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Premium Risk Scorer MCP
x402
Premium Risk Scorer MCP is a paid API for AI agents from api.m2mcent.com, paid per call via x402, $0.2/call, status unknown (last checked 2026-09-15).
Scores and assesses premium risk for a given input, returning a risk evaluation or score
Price / call$0.2
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 risk score or rating for the submitted data, likely including a numeric score, risk classification (e.g. low/medium/high), and potentially supporting detail or confidence indicators about the assessed risk level.
Example use cases
Insurance underwriting risk triage
“Score the risk for this insurance applicant: 'age 38, non-smoker, BMI 27, no prior claims, annual income $75,000' — I need to know if they're low, medium, or high risk before we proceed with the quote.”
Financial loan default risk check
“Assess the premium risk on this borrower profile: 'credit score 620, debt-to-income ratio 42%, self-employed 2 years, loan amount $50,000' so I can decide whether to flag it for manual review.”
Real-time fraud or anomaly risk flagging
“Run a risk score on this transaction record: 'amount $4,800, merchant category: electronics, location: foreign IP, account age 3 months' and tell me how risky it looks.”
Technical details
Endpoint
POSThttps://api.m2mcent.com/premium-risk-scorer-mcp/api/processWhen to prefer
Choose this endpoint when you need a rapid, automated premium risk score on a data record without building your own scoring model — especially useful in underwriting, loan origination, fraud detection, or any context where a risk rating must be computed programmatically at $0.20 per call.
Side effects
- Empty or malformed data string returns a validation error
- Ambiguous or insufficient data may produce a low-confidence score
- Service may return 402 Payment Required if payment is not attached
- Timeouts possible for very large data payloads
- Non-English or unstructured data may reduce scoring accuracy
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| payload | string |
Output
Schema · Response
{
"type": "json",
"example": {
"success": true
}
}Tags
x402
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