describe_severity_levels

WHAT IT DOES

What describe_severity_levels does on Amazon Data Processing MCP Server

AI agents call describe_severity_levels 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 describe_severity_levels needs a policy

The tool appears to query or retrieve metadata about severity levels without side effects. However, confidence is reduced to 0.6 due to the empty description, which prevents certainty about the tool's actual behavior and any potential data sensitivity involved in exposing severity level information.

From the tool's definition Tool name 'describe_severity_levels' indicates a retrieval or query operation that returns information about severity level definitions or classifications. No action verbs suggesting modification, deletion, or execution are present.

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

POLICY

How to control describe_severity_levels

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 describe_severity_levels:

policy.json

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

describe_severity_levels 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 describe_severity_levels

What does the describe_severity_levels tool do? +

describe_severity_levels. 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 describe_severity_levels? +

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

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

Can I rate-limit describe_severity_levels? +

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

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

describe_severity_levels 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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