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stop_application

stop_application

How to control stop_application ↓

What stop_application does on Amazon Data Processing MCP Server

AI agents invoke stop_application to trigger actions in Amazon Data Processing 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.

High Risk

Why stop_application needs a policy

Stopping an application is an Execute-class action—it triggers an external operation (application termination) whose effects are immediate and depend on which application is targeted. While potentially reversible by restarting, it causes immediate service disruption. High severity due to potential blast radius on dependent systems and business continuity.

From the tool's definition Tool name 'stop_application' indicates termination of an application or service; the empty description prevents definitive assessment but the action name implies operational control with immediate effects.

Documented attack patterns abuse exactly the kind of access stop_application gives an agent:

How to control stop_application

PolicyLayer is an MCP gateway — it sits between your AI agents and Amazon Data Processing MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for stop_application:

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "stop_application": {
      "limits": [
        {
          "counter": "stop_application_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

stop_application 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.

  1. Create a free account and register Amazon Data Processing MCP Server — nothing to install.
  2. Add this policy — paste it, or build it visually.
  3. Point your MCP client (Claude, Cursor, anything) at your gateway URL.
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Related tools and policies

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Questions about stop_application

What does the stop_application tool do? +

stop_application. It is categorised as a Execute tool in the Amazon Data Processing 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 stop_application? +

Register the Amazon Data Processing MCP Server MCP server in PolicyLayer and add a rule for stop_application: 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 Data Processing MCP Server. Nothing to install.

What risk level is stop_application? +

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

Can I rate-limit stop_application? +

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

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

stop_application is provided by the Amazon Data Processing MCP Server MCP server (awslabs.aws-dataprocessing-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Amazon Data Processing MCP Server tool call.

Start from Amazon Data Processing MCP Server, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.

Free to start. No card required.

805 Amazon Data Processing MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.

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