kubeview-mcp
Verified Safeby mikhae1
Overview
Enables AI agents to inspect, diagnose, and debug Kubernetes clusters through a read-only Model Context Protocol (MCP) server.
Installation
npx -y kubeview-mcpEnvironment Variables
- KUBECONFIG
- MCP_MODE
- MCP_LOG_LEVEL
- MCP_HIDE_SENSITIVE
- MCP_KUBE_CONTEXT
- MCP_K8S_SKIP_TLS_VERIFY
- ARGOCD_SERVER
- ARGOCD_AUTH_TOKEN
- MCP_KUBE_METRICS_DISABLE_KUBELET
- MCP_DISABLE_HELM_PLUGIN
- MCP_DISABLE_ARGO_PLUGIN
- MCP_DISABLE_ARGOCD_PLUGIN
- MCP_LOG_FILE
- HELM_TIMEOUT
- ARGO_TIMEOUT
- ARGOCD_TIMEOUT
Security Notes
The server uses a sandboxed Node.js `vm` environment for executing agent-provided TypeScript code (`run_code`), which enhances isolation. Sensitive data masking is implemented for ConfigMaps and Secrets, and is configurable (`MCP_HIDE_SENSITIVE`). However, while the server's direct interaction with the Kubernetes API aims to be read-only, the `kube_exec` tool allows agents to execute arbitrary commands inside specific containers within pods. This means an agent could instruct the tool to perform write operations or other non-read-only actions within a running workload, potentially impacting applications. Similarly, `kube_port` can establish temporary port-forwards, exposing internal services locally. Users and AI agents should exercise caution when utilizing these powerful capabilities.
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