# Scratch-Off Top Prize Alerts: Prizes Left & Claimed (`jackpotledger/scratch-off-top-prizes-alert`) Actor

Alerts on scratch-off top prizes across states: games with all top prizes left, only one top prize left, all gone, or a top prize claimed since your last run. TX, NY, CO, NM, IN, CA and PA. Export to JSON, CSV or Excel.

- **URL**: https://apify.com/jackpotledger/scratch-off-top-prizes-alert.md
- **Developed by:** [JackpotLedger](https://apify.com/jackpotledger) (community)
- **Categories:** Business, Automation, Other
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $15.00 / 1,000 results

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/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

## Scratch-Off Top Prize Alerts: Prizes Left and Claimed

Know which scratch-off games still have every top prize, which are down to their last one, which have none left and which had a top prize claimed since your last check. Covers several state lotteries in one schema.

### What you get

One record per game that matches an alert, with the alert types, top prize, top prizes printed and remaining, the remaining count from your previous run and the full prize table.

### Who is it for

- Lottery apps and newsletters that notify players
- Media covering big lottery wins
- Retailers planning which games to promote

### How to use it

Choose the alert types and states, optionally a minimum top prize, and schedule the actor. Claimed since last run compares with the previous run stored under the memory name.

### Coverage and freshness

Texas, New York, Colorado, New Mexico, Indiana, California, Pennsylvania, Florida, Georgia, Virginia and Washington today, with more states added over time. Each state publishes different details; expected value is only computed where the full prize table with remaining counts is published (Texas, California, New Mexico and part of Indiana).

### Pricing

You pay per alert returned. If nothing matches your filters you get one explanation row and you are not charged. Free Apify plans get up to 10 alerts per run.

### Responsible play

This actor reports official lottery and gaming data. It does not predict results and nothing here can guarantee a win. Play responsibly; in the US, help is available at 1-800-GAMBLER.

# Actor input Schema

## `states` (type: `array`):

States to include. Leave empty for all supported states (Texas, New York, Colorado, New Mexico, Indiana, California, Pennsylvania, Florida, Georgia, Virginia, Washington).

## `alertTypes` (type: `array`):

Which situations to return. Leave empty for all.

## `minTopPrize` (type: `integer`):

Only games whose top prize is at least this amount.

## `sortBy` (type: `string`):

Order of the returned games.

## `minTicketPrice` (type: `integer`):

Only games at or above this price.

## `maxTicketPrice` (type: `integer`):

Only games at or below this price.

## `maxGames` (type: `integer`):

Maximum number of games to return.

## `memoryName` (type: `string`):

Name of the storage that remembers games between runs. Use a different name per alert.

## Actor input object example

```json
{
  "sortBy": "expected_return",
  "maxGames": 100,
  "memoryName": ""
}
```

# Actor output Schema

## `results` (type: `string`):

No description

# 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 = {};

// Run the Actor and wait for it to finish
const run = await client.actor("jackpotledger/scratch-off-top-prizes-alert").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 = {}

# Run the Actor and wait for it to finish
run = client.actor("jackpotledger/scratch-off-top-prizes-alert").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 '{}' |
apify call jackpotledger/scratch-off-top-prizes-alert --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,jackpotledger/scratch-off-top-prizes-alert"
        }
    }
}
```

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/rZ3xU6IsOi0Ql2CtI/builds/Hc5denJRj5IBAkl9H/openapi.json