{"id":"xwomen1-mcp-k8s-server","name":"mcp-k8s-server","af_score":44.0,"security_score":39.2,"reliability_score":17.5,"what_it_does":"An MCP (Model Context Protocol) server that provides Kubernetes management tools to AI clients, enabling operations such as applying manifests (including server-side apply), dry-run validation, viewing/scaling workload resources, log streaming, port-forwarding, and multi-cluster context switching.","best_when":"You have an MCP-capable AI client and a controlled environment where the server can safely execute Kubernetes API actions using a known kubeconfig/service account and scoped RBAC permissions.","avoid_when":"You cannot restrict RBAC permissions and network access; or you need documented rate limits, strong auth, and concrete error/pagination/retry contracts for reliable agent automation.","last_evaluated":"2026-04-04T19:51:10.399047+00:00","has_mcp":true,"has_api":false,"auth_methods":["Kubeconfig path via KUBECONFIG_PATH (implied)"],"has_free_tier":false,"known_gotchas":["Kubernetes operations can be destructive; tool calls that 'apply' arbitrary resources require strict RBAC and client-side validation.","Port-forwarding/tunneling requires careful session lifecycle handling (start/stop) to avoid lingering access.","Multi-cluster support increases risk of applying manifests to the wrong cluster context without strong safeguards.","Dry-run validation depends on kube-apiserver behavior and permissions; agents may misinterpret dry-run results if RBAC differs from real apply."],"error_quality":0.0}