compute_start_instance · Google Cloud MCP: Risk & Policy

WHAT IT DOES

What compute_start_instance does on Google Cloud

AI agents invoke compute_start_instance to trigger actions in Google Cloud. 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 compute_start_instance needs a policy

Starting a Compute Engine instance is an operational action that initiates external compute resources and can incur financial costs, consume quota, and enable subsequent workloads. While not destructive (the instance can be stopped) or directly financial (no direct money movement), it is an Execute action because it triggers infrastructure state changes based on arguments provided by the caller.

From the tool's definition Tool name 'compute_start_instance' and description 'Start a Compute Engine instance' indicate the tool triggers an external operation (starting a VM instance) whose effects depend on which instance is specified as an argument.

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

compute_start_instance Rate-limited

compute_start_instance 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": {
    "compute_start_instance": {
      "limits": [
        {
          "counter": "compute_start_instance_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 Google Cloud, so you can run agents against it safely.

FAQ

Questions about compute_start_instance

What does the compute_start_instance tool do? +

Start a Compute Engine instance. It is categorised as a Execute tool in the Google Cloud MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on compute_start_instance? +

Register the Google Cloud MCP server in PolicyLayer and add a rule for compute_start_instance: 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 Google Cloud. Nothing to install.

What risk level is compute_start_instance? +

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

Can I rate-limit compute_start_instance? +

Yes. Add a rate_limit block to the compute_start_instance 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 compute_start_instance completely? +

Set action: deny in the PolicyLayer policy for compute_start_instance. 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 compute_start_instance? +

compute_start_instance is provided by the Google Cloud MCP server (lockon-n/google-cloud-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.