create_batch_job · Dataproc MCP Server MCP: Risk & Policy

WHAT IT DOES

What create_batch_job does on Dataproc MCP Server

AI agents invoke create_batch_job to trigger actions in Dataproc 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 create_batch_job needs a policy

The tool name 'create_batch_job' strongly implies submitting/executing a batch job (likely Spark, PySpark, Hive, etc.) on Google Cloud Dataproc. Job submission triggers external computation with potentially significant resource consumption and side effects. While the description is empty (lowering confidence), the server context makes Execute the most appropriate category.

From the tool's definition Tool name 'create_batch_job' on a server that 'Supports cluster creation/deletion, job submission (Spark, PySpark, Hive, etc.), and serverless batch operations'

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

create_batch_job Rate-limited

create_batch_job 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": {
    "create_batch_job": {
      "limits": [
        {
          "counter": "create_batch_job_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 Dataproc MCP Server, so you can run agents against it safely.

FAQ

Questions about create_batch_job

What does the create_batch_job tool do? +

create_batch_job. It is categorised as a Execute tool in the Dataproc 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 create_batch_job? +

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

What risk level is create_batch_job? +

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

Can I rate-limit create_batch_job? +

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

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

create_batch_job is provided by the Dataproc MCP Server MCP server (warrenzhu25/dataproc-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.