cleanup
AI agents call cleanup to permanently remove resources in Kube — typically in cleanup and lifecycle workflows. It does its job in a single call, and there is no undo.
In Kubernetes contexts, 'cleanup' almost universally implies bulk removal of resources (pods, deployments, services, namespaces, etc.), which is irreversible. Given the server's purpose of managing Kubernetes clusters and the presence of sibling delete tools, 'cleanup' likely performs broad destructive operations.
From the tool's definition Tool name 'cleanup' on a Kubernetes MCP server that also exposes 'delete_pod' and other destructive operations; description is empty and uninformative.
Attacks that exploit this kind of access
cleanup. It is categorised as a Destructive tool in the Kube MCP Server, which means it can permanently delete or destroy data. Block by default and require explicit approval.
Register the Kube MCP server in PolicyLayer and add a rule for cleanup: 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 Kube. Nothing to install.
cleanup 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 cleanup 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 cleanup. 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.
cleanup is provided by the Kube MCP server (lochgeo/kube-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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