Delete a Kubernetes resource in the current cluster by providing its apiVersion, kind, optionally the namespace, and its name
Part of the Kubernetes server.
Free to start. No card required.
AI agents may call resources_delete to permanently remove or destroy resources in Kubernetes. Without a policy, an autonomous agent could delete critical data in a loop with no way to undo the damage. PolicyLayer blocks destructive tools by default and requires explicit human approval before enabling them.
Without a policy, an AI agent could call resources_delete in a loop, permanently destroying resources in Kubernetes. There is no undo for destructive operations. PolicyLayer blocks this tool by default and only allows it when a human explicitly approves the action.
Destructive tools permanently remove data. Block by default. Only enable with explicit approval workflows.
{
"version": "1",
"default": "deny",
"hide": [
"resources_delete"
]
}See the full Kubernetes policy for all 45 tools.
These attack patterns abuse exactly the kind of access resources_delete gives an agent. Each links to the full case and the policy that stops it:
Other destructive tools across the catalogue. The same approach applies to each: deny by default, or require human approval.
Delete a Kubernetes resource in the current cluster by providing its apiVersion, kind, optionally the namespace, and its name. It is categorised as a Destructive tool in the Kubernetes MCP Server, which means it can permanently delete or destroy data. Block by default and require explicit approval.
Register the Kubernetes MCP server in PolicyLayer and add a rule for resources_delete: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Kubernetes. Nothing to install.
resources_delete is a Destructive tool with critical risk. Critical-risk tools should be blocked by default and only enabled with explicit human approval.
Yes. Add a rate_limit block to the resources_delete rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for resources_delete. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
resources_delete is provided by the Kubernetes MCP server (kubernetes-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 45 Kubernetes tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
Free to start. No card required.
4,600+ MCP servers and 31,000+ tools scanned and risk-classified.