP) server for Kubernetes and OpenShift