gcp_compute_start_instance

Start a stopped VM instance

SERVERGCP MCP Server SOURCEahmedselimmansor-ctrl/gcp_mcp_server

High RISK CLASS

Category Execute

Parameters 00 required

Recommended Rate-limitedsee the rule below

Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/ahmedselimmansor-ctrl-gcp-mcp-server/gcp-compute-start-instance.md

WHAT IT DOES

What gcp_compute_start_instance does on GCP MCP Server

AI agents invoke gcp_compute_start_instance to trigger actions in GCP 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.

RISK

Why gcp_compute_start_instance is rated High

Starting a VM instance triggers external compute operations whose effects depend on which instance is specified as an argument. This is not merely querying data (Read), creating reversible configuration (Write), or irreversibly deleting resources (Destructive).

From the tool's definition Tool name 'gcp_compute_start_instance' and description 'Start a stopped VM instance' indicate execution of an infrastructure state change operation on a compute resource.

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs gcp_compute_start_instance safely

PolicyLayer is an MCP gateway: it sits between your AI agents and GCP MCP Server, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For gcp_compute_start_instance, this is the rule to start with:

gcp_compute_start_instance Rate-limited

gcp_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": {
    "gcp_compute_start_instance": {
      "limits": [
        {
          "counter": "gcp_compute_start_instance_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

RATE-LIMIT THIS TOOL → Instant setup, no code required.

The button opens the PolicyLayer dashboard: create your workspace, connect GCP MCP Server, apply this rule, and every gcp_compute_start_instance call is checked against it from then on.

FAQ

Questions about gcp_compute_start_instance

What does the gcp_compute_start_instance tool do? +

Start a stopped VM instance. It is categorised as a Execute tool in the GCP 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 gcp_compute_start_instance? +

Register the GCP MCP Server MCP server in PolicyLayer and add a rule for gcp_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 GCP MCP Server. Nothing to install.

What risk level is gcp_compute_start_instance? +

gcp_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 gcp_compute_start_instance? +

Yes. Add a rate_limit block to the gcp_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 gcp_compute_start_instance completely? +

Set action: deny in the PolicyLayer policy for gcp_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 gcp_compute_start_instance? +

gcp_compute_start_instance is provided by the GCP MCP Server MCP server (ahmedselimmansor-ctrl/gcp_mcp_server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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