Low Risk

latency_benchmark

Measure response time of one or more HTTP endpoints (GET/POST). Runs N iterations and returns min/max/avg/p95 latency. Useful for API and MCP server benchmarking.

Risk signalsAccepts URL/endpoint input (endpoints[].url) · Accepts raw HTML/template content (endpoints[].body)

Part of the Ia Qa Com/mcp llm and RAG testing Dev/QA toolbox server.

latency_benchmark is read-only, but an agent in a loop can still rack up calls and cost. PolicyLayer caps every call before it runs. Live in minutes.

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AI agents call latency_benchmark to retrieve information from Ia Qa Com/mcp llm and RAG testing Dev/QA toolbox without modifying any data. This is common in research, monitoring, and reporting workflows where the agent needs context before taking action. Because read operations don't change state, they are generally safe to allow without restrictions -- but you may still want rate limits to control API costs.

Even though latency_benchmark only reads data, uncontrolled read access can leak sensitive information or rack up API costs. An agent caught in a retry loop could make thousands of calls per minute. A rate limit gives you a safety net without blocking legitimate use.

Read-only tools are safe to allow by default. No rate limit needed unless you want to control costs.

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "latency_benchmark": {}
  }
}

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These attack patterns abuse exactly the kind of access latency_benchmark gives an agent. Each links to the full case and the policy that stops it:

Browse the full MCP Attack Database →

Every attack above starts with a tool call. PolicyLayer checks each one against your policy first, so latency_benchmark only ever does what you allow.

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Other read tools across the catalogue. The same approach applies to each: allow, with a rate cap to control cost.

What does the latency_benchmark tool do? +

Measure response time of one or more HTTP endpoints (GET/POST). Runs N iterations and returns min/max/avg/p95 latency. Useful for API and MCP server benchmarking.. It is categorised as a Read tool in the Ia Qa Com/mcp llm and RAG testing Dev/QA toolbox MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on latency_benchmark? +

Register the Ia Qa Com/mcp llm and RAG testing Dev/QA toolbox MCP server in PolicyLayer and add a rule for latency_benchmark: 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 Ia Qa Com/mcp llm and RAG testing Dev/QA toolbox. Nothing to install.

What risk level is latency_benchmark? +

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

Can I rate-limit latency_benchmark? +

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

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

latency_benchmark is provided by the Ia Qa Com/mcp llm and RAG testing Dev/QA toolbox MCP server (ia-qa/api). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Ia Qa Com/mcp llm and RAG testing Dev/QA toolbox tool call.

Deterministic rules across all 139 Ia Qa Com/mcp llm and RAG testing Dev/QA toolbox tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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