gcp_run_execute_job

What gcp_run_execute_job does on GCP MCP Server

AI agents invoke gcp_run_execute_job 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.

Why gcp_run_execute_job is rated High

This tool runs code/workloads on Google Cloud Run, which is an external operation with side effects determined by the job definition. While not irreversible (Destructive) or financial, executing arbitrary jobs in production infrastructure poses significant risk if misused by an AI agent—jobs could consume resources, modify data, or trigger downstream processes. This clearly fits Execute rather than Write or Read.

From the tool's definition Tool name contains 'execute' and description states 'Execute a Cloud Run job', indicating it triggers external operations (Cloud Run job execution) whose effects depend on the job configuration and arguments provided.

The rule that runs gcp_run_execute_job 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_run_execute_job, this is the rule to start with:

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

Questions about gcp_run_execute_job