Weather Forecast for Prediction Market Stations is a paid API for AI agents from weather-x402.linholiday.workers.dev, paid per call via x402, $0.02/call, status unknown (last checked 2026-10-22).
Returns multi-source consensus high/low temperature forecasts for ICAO weather stations used in Kalshi and Polymarket temperature markets
Paid calls cost 0.01-0.02 USDC on eip155:8453 via x402 (exact scheme). Free: /stations, /preview/*, /health, /, /openapi.json, /llms.txt, /.well-known/x402.
Returns a JSON object with consensus high and low temperatures (in both Celsius and Fahrenheit), spread between sources, number of sources, individual source forecasts (e.g. nws_forecast, met_norway), the station name and ICAO ID, the date, and the precise UTC settlement day window with start/end timestamps and UTC offset.
GEThttps://weather-x402.linholiday.workers.dev/forecast?utm_source=zero.xyzUse this endpoint when you need temperature forecasts specifically aligned to Kalshi or Polymarket settlement windows for trading or researching prediction market temperature contracts. It aggregates multiple meteorological sources (NWS, MET Norway) into a single consensus with spread, which is more reliable than any single source. Prefer this over general weather APIs when you need settlement-day-exact windows and market-specific ICAO stations.
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
{
"type": "json",
"example": {
"low": {
"spread": {
"c": 0.9,
"f": 1.6
},
"consensus": {
"c": 8.5,
"f": 47.2
},
"n_sources": 2,
"consensus_f_whole": 47
},
"date": "2026-10-22",
"high": {
"spread": {
"c": 0.7,
"f": 1.3
},
"consensus": {
"c": 18,
"f": 64.3
},
"n_sources": 2,
"consensus_f_whole": 64
},
"name": "New York/Central Park",
"sources": [
{
"low": {
"c": 8.9,
"f": 48
},
"high": {
"c": 18.3,
"f": 65
},
"source": "nws_forecast"
},
{
"low": {
"c": 8,
"f": 46.4
},
"high": {
"c": 17.6,
"f": 63.7
},
"source": "met_norway"
}
],
"station": "KNYC",
"day_window": {
"end": "2026-10-23T05:00:00.000Z",
"date": "2026-10-22",
"basis": "local_standard_time_day",
"start": "2026-10-22T05:00:00.000Z",
"utc_offset": "-05:00"
}
}
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