get_execution_plan · Amazon Data Processing MCP Server MCP

WHAT IT DOES

What get_execution_plan does on Amazon Data Processing MCP Server

AI agents call get_execution_plan to retrieve information from Amazon Data Processing MCP Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.

THE RISK

Low Risk

Why get_execution_plan needs a policy

The 'get_' prefix and 'plan' retrieval pattern indicate a query or retrieval operation with no apparent side effects. This maps to the Read category. Severity is medium rather than low because execution plans in AWS data processing contexts may expose sensitive details about system configurations, data flow, or infrastructure topology that could inform attacks.

From the tool's definition Tool name 'get_execution_plan' suggests retrieval of an execution plan, consistent with Read operations (get, fetch). However, the description is empty, which limits certainty about its precise function and blast radius.

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

POLICY

How to control get_execution_plan

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 get_execution_plan:

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "get_execution_plan": {}
  }
}

get_execution_plan is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.

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

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EXPLORE

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Go deeper

Roll out MCP under one policy → Per-person scoped tokens, one central policy, and full audit across every server your team connects.
The MCP Attack Database → Documented attack patterns against MCP deployments — and the policies that stop them.
Data exfiltration → How read access becomes an exfiltration channel when chained with untrusted content.
MCP token cost → What connecting this server costs in context-window tokens on every request.
Rate Limiting MCP Tool Calls: A Practical Guide →
MCP Security: Why Prompt Guardrails Aren't Enough →
PolicyLayer vs alternatives → How deterministic, per-call MCP policy compares with gateways, identity layers, and authorisation platforms.

FAQ

Questions about get_execution_plan

What does the get_execution_plan tool do? +

get_execution_plan. It is categorised as a Read tool in the Amazon Data Processing MCP Server MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on get_execution_plan? +

Register the Amazon Data Processing MCP Server MCP server in PolicyLayer and add a rule for get_execution_plan: 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 get_execution_plan? +

get_execution_plan is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit get_execution_plan? +

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

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

get_execution_plan 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.

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