k8s_scale_deployment · Kubernetes MCP Server MCP

WHAT IT DOES

What k8s_scale_deployment does on Kubernetes MCP Server

AI agents invoke k8s_scale_deployment to trigger actions in Kubernetes MCP Server. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call — builds kicked off, notifications sent, workflows started.

WHY IT NEEDS A POLICY

Why k8s_scale_deployment needs a policy

This tool executes commands that modify Kubernetes deployment replicas, causing immediate infrastructure changes whose effects depend on the numeric argument (replica count) provided. While not destructive (reversible by rescaling) or financial, it actively executes operational changes affecting cluster state and resource utilization.

From the tool's definition Tool name 'k8s_scale_deployment' with description 'Scale a deployment to a specific number of replicas' performs operational execution that triggers external effects on Kubernetes infrastructure.

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

k8s_scale_deployment Rate-limited

k8s_scale_deployment stays usable, but rate-capped — a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "k8s_scale_deployment": {
      "limits": [
        {
          "counter": "k8s_scale_deployment_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

RATE-LIMIT THIS TOOL →

Instant setup, no code required.

PolicyLayer is an MCP gateway: every tool call is checked against your rule before it reaches Kubernetes MCP Server, so you can run agents against it safely.

FAQ

Questions about k8s_scale_deployment

What does the k8s_scale_deployment tool do? +

Scale a deployment to a specific number of replicas. It is categorised as a Execute tool in the Kubernetes MCP Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on k8s_scale_deployment? +

Register the Kubernetes MCP Server MCP server in PolicyLayer and add a rule for k8s_scale_deployment: 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 MCP Server. Nothing to install.

What risk level is k8s_scale_deployment? +

k8s_scale_deployment is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.

Can I rate-limit k8s_scale_deployment? +

Yes. Add a rate_limit block to the k8s_scale_deployment 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.

How do I block k8s_scale_deployment completely? +

Set action: deny in the PolicyLayer policy for k8s_scale_deployment. 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.

What MCP server provides k8s_scale_deployment? +

k8s_scale_deployment is provided by the Kubernetes MCP Server MCP server (mjrestivo16/mcp-kubernetes). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.