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kubectl-mcp-server enables natural language interaction with Kubernetes clusters, allowing users to manage and troubleshoot their infrastructure via AI assistants.
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kubectl-mcp-server enables natural language interaction with Kubernetes clusters, allowing users to manage and troubleshoot their infrastructure via AI assistants.
kubectl-mcp-server offers a convenient way to interact with Kubernetes using natural language. It's relatively safe for read-only operations and exploration. However, caution is advised when performing write operations, and proper RBAC configuration is crucial to mitigate risks.
Performance depends on the size and complexity of the Kubernetes cluster. Large clusters may experience slower response times.
Cost is primarily associated with the AI assistant's usage and any associated API calls. The kubectl-mcp-server itself has minimal resource requirements.
npm install -g skillkit{
"mcpServers": {
"kubernetes": {
"command": "npx",
"args": ["-y", "kubectl-mcp-server"]
}
}
}MCP_AUTH_JWKS_URIMCP_BROWSER_CDP_URLget_podsRetrieves a list of pods in a specified namespace.
Read-only operation, no modification of cluster state.
create_deploymentCreates a new deployment in the Kubernetes cluster.
Creates resources, but doesn't directly impact existing critical components.
scale_deploymentScales the number of replicas for a given deployment.
Modifies the number of pods, potentially impacting application availability.
exec_podExecutes a command inside a specified pod.
Allows arbitrary command execution within a pod, potentially leading to security breaches.
delete_podDeletes a pod from the cluster.
Destructive operation that can cause service disruption.
Token
hybrid
kubectl-mcp-server offers a convenient way to interact with Kubernetes using natural language. It's relatively safe for read-only operations and exploration. However, caution is advised when performing write operations, and proper RBAC configuration is crucial to mitigate risks.
Autonomy depends on the AI assistant's capabilities and configuration. Exercise caution when granting full autonomy, especially with destructive tools.
Production Tip
Use dry-run mode and thorough testing in a non-production environment before applying changes to production clusters.
kubectl-mcp-server supports the same Kubernetes versions as the underlying kubectl client.
Configure RBAC roles and role bindings to grant the necessary permissions to the service account used by kubectl-mcp-server.
Yes, kubectl-mcp-server supports multi-cluster environments by leveraging kubectl's context switching capabilities.
Enable authentication, use RBAC to restrict access, and regularly audit configurations.
kubectl-mcp-server is compatible with any MCP-compatible AI assistant, including Claude, Cursor, and GitHub Copilot.
Yes, but thorough testing and security precautions are recommended before deploying to production.
Check the logs for errors, verify kubectl configuration, and ensure the AI assistant is properly configured.