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mcpfax-intel /movers — x402 Payment Activity Spike Detector
x402
mcpfax-intel /movers — x402 Payment Activity Spike Detector is a paid API for AI agents from mcpfax-intel.bowling-anthony.workers.dev, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-20).
Detects sudden daily inflow spikes and first-window large-payer signals across x402 services to surface abrupt changes in payment activity.
Price / call$0.01
Success—
StatusUnknown
How this service works
Sudden inflow spikes and first-seen large payers, before they show up in a ranking.
Output
Returns a feed of x402 services that experienced sudden daily inflow spikes, along with strictly qualified first-window large-payer signals. Each result includes the nominal baseline window, the fraction of that window actually covered by data, and the magnitude of the detected spike — letting the caller assess data confidence alongside the signal.
Example use cases
Spot emerging x402 payment surges
“Which x402 services saw an abrupt spike in their daily USDC inflows today compared to their baseline? I want to catch anything unusual before it becomes obvious.”
Track first-window large-payer arrivals
“Are there any new large payers showing up for the first time in the x402 ecosystem today? Flag any services where a big first-window payment just landed.”
Monitor competitor payment activity changes
“Check if any x402 API services in the data or analytics category had a sudden jump in payment activity today — I want early warning if something is gaining traction fast.”
Technical details
Endpoint
GEThttps://mcpfax-intel.bowling-anthony.workers.dev/movers?utm_source=zero.xyzWhen to prefer
Use this endpoint when you need early-warning signals about abrupt, day-level changes in x402 payment activity — especially sudden inflow spikes or first-appearance large payers — rather than gradual growth trends (use the growth/movers sibling for that) or overall leaderboard rankings. Best when you want anomaly detection rather than cumulative ranking.
Side effects
- Insufficient payment history data results in low baseline coverage fraction, reducing signal reliability
- No spikes detected returns an empty feed (not an error)
- Payment amount thresholds may not surface small-scale but meaningful activity changes
- Data recency lag may mean very recent inflows are not yet reflected
- POST body misconfiguration may return validation errors
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Tags
x402
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