{"uid":"cap_POBQ0i3TmBZTyzo_yrbwN","slug":"m2mcent-healthcare-fraud-detection-aggregator-mcp-abe798e1","name":"M2MCent Healthcare Fraud Detection Aggregator MCP","description":"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.","url":"https://api.m2mcent.com/healthcare-fraud-detection-aggregator-mcp-283/api/execute?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","required":["text"],"properties":{"text":{"type":"string"}}},"responseSchema":{"type":"object","required":["result"],"properties":{"result":{"type":"boolean"}}},"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.15","displayCostAsset":"USDC","priceDynamic":false,"priceHint":null,"priceStatus":"priced","priceSource":"probe","requiresHandshake":false,"reviewCount":0,"rating":{"score":"0.00","successRate":"0.00","reviews":0,"stars":null,"state":"unrated"},"availabilityStatus":"unknown","priceObserved":null,"sessionDeposit":null,"pricing":{"kind":"static","summary":"$0.487839/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.487839","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.487839","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_plkA8CKbLa4btjvlf_eOl","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.487839","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Analyzes a text input and returns a boolean indicating whether healthcare fraud is detected","exampleAgentPrompt":"Can you check this healthcare claim text for fraud: 'Patient billed for 3 MRI scans on the same day at different facilities under identical procedure codes' — tell me if it's fraudulent or not.","exampleUseCases":[{"title":"Insurance claim fraud screening","prompt":"I have this insurance claim description: 'Physician billed for 12 office visits in a single day for the same patient under Medicare.' Can you run it through the healthcare fraud detector and tell me if it flags as fraudulent?"},{"title":"Medical billing compliance check","prompt":"Check this billing note for fraud signals: 'Duplicate claims submitted for the same procedure on 03/15 and 03/16 under two different provider NPI numbers for the same patient.'"},{"title":"Suspicious provider activity review","prompt":"Analyze this text for healthcare fraud: 'Provider consistently upcodes routine checkups as complex visits and bills for services not documented in patient records.' Does the fraud detection model flag this?"}],"resultDescription":"Returns a JSON object with a single boolean field 'result' — true if healthcare fraud is detected in the input text, false if no fraud is detected.","failureModes":["Missing required 'text' field returns a validation error","Empty or very short text may produce unreliable boolean results","Payment failure via x402 protocol returns HTTP 402 before execution","Ambiguous or non-healthcare text may yield false positives or false negatives","Network timeout on Base L2 settlement may delay or fail the call"],"whenToPreferThis":"Use this endpoint when you need a fast, low-latency boolean fraud signal on healthcare claim or billing text and want a pay-per-call model with no subscription overhead. Prefer this over general-purpose LLM classification when you need a specialized healthcare fraud detection model with deterministic output format and gasless USDC micropayment settlement.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-13T06:51:43.685Z","isFirstParty":false,"canonicalSlug":"m2mcent-healthcare-fraud-detection-aggregator-mcp-abe798e1"}