@Flux159
基本信息
MCP Server for kubernetes management commands
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"kubernetes": {
"command": "npx",
"args": [
"mcp-server-kubernetes"
]
}
}
}Cleanup all managed resources
Get or list Kubernetes resources by resource type, name, and optionally namespace
Describe Kubernetes resources by resource type, name, and optionally namespace
Apply a Kubernetes YAML manifest from a string or file
Delete Kubernetes resources by resource type, name, labels, or from a manifest file
Create Kubernetes resources using various methods (from file or using subcommands)
Get logs from Kubernetes resources like pods, deployments, or jobs
Scale a Kubernetes deployment
Update field(s) of a resource using strategic merge patch, JSON merge patch, or JSON patch
Manage the rollout of a resource (e.g., deployment, daemonset, statefulset)
Manage Kubernetes contexts - list, get, or set the current context
Reconnect to the Kubernetes API server by recreating all API clients. Use this after cluster upgrades (e.g., EKS control plane upgrades that rotate ENIs/IPs) to force fresh DNS resolution and new TCP connections.
Get documentation for a Kubernetes resource or field
Install a Helm chart with support for both standard and template-based installation
Upgrade an existing Helm chart release
Uninstall a Helm chart release
Manage Kubernetes nodes with cordon, drain, and uncordon operations
Forward a local port to a port on a Kubernetes resource
Stop a port-forward process
Execute a command in a Kubernetes pod or container and return the output. Command must be an array of strings where the first element is the executable and remaining elements are arguments. This executes directly without shell interpretation for security.
List the API resources available in the cluster
Execute any kubectl command with the provided arguments and flags
Verify that the counterpart is still responsive and the connection is alive.
MCP Server Kubernetes is a Model Context Protocol server that connects to a Kubernetes cluster and enables AI assistants to manage it. It loads kubeconfig from multiple sources in priority order and integrates with clients such as Claude Code, Claude Desktop, VS Code, Cursor, and Gemini CLI. It is intended for developers who need AI-assisted Kubernetes operations.
Install it via npx (e.g., npx mcp-server-kubernetes) and configure the server in your MCP client’s settings (e.g., claude mcp add kubernetes -- npx mcp-server-kubernetes). The server automatically uses your current kubectl context. Prerequisites: kubectl in PATH, a valid kubeconfig, and cluster access; Helm v3 is optional.
You need kubectl installed and in your PATH, a valid kubeconfig file with configured contexts, and access to a Kubernetes cluster (e.g., minikube, Rancher Desktop, GKE). Helm v3 is optional.
Set the environment variable `ALLOW_ONLY_NON_DESTRUCTIVE_TOOLS=true` when starting the server. This disables all destructive operations (delete, drain, etc.) while keeping read and create/update tools available.
Yes, it includes optional OpenTelemetry integration (disabled by default). Enable it with `ENABLE_TELEMETRY=true` and configure `OTEL_EXPORTER_OTLP_ENDPOINT`. Traces can be sent to Jaeger, Grafana Tempo, Datadog, New Relic, and other OTLP-compatible backends.
By default, it loads kubeconfig from `~/.kube/config`. Additional authentication options (environment variables, custom paths) are described in the advanced documentation.
It uses stdio transport configured through your MCP client. Authentication relies on your existing kubectl context and kubeconfig; no separate credentials are managed by the server itself.
Connect Supabase to your AI assistants
MCP server connecting to Kubernetes
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