# Kalshi Prediction Markets Scraper (`neuro-scraper/kalshi-prediction-markets-scraper`) Actor

Kalshi Prediction Markets Scraper SD - Kalshi Prediction Markets Scraper is a market data tool that extracts Kalshi event contracts by keyword, category, series, event, ticker or weather city: yes/no bid and ask, implied probability, volume, open interest, rules, order book and trades.

- **URL**: https://apify.com/neuro-scraper/kalshi-prediction-markets-scraper.md
- **Developed by:** [Neuro Scraper](https://apify.com/neuro-scraper) (community)
- **Categories:** Developer tools, News, Automation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $2.49 / 1,000 results

This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

./README.md

# Actor input Schema

## `searchQueries` (type: `array`):

Kalshi's own site search, one keyword per line, e.g. bitcoin, fed rate, super bowl. Every event the search lists is read with all its markets.

## `categories` (type: `array`):

Kalshi categories, read from Kalshi's own category list on every run: Politics, Elections, Economics, Financials, Crypto, Climate and Weather, Sports, Entertainment, Companies, Science and Technology, Health, World, Commodities, Mentions ... Events come in Kalshi's volume order (most traded first).

## `seriesTickers` (type: `array`):

Kalshi series tickers, e.g. KXHIGHNY (NYC daily high temperature), KXBTCD (Bitcoin daily price), KXFED. Every event of the series in the chosen status is read with the platform's cursor.

## `eventTickers` (type: `array`):

Exact events, e.g. KXHIGHNY-26OCT09 or KXNEWPOPE-70.

## `marketTickers` (type: `array`):

Exact markets, e.g. KXHIGHNY-26OCT09-B73.5.

## `startUrls` (type: `array`):

Kalshi market pages: https://kalshi.com/markets/kxhighny (a series) or https://kalshi.com/markets/kxhighny/highest-temperature-in-nyc/kxhighny-26oct09 (one event).

## `cities` (type: `array`):

US cities for Kalshi's weather markets, e.g. NYC, Chicago, Miami, Austin, Denver, Los Angeles, Philadelphia, Houston. The weather series that name the city are read from Kalshi's series list on every run.

## `metrics` (type: `array`):

Which weather series to read for each city: daily high temperature, daily low temperature, rain, snow.

## `mode` (type: `string`):

markets = one row per market (bracket); events = one row per event with every market nested, the favourite, overround and fair (overround-free) probabilities.

## `status` (type: `string`):

open = trading now; unopened = listed, not trading yet; closed = trading ended, result not final; settled = final result; any = every status. Settled history works best with a series, city, event or ticker.

## `dateFrom` (type: `string`):

YYYY-MM-DD. Only events dated on or after this day (the date in the event ticker, e.g. KXHIGHNY-26OCT07 = 2026-10-07; otherwise the close date).

## `dateTo` (type: `string`):

YYYY-MM-DD. Only events dated on or before this day.

## `lookbackDays` (type: `integer`):

Only markets that closed in the last N days (Kalshi's min_close_ts filter). 0 = no limit.

## `closesWithinHours` (type: `integer`):

Only markets that close within N hours from now (Kalshi's max_close_ts filter). 0 = no limit.

## `minVolume` (type: `integer`):

Only markets with at least this lifetime volume (filtered after reading).

## `minVolume24h` (type: `integer`):

Only markets with at least this 24-hour volume (filtered after reading).

## `minOpenInterest` (type: `integer`):

Only markets with at least this open interest (filtered after reading).

## `minYesPrice` (type: `integer`):

Only markets whose implied probability (yes mid price, else last price) is at least this percent, e.g. 10.

## `maxYesPrice` (type: `integer`):

Only markets whose implied probability is at most this percent, e.g. 90.

## `minLiquidity` (type: `integer`):

Only markets with at least this many dollars resting in the order book levels read (price x size, both sides). Reads the order book of every market.

## `onlyPriced` (type: `boolean`):

Skip markets that have never traded and have no yes bid.

## `requireLiveQuote` (type: `boolean`):

Keep only markets with both a yes bid and a yes ask right now.

## `includeOrderbook` (type: `boolean`):

Adds the order book (yes and no bids: price + size) and its dollar liquidity per market. One extra request per market (markets shape).

## `orderbookDepth` (type: `integer`):

Price levels per side.

## `includeTrades` (type: `boolean`):

Adds the market's most recent trades (time, contracts, yes / no price, taker side), newest first, following Kalshi's trade cursor. Markets shape.

## `tradesPerMarket` (type: `integer`):

Most trades added per market with 'Include recent trades'.

## `includeRules` (type: `boolean`):

Adds the secondary rules text and the early-close condition (the primary rule is always in 'rules').

## `allMarkets` (type: `boolean`):

With no keyword, category, series, event, ticker or city: read Kalshi's full event list in the chosen status (use the date, close-time and volume filters to narrow it).

## `includeCombos` (type: `boolean`):

With 'All markets': Kalshi's raw market list is mostly multi-leg sports combos (100 of the first 100 open markets, measured); they are skipped unless this is on.

## `maxItems` (type: `integer`):

Most rows in the dataset (markets, or events in the events shape); each row is one result. Lists follow Kalshi's cursor until this number or the end.

## `proxyConfiguration` (type: `object`):

Kalshi's public API answered without a proxy in our tests; residential proxy (US) is the default.

## Actor input object example

```json
{
  "searchQueries": [
    "bitcoin"
  ],
  "metrics": [
    "high",
    "low"
  ],
  "mode": "markets",
  "status": "open",
  "lookbackDays": 0,
  "closesWithinHours": 0,
  "minVolume": 0,
  "minVolume24h": 0,
  "minOpenInterest": 0,
  "minYesPrice": 0,
  "maxYesPrice": 100,
  "minLiquidity": 0,
  "onlyPriced": false,
  "requireLiveQuote": false,
  "includeOrderbook": false,
  "orderbookDepth": 10,
  "includeTrades": false,
  "tradesPerMarket": 20,
  "includeRules": false,
  "allMarkets": false,
  "includeCombos": false,
  "maxItems": 50,
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": [
      "RESIDENTIAL"
    ],
    "apifyProxyCountry": "US"
  }
}
```

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "searchQueries": [
        "bitcoin"
    ],
    "proxyConfiguration": {
        "useApifyProxy": true,
        "apifyProxyGroups": [
            "RESIDENTIAL"
        ],
        "apifyProxyCountry": "US"
    }
};

// Run the Actor and wait for it to finish
const run = await client.actor("neuro-scraper/kalshi-prediction-markets-scraper").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "searchQueries": ["bitcoin"],
    "proxyConfiguration": {
        "useApifyProxy": True,
        "apifyProxyGroups": ["RESIDENTIAL"],
        "apifyProxyCountry": "US",
    },
}

# Run the Actor and wait for it to finish
run = client.actor("neuro-scraper/kalshi-prediction-markets-scraper").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "searchQueries": [
    "bitcoin"
  ],
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": [
      "RESIDENTIAL"
    ],
    "apifyProxyCountry": "US"
  }
}' |
apify call neuro-scraper/kalshi-prediction-markets-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,neuro-scraper/kalshi-prediction-markets-scraper"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/cgDk5X6Z2kMOkFi0Z/builds/3OC910okceQIDmCfT/openapi.json