# Kalshi Prediction Market Scraper: Live Event Odds (`scrapemint/kalshi-prediction-market-scraper`) Actor

Live odds from Kalshi, the regulated US event contract exchange: sports, elections, economics, weather, and culture markets with yes/no prices, implied probability, volume, and open interest. Filter by category, keyword, or ticker. Keyless, no browser. Pay per market row.

- **URL**: https://apify.com/scrapemint/kalshi-prediction-market-scraper.md
- **Developed by:** [Ken M](https://apify.com/scrapemint) (community)
- **Categories:** Business, News
- **Stats:** 7 total users, 6 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$4.00 / 1,000 kalshi market rows

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

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

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
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.
Actors are written with capital "A".

## 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.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## Kalshi Prediction Market Scraper: Live Event Odds

Live market data from Kalshi, the CFTC-regulated US event contract exchange. Every market is a real-money yes/no question - who wins the game, where the Fed sets rates, how hot the summer gets - and the price is the crowd's probability. This actor reads those markets through Kalshi's public API and gives you clean rows.

### What you get

One row per market:

| Field | Description |
| --- | --- |
| `eventTitle`, `outcome` | The question and the specific outcome this market prices |
| `yesBid`, `yesAsk`, `noBid`, `noAsk` | Live order book, in dollars (0 to 1) |
| `lastPrice` | Last trade price |
| `impliedProbabilityPct` | Book midpoint (or last trade) as a percentage |
| `volume`, `volume24h`, `openInterest` | Activity and positioning |
| `openTime`, `closeTime`, `status`, `result` | Lifecycle |
| `rules` | Exact resolution criteria |
| `ticker`, `eventTicker`, `seriesTicker`, `category` | Identifiers for joins |

### Three ways to query

1. **Discovery** - pick `categories` (Politics, Economics, Sports, Financials, Climate and Weather, Culture, Crypto...) and optional `keywords`; the actor browses open events and returns matching markets.
2. **Event tickers** - exact events like `KXNEWPOPE-70`.
3. **Series tickers** - everything in a recurring series, like Fed decisions or monthly CPI.

### Typical uses

- **Traders and arb hunters**: compare Kalshi prices against Polymarket and sportsbook lines. Pairs with our Polymarket Prediction Market Scraper for a two-exchange view.
- **Researchers and journalists**: probability time series on elections, rates, and geopolitics - schedule the actor and build your own history.
- **Dashboards and newsletters**: structured event odds without touching an exchange account.
- **Sports analytics**: event contract prices on games as a sharp, regulated reference line.

### Pricing

You pay per market row (`market_row`). The first 2 rows of every run are free. Unknown tickers and searches with no matches cost nothing.

### Input example

```json
{
    "categories": ["Economics"],
    "keywords": ["Fed", "CPI", "inflation"],
    "onlyPriced": true,
    "minVolume": 100,
    "maxRows": 100
}
```

### Notes

- Data comes from Kalshi's public market-data API. No account, no API key, no browser. This actor reads prices; it does not trade.
- Prices are dollars per contract that pays $1, so 0.63 means a 63% implied probability.
- `onlyPriced` (default on) skips empty order books and long-dated combo markets that have never traded.
- Kalshi rate limits are handled: the actor paces requests, retries once, and stops cleanly with partial data if limits persist.

# Actor input Schema

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

Kalshi categories to browse, e.g. Politics, Economics, Sports, Financials, Climate and Weather, Science and Technology, Culture, World, Health, Companies, Crypto. Matched loosely.

## `keywords` (type: `array`):

Only markets whose event title or outcome mentions one of these, e.g. Fed, inflation, Chiefs, Bitcoin.

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

Exact Kalshi event tickers to fetch, e.g. KXNEWPOPE-70. Overrides categories and series.

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

Kalshi series tickers to fetch all markets from, e.g. KXFED, KXCPI.

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

Open markets trade now; closed and settled are history.

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

Skip markets that have no bids and no trades yet (empty books, long-dated combos).

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

Skip markets with lifetime volume below this.

## `maxRows` (type: `integer`):

Cap on market rows returned. Controls total cost.

## Actor input object example

```json
{
  "categories": [
    "Economics",
    "Politics"
  ],
  "keywords": [],
  "eventTickers": [],
  "seriesTickers": [],
  "status": "open",
  "onlyPriced": true,
  "minVolume": 0,
  "maxRows": 100
}
```

# 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 = {
    "categories": [
        "Economics",
        "Politics"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("scrapemint/kalshi-prediction-market-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 = { "categories": [
        "Economics",
        "Politics",
    ] }

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

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

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

```

## CLI example

```bash
echo '{
  "categories": [
    "Economics",
    "Politics"
  ]
}' |
apify call scrapemint/kalshi-prediction-market-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=scrapemint/kalshi-prediction-market-scraper",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/9EYqcLYSk9VRsLnz0/builds/EJkXX1Ypp4tbomOhB/openapi.json