Kalshi Weather Market Data Scraper

x402

Kalshi Weather Market Data Scraper is a paid API for AI agents from api.scrapeforagents.tech, paid per call via x402, $0.025/call, status unknown (last checked 2026-10-02).

Fetches structured Kalshi weather prediction market data (temperature highs/lows and rainfall contracts) for specified cities and date ranges, including optional order book and trade history.

Price / call$0.025

Seller volume →—

Success—

StatusUnknown

How this service works

Pay-per-call structured web data. Failed or empty runs are not charged.

Output

Returns a JSON object with a count and an items array. Each item represents a Kalshi weather market contract with fields including city, ticker, station_id, series_type, strike_type, event_ticker, bracket_label, and series_ticker. If requested, each item may also include up to 1,000 recent trades and/or order book bid levels for active markets.

Example use cases

Live weather market monitoring for traders

“Get all live Kalshi temperature markets for NYC, Chicago, and Miami right now — both daily high and daily low series — with the current order book included so I can see bid levels.”

Backtesting settled rain markets

“Pull settled Kalshi rain markets (KXRAIN) for NYC and Miami for the past 90 days, including trade history for each market, so I can analyze how they resolved.”

Multi-city weather contract research

“Fetch both live and settled Kalshi weather markets across all available cities for the date range from March 1 to March 31, covering all four series types — KXHIGH, KXLOW, KXRAIN, and KXRAINM — and give me up to 500 records.”

Technical details

Endpoint

POSThttps://api.scrapeforagents.tech/v1/kalshi?utm_source=zero.xyz

When to prefer

Use this endpoint when you need structured Kalshi weather prediction market data — temperature (daily high/low) or rainfall contracts — for specific cities and date ranges, with optional trade history and order book depth. Prefer this over direct Kalshi API calls when you need pay-per-use access without managing API credentials, or when you need both live and archived settled markets in one call. Best for weather market research, trading strategy backtesting, and real-time market monitoring across multiple cities.

Side effects

Invalid city code returns empty items array or error
Date format not matching YYYY-MM-DD or YYYYMMDD causes parsing failure
Unsupported seriesType enum value rejected
lookbackDays exceeding 365 rejected with validation error
includeTrades or includeOrderbook causing timeout for large market sets
Empty result set when no markets exist for the given parameters — not charged
Kalshi upstream API unavailability causing failed run — not charged

Input

Schema · Request body

Field	Type	Description
mode	string	Live contracts, finalized contracts with results, or both. Settled mode includes archived markets within the date window.
cities	array	City names or codes such as NYC, Chicago, Miami, or all. Temperature markets cover 24 cities; daily rain also covers several more.
dateTo	string	Optional last market date, inclusive. Use YYYY-MM-DD, YYYYMMDD, today, tomorrow or yesterday.
dateFrom	string	Optional first market date, inclusive. Use YYYY-MM-DD, YYYYMMDD, today, tomorrow or yesterday.
maxItems	integer	Stop after this many market records. Zero means no item cap; the run charge limit still applies.
seriesType	string	Choose daily high, daily low, daily rain, monthly rain, both temperature series, both rain series, or all four families.
lookbackDays	integer	How many market dates to include in settled mode when dateFrom is empty. The archive is included when needed.
includeTrades	boolean	Add up to 1,000 recent trades per market. Adds one request per market and can take longer.
includeOrderbook	boolean	Add bid levels for active markets. Adds one request per active market; settled markets have empty books.

Output

Schema · Response

{
  "type": "json",
  "example": {
    "count": 1,
    "items": [
      {
        "city": null,
        "ticker": null,
        "station_id": null,
        "series_type": null,
        "strike_type": null,
        "event_ticker": null,
        "bracket_label": null,
        "series_ticker": null
      }
    ],
    "product": "kalshi"
  }
}

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