Display CPU and memory usage of pods, broken down by container.
AI agents call k8s_top_pods to retrieve information from Multi Cluster Kubernetes MCP Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool retrieves and presents resource usage statistics without creating, modifying, deleting, or executing any operations. It is purely informational monitoring data similar to 'kubectl top pods' which is a read-only diagnostic command. The blast radius of misuse is minimal—an agent could only over-query or gather resource information, posing no risk to cluster integrity or data.
From the tool's definition The tool 'k8s_top_pods' displays CPU and memory usage metrics of pods and containers. The verb 'display' and the metric-only nature (CPU, memory usage) indicate read-only querying of monitoring data with no modification or side effects.
Documented attack patterns abuse exactly the kind of access k8s_top_pods gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Multi Cluster Kubernetes MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for k8s_top_pods:
{
"version": "1",
"default": "deny",
"tools": {
"k8s_top_pods": {}
}
} k8s_top_pods is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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Display CPU and memory usage of pods, broken down by container. It is categorised as a Read tool in the Multi Cluster Kubernetes MCP Server MCP Server, which means it retrieves data without modifying state.
Register the Multi Cluster Kubernetes MCP Server MCP server in PolicyLayer and add a rule for k8s_top_pods: 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 Multi Cluster Kubernetes MCP Server. Nothing to install.
k8s_top_pods is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the k8s_top_pods 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 k8s_top_pods. 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.
k8s_top_pods is provided by the Multi Cluster Kubernetes MCP Server MCP server (razvanmacovei/k8s-multicluster-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Multi Cluster Kubernetes MCP Server, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
Free to start. No card required.
57 Multi Cluster Kubernetes MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.