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LLM Benchmark Evaluator MCP
x402
LLM Benchmark Evaluator MCP is a paid API for AI agents from api.m2mcent.com, paid per call via x402, $0.22/call, status unknown (last checked 2026-10-11).
Evaluates and benchmarks large language model outputs against standard or custom performance metrics
Price / call$0.22
Success—
StatusUnknown
How this service works
The premier global index of 1,069 monetized MCP nodes across 205 specialized subdomains. Gasless USDC runtime settlements via x402 V2 Spec on Base L2. Save 95% token context.
Output
Returns a benchmark evaluation result including quality scores, performance metrics, and assessment details for the submitted LLM output text.
Example use cases
Automated model quality regression check
“I just updated my fine-tuned model and want to make sure it didn't regress — can you run a benchmark evaluation on this sample output: 'Photosynthesis converts sunlight into glucose using chlorophyll in plant cells.'”
Compare LLM outputs for prompt engineering
“I'm testing two different prompt versions — can you benchmark this response for me: 'Machine learning is a subset of AI that allows systems to learn from data without being explicitly programmed.' I want to know how it scores on quality metrics.”
Pre-deployment LLM performance audit
“Before we ship this chatbot to production, can you run an LLM benchmark evaluation on its response to a factual question? Here's what it said: 'Water boils at 100 degrees Celsius at standard atmospheric pressure.'”
Technical details
Endpoint
POSThttps://api.m2mcent.com/llm-benchmark-evaluator-mcp/api/process?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need programmatic, per-call LLM output evaluation or benchmarking without setting up your own evaluation infrastructure. Best suited for agents that need to score or quality-check model-generated text on demand, especially in automated pipelines or regression testing workflows.
Side effects
- Empty or missing 'data' field returns validation error
- Malformed input string may return low-confidence or error result
- Service unavailable or timeout on large input payloads
- Ambiguous or very short inputs may yield low-signal scores
- Payment failure via x402 protocol blocks request execution
Output
Schema · Response
{
"type": "json",
"example": {
"success": true
}
}Tags
x402
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Zero review prompt (fires after every successful call)
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