fraud_detector
Détecteur de fraude — Gapup agent-payable C-suite expertise (RISK). Returns a structured, audited deliverable. Reference case: TechManu SAS — Industriel FR €32M CA, 148 FTE · 30j · 21 anomalies · €487k à risque. Inputs are validated server-side — send the documented case fields.
This record as markdown: /tools/io-github-getgapup-gapup-mcp/fraud-detector.md
What fraud_detector does on Gapup Mcp
AI agents use fraud_detector to commit financial operations through Gapup Mcp, usually the final step of a payment, billing, or trading workflow. A call moves real money.
| Parameter | Type | Required | Description |
|---|---|---|---|
async | boolean | — | If true, returns a job_id immediately (<200ms) instead of waiting for the result. Poll the result with job_result(job_id). Use for slow tools to avoid client ti |
focus | string | — | |
company | object | Yes | |
analysisPeriodDays | integer | Yes | |
transactionVolumes | object | Yes |
Parameters from the server's own tool schema.
Why fraud_detector is rated Critical
This tool is agent-payable on a per-call basis (x402), meaning each invocation incurs a financial transaction. Beyond the payment obligation, it analyzes financial fraud risk (€487k at risk referenced), operates in the financial compliance domain, and misuse could expose sensitive financial/KYC data or trigger erroneous fraud flags with real-world financial consequences.
From the tool's definition Détecteur de fraude — Gapup agent-payable C-suite expertise (RISK). Returns a structured, audited deliverable. 21 anomalies · €487k à risque. x402 per-call.
Risk signalsHigh parameter count (14 properties)
Attacks that exploit this kind of access
The rule that runs fraud_detector safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Gapup Mcp, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For fraud_detector, this is the rule to start with:
Any call to fraud_detector is blocked until a human approves it. The rest of the server keeps working.
The button opens the PolicyLayer dashboard: create your workspace, connect Gapup Mcp, apply this rule, and every fraud_detector call is checked against it from then on.
Questions about fraud_detector
Détecteur de fraude — Gapup agent-payable C-suite expertise (RISK). Returns a structured, audited deliverable. Reference case: TechManu SAS — Industriel FR €32M CA, 148 FTE · 30j · 21 anomalies · €487k à risque. Inputs are validated server-side — send the documented case fields. It is categorised as a Financial tool in the Gapup Mcp MCP Server, which means it involves financial transactions. Block by default and require explicit approval.
fraud_detector accepts 5 parameters: async, focus, company, analysisPeriodDays, transactionVolumes. Required: company, analysisPeriodDays, transactionVolumes. The full parameter table on this page comes from the server's own tool schema.
Register the Gapup MCP server in PolicyLayer and add a rule for fraud_detector: 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 Gapup Mcp. Nothing to install.
fraud_detector is a Financial tool with critical risk. Critical-risk tools should be blocked by default and only enabled with explicit human approval.
Yes. Add a rate_limit block to the fraud_detector 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.
Set action: deny in the PolicyLayer policy for fraud_detector. 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.
fraud_detector is provided by the Gapup MCP server (https://mcp.gapup.io/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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