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Fraud Claim Detector MCP
x402
Fraud Claim Detector MCP is a paid API for AI agents from api.m2mcent.com, paid per call via x402, $0.2/call, status unknown (last checked 2026-10-15).
Analyzes submitted text or claim data to detect potential fraud, flagging suspicious patterns and providing a fraud assessment.
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 fraud assessment for the submitted data string, likely including a fraud likelihood score or classification, identified suspicious indicators or red flags, and a summary judgment on whether the claim appears fraudulent or legitimate.
Example use cases
Insurance claim fraud screening
“I need you to check this auto insurance claim for fraud signals: 'Claimant reports theft of a $35,000 vehicle with no surveillance footage, no witnesses, and the incident occurred two days before policy expiration.'”
E-commerce chargeback fraud check
“Can you analyze this chargeback claim for potential fraud? The customer says they never received the order but our shipping logs show delivery confirmation with a signature at their address.”
Benefits application fraud detection
“Please run fraud detection on this benefits application text: 'Applicant reports zero income for 3 years but lists ownership of two residential properties and a boat in the supporting documentation.'”
Technical details
Endpoint
POSThttps://api.m2mcent.com/fraud-claim-detector-mcp/api/process?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need automated, per-claim fraud screening at low cost ($0.20/call) without building internal ML models. Best suited for text-based claims, narratives, or structured claim descriptions that need rapid fraud risk assessment. Prefer this over manual review workflows or general-purpose LLM prompting when you want a specialized fraud-detection signal integrated into an agentic pipeline.
Side effects
- Empty or missing 'data' field returns a validation error
- Extremely short or ambiguous input may yield low-confidence results
- Non-textual or binary data in the string field may cause processing errors
- Rate limiting or payment failures may return 402 or 429 status codes
- Malformed JSON body returns 400 bad request
Output
Schema · Response
{
"type": "json",
"example": {
"success": true
}
}Tags
x402
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