llm_benchmark · LLM MCP Bridge MCP: Risk & Policy

WHAT IT DOES

What llm_benchmark does on LLM MCP Bridge

AI agents invoke llm_benchmark to trigger actions in LLM MCP Bridge. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call — builds kicked off, notifications sent, workflows started.

WHY IT NEEDS A POLICY

Why llm_benchmark needs a policy

This tool executes a benchmarking process by sending multiple prompts to an LLM model and measuring performance. It triggers external API calls and computational operations, placing it in the Execute category. The blast radius is medium since it could incur API costs, consume rate limits, or generate large volumes of requests against cloud or local LLM endpoints.

From the tool's definition 'Ejecuta un benchmark' (Executes a benchmark) with 'múltiples prompts para evaluar rendimiento del modelo' (multiple prompts to evaluate model performance) — actively runs/executes operations against an LLM API

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

llm_benchmark Rate-limited

llm_benchmark stays usable, but rate-capped — a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "llm_benchmark": {
      "limits": [
        {
          "counter": "llm_benchmark_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

RATE-LIMIT THIS TOOL →

Instant setup, no code required.

PolicyLayer is an MCP gateway: every tool call is checked against your rule before it reaches LLM MCP Bridge, so you can run agents against it safely.

FAQ

Questions about llm_benchmark

What does the llm_benchmark tool do? +

Ejecuta un benchmark con múltiples prompts para evaluar rendimiento del modelo. It is categorised as a Execute tool in the LLM MCP Bridge MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on llm_benchmark? +

Register the LLM MCP Bridge MCP server in PolicyLayer and add a rule for llm_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 LLM MCP Bridge. Nothing to install.

What risk level is llm_benchmark? +

llm_benchmark is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.

Can I rate-limit llm_benchmark? +

Yes. Add a rate_limit block to the llm_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 llm_benchmark completely? +

Set action: deny in the PolicyLayer policy for llm_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 llm_benchmark? +

llm_benchmark is provided by the LLM MCP Bridge MCP server (ramgeart/llm-mcp-bridge). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.