manage_aws_emr_serverless_job_runs

WHAT IT DOES

What manage_aws_emr_serverless_job_runs does on Amazon MQ MCP Server

AI agents invoke manage_aws_emr_serverless_job_runs to trigger actions in Amazon MQ 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 manage_aws_emr_serverless_job_runs needs a policy

The tool name implies execution control over AWS EMR Serverless job runs (start, stop, cancel operations). EMR jobs can process large datasets and incur significant costs. However, the description is empty, so the classification is based solely on the name. 'Manage' could span Read through Execute categories; given job runs context, Execute is most likely. Confidence is lowered due to the empty description.

From the tool's definition Tool name: manage_aws_emr_serverless_job_runs — 'manage' and 'job_runs' suggest starting, stopping, or controlling EMR Serverless job executions

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

manage_aws_emr_serverless_job_runs Rate-limited

manage_aws_emr_serverless_job_runs 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": {
    "manage_aws_emr_serverless_job_runs": {
      "limits": [
        {
          "counter": "manage_aws_emr_serverless_job_runs_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 Amazon MQ MCP Server, so you can run agents against it safely.

FAQ

Questions about manage_aws_emr_serverless_job_runs

What does the manage_aws_emr_serverless_job_runs tool do? +

manage_aws_emr_serverless_job_runs. It is categorised as a Execute tool in the Amazon MQ 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 manage_aws_emr_serverless_job_runs? +

Register the Amazon MQ MCP Server MCP server in PolicyLayer and add a rule for manage_aws_emr_serverless_job_runs: 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 Amazon MQ MCP Server. Nothing to install.

What risk level is manage_aws_emr_serverless_job_runs? +

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

Can I rate-limit manage_aws_emr_serverless_job_runs? +

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

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

manage_aws_emr_serverless_job_runs is provided by the Amazon MQ MCP Server MCP server (awslabs.amazon-mq-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.