predict_performance_impact

THE RISK

Low Risk

Why predict_performance_impact needs a policy

This tool performs static analysis of provided code to identify performance issues. It only reads/analyzes input data and produces warnings/recommendations. No code is executed, no data is written, and no external systems are modified. The blast radius of misuse is minimal as it is purely advisory.

From the tool's definition 'Analyze a code snippet and warn about potential performance issues' — read-only analysis with no side effects

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

POLICY

How to control predict_performance_impact

PolicyLayer is an MCP gateway — it sits between your AI agents and Mcp Game Helper, and nothing reaches the server without passing your rules. This is the rule we recommend for predict_performance_impact:

policy.json

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

predict_performance_impact 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 Mcp Game Helper — 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

Related tools and policies

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Go deeper

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 →

FAQ

Questions about predict_performance_impact

What does the predict_performance_impact tool do? +

Analyze a code snippet and warn about potential performance issues. It is categorised as a Read tool in the Mcp Game Helper MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on predict_performance_impact? +

Register the Mcp Game Helper MCP server in PolicyLayer and add a rule for predict_performance_impact: 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 Mcp Game Helper. Nothing to install.

What risk level is predict_performance_impact? +

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

Can I rate-limit predict_performance_impact? +

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

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

predict_performance_impact is provided by the Mcp Game Helper MCP server (xhulz/mcp-game-helper). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Mcp Game Helper tool call.

Start from Mcp Game Helper, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.

CHECK YOUR STACK →