AnalyzeAHORunPerformance

THE RISK

Low Risk

Why AnalyzeAHORunPerformance needs a policy

The tool name suggests it analyzes (reads and examines) performance data from AHO (AWS Health Omics) runs without modifying or executing external operations. Analysis typically retrieves and processes data for reporting purposes. However, the empty description prevents definitive classification of potential side effects, warranting medium confidence.

From the tool's definition Tool name 'AnalyzeAHORunPerformance' indicates analysis of performance metrics, which is a read operation. The tool description is empty, which reduces confidence.

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

POLICY

How to control AnalyzeAHORunPerformance

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

policy.json

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

AnalyzeAHORunPerformance 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 AWS Serverless 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.

CAP THIS TOOL →

Free to start. No card required.

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 AnalyzeAHORunPerformance

What does the AnalyzeAHORunPerformance tool do? +

AnalyzeAHORunPerformance. It is categorised as a Read tool in the AWS Serverless MCP Server MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on AnalyzeAHORunPerformance? +

Register the AWS Serverless MCP Server MCP server in PolicyLayer and add a rule for AnalyzeAHORunPerformance: 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 AWS Serverless MCP Server. Nothing to install.

What risk level is AnalyzeAHORunPerformance? +

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

Can I rate-limit AnalyzeAHORunPerformance? +

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

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

AnalyzeAHORunPerformance is provided by the AWS Serverless MCP Server MCP server (awslabs.aws-serverless-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 AWS Serverless MCP Server tool call.

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

CHECK YOUR STACK →