# Game Deals Scraper - Prices Across 30+ Stores (`logiover/cheapshark-game-deals-scraper`) Actor

Scrape live PC game deals across more than thirty stores in bulk. Extract title, sale price, normal price, savings percentage, store, Steam rating, Metacritic score and deal link to CSV/JSON. No API key.

- **URL**: https://apify.com/logiover/cheapshark-game-deals-scraper.md
- **Developed by:** [Logiover](https://apify.com/logiover) (community)
- **Categories:** E-commerce
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $3.50 / 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.
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?

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

## Game Deals Scraper - Prices Across 30+ Stores

![Apify Actor](https://img.shields.io/badge/Apify-Actor-00A67E?logo=apify\&logoColor=white) ![No API key](https://img.shields.io/badge/No%20API%20key-required-2ea44f) ![Pay per result](https://img.shields.io/badge/Pricing-Pay%20per%20result-1C7ED6) ![Export](https://img.shields.io/badge/Export-JSON%20%7C%20CSV%20%7C%20Excel-F59E0B)

**Scrape live PC game deals across more than thirty stores in bulk. Extract title, sale price, normal price, savings percentage, store, Steam rating, Metacritic score and deal link to CSV/JSON. No API key.**

***

### What does the CheapShark Scraper do?

This Actor turns any CheapShark search into a structured dataset. You give it every store or filtered by store and rating, it walks the result pages one after another, and it writes one clean row per deal into your dataset — ready to export as JSON, CSV or Excel, or to pull straight from the Apify API.

CheapShark aggregates live pricing from more than thirty PC game stores behind one keyless REST API, and the Actor reads it directly. Every row already carries both the sale and the normal price, so the saving is a fact from the source rather than a calculation. Pagination is followed automatically until it runs out of results, hits your page limit or hits your **Max items** cap, whichever comes first. Every row is de-duplicated across the whole run, so you are never billed twice for the same deal.

There is **no API key, no login and no browser** involved. That keeps runs fast and cheap, and it means you can schedule the Actor without worrying about credentials expiring.

### Who is it for?

- **Price-comparison products** that need a cross-store game pricing feed.
- **Deal and coupon sites** sourcing live discounts automatically.
- **Game publishers** watching where their titles are discounted and by whom.
- **Analysts** studying how discounting differs between storefronts.
- **Affiliate marketers** building deal feeds without manual curation.

### Use cases

- Export every live deal and rank by savings percentage.
- Track one store's discounting behaviour over time.
- Find titles below a price threshold with a strong Steam rating.
- Compare the same game's price across competing storefronts.
- Build a historical deal dataset by scheduling repeated runs.

### Why use this CheapShark Scraper?

- 🔑 **Keyless** — no account, no API token, no cookies to paste.
- 📦 **18 fields per deal** — everything the result page exposes, already typed.
- 📄 **Real pagination** — it walks page after page instead of returning the first screen.
- 🎯 **Precise caps** — **Max items** stops the run exactly where you want it, so the bill is predictable.
- 📊 **Export anywhere** — JSON, CSV, Excel or HTML, plus the Apify API and integrations.
- 💸 **Pay per result** — you pay for rows you actually receive, with no platform fees to calculate.

### What data can you extract?

Every run produces one row per deal, with these fields:

| Field | Type | Description |
|-------|------|-------------|
| `dealId` | string | CheapShark deal ID |
| `title` | string | Game title |
| `dealUrl` | string | Link that redirects to the store offer |
| `storeId` | string | Store identifier |
| `salePrice` | number | Current sale price |
| `normalPrice` | number | Normal price before the discount |
| `savingsPercent` | number | Percentage saved against the normal price |
| `isOnSale` | boolean | Whether the listing is currently discounted |
| `steamAppId` | string | Matching Steam application ID when known |
| `steamRatingPercent` | number | Percentage of positive Steam reviews |
| `steamRatingCount` | number | Number of Steam reviews |
| `steamRatingText` | string | Steam review summary, e.g. Very Positive |
| `metacriticScore` | number | Metacritic score when available |
| `dealRating` | number | CheapShark's own 0-10 rating of the deal |
| `releaseDate` | string | Release date of the title |
| `thumbnailUrl` | string | Thumbnail image URL |
| `page` | number | Result page the deal appeared on |
| `scrapedAt` | string | ISO timestamp of extraction |

#### Output example

```json
{
  "dealId": "ognJ9LfwN74A5N2nMqzcLqKjKobCdudf7BmpU2ON0qw%3D",
  "dealRating": 10,
  "dealUrl": "https://www.cheapshark.com/redirect?dealID=ognJ9LfwN74A5N2nMqzcLqKjKobCdudf7BmpU2ON0qw%253D",
  "isOnSale": true,
  "metacriticScore": 86,
  "normalPrice": 24.99,
  "page": 1,
  "releaseDate": "2023-11-14",
  "salePrice": 0,
  "savingsPercent": 100,
  "scrapedAt": "2026-09-14T07:51:50.311Z",
  "steamAppId": "1280930",
  "steamRatingCount": 1811,
  "steamRatingPercent": 95,
  "steamRatingText": "Overwhelmingly Positive",
  "storeId": "25",
  "thumbnailUrl": "https://shared.fastly.steamstatic.com/store_item_assets/steam/apps/1280930/8326b5c061ca3c8eb24ee9a45d4b5a93f379067c/capsule_231x87.jpg?t=1788164581",
  "title": "Astral Ascent"
}
```

### How to use

#### Option A — every store

```json
{
  "maxItems": 900,
  "maxPagesPerSearch": 15
}
```

1. Open the Actor and fill in the every store field.
2. Set **Max pages per search** and **Max items** to bound the run.
3. Click **Start**, then export from the **Output** tab.

#### Option B — filtered by store and rating

```json
{
  "maxItems": 500,
  "maxPagesPerSearch": 10,
  "maxPrice": 20,
  "minSteamRating": 80,
  "storeId": "1"
}
```

Paste one or more CheapShark URLs into **Start URLs** and the Actor paginates each of them independently.

### Input parameters

| Parameter | Type | Default | Description |
|-----------|------|---------|-------------|
| `storeId` | string | \`\` | CheapShark store ID to restrict the run to, e. |
| `minSteamRating` | integer | `0` | Drop deals whose Steam positive-review percentage is below this. |
| `maxPrice` | integer | `0` | Only return deals at or below this price. |
| `maxPagesPerSearch` | integer | `4` | How many result pages to walk for each search. |
| `maxItems` | integer | `200` | Stop after this many deals. |
| `maxConcurrency` | integer | `2` | Parallel requests. |
| `proxyConfiguration` | object | `{"useApifyProxy": true}` | Proxy used to fetch pages. |

### Tips for best results

- Leave the store filter empty to sweep every store CheapShark tracks.
- 60 deals come back per page, so a 20-page run yields roughly 1,200 rows.
- `dealRating` blends price and quality — sort by it to surface genuinely good offers.
- `savingsPercent` is supplied by the source, so it is consistent across stores.
- Use the minimum-Steam-rating filter to drop shovelware from a deal feed.
- Deals change constantly; schedule hourly or daily runs to build a price history.
- `steamAppId` lets you join these rows to the Steam store scraper's output.
- A null `metacriticScore` simply means the title was never scored there.
- Keep **Max concurrency** low — the API is free and politeness keeps it that way.
- Pair with the Steam and GOG scrapers to see list price against street price.

### Integrations

Send results straight into the tools you already use: **Google Sheets**, **Slack**, **Zapier**, **Make**, **Airtable** or any **Webhook**. You can also **schedule** the Actor to run hourly, daily or weekly and have each run append to the same dataset, which is how you build a price or availability history rather than a one-off snapshot.

### API usage

Run the Actor and collect results from any language. Replace `<YOUR_TOKEN>` with your Apify API token.

**cURL**

```bash
curl -X POST "https://api.apify.com/v2/acts/logiover~cheapshark-game-deals-scraper/run-sync-get-dataset-items?token=<YOUR_TOKEN>" \
  -H "Content-Type: application/json" \
  -d '{"maxItems": 900, "maxPagesPerSearch": 15}'
```

**Node.js**

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

const client = new ApifyClient({ token: '<YOUR_TOKEN>' });
const run = await client.actor('logiover/cheapshark-game-deals-scraper').call({"maxItems": 900, "maxPagesPerSearch": 15});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);
```

**Python**

```python
from apify_client import ApifyClient

client = ApifyClient('<YOUR_TOKEN>')
run = client.actor('logiover/cheapshark-game-deals-scraper').call(run_input={"maxItems": 900, "maxPagesPerSearch": 15})
for item in client.dataset(run['defaultDatasetId']).iterate_items():
    print(item)
```

### Use with AI agents (MCP)

This Actor is available through the Apify MCP server, so an AI agent can call it as a tool. Point your agent at `https://mcp.apify.com` and it can run the CheapShark Scraper on demand — for example: *"Pull the first 500 deals from CheapShark and summarise the price distribution."* The agent receives the same structured rows you would get from the UI.

### FAQ

#### Do I need a CheapShark account or API key?

No. The Actor reads publicly available pages only. There is nothing to authenticate and no credentials to rotate.

#### How many deals can I get in one run?

As many as the search exposes. Raise **Max pages per search** and **Max items** together; the run stops at whichever limit it reaches first.

#### Why did I get fewer rows than I asked for?

The search ran out of deals. That is normal for narrow queries — broaden the search or add more searches to one run.

#### Are results de-duplicated?

Yes. Each deal is emitted once per run, even when it appears on several pages, so you are never billed twice for the same record.

#### Why are some fields empty?

CheapShark does not publish every attribute for every deal. Empty means the source did not show it, not that extraction failed.

#### What export formats are supported?

JSON, CSV, Excel, HTML and RSS from the **Output** tab, plus the Apify API and any integration you connect.

#### How fast is it?

It is pure HTTP with no browser, so a page of results typically takes a second or two. Raise **Max concurrency** carefully — the source rate-limits aggressive crawling.

#### Can I schedule it?

Yes. Use the Apify scheduler to run it on any interval and append each run to the same dataset for time-series analysis.

#### Does it work behind a proxy?

It uses Apify Proxy automatically. You can switch groups or supply your own proxies in **Proxy configuration**.

#### How often does the data change?

CheapShark updates continuously. Re-run whenever you need current data; the Actor always reads the live pages, never a cache.

#### Is the output schema stable?

Yes. Field names and types are fixed, so downstream pipelines will not break between runs.

#### What if the site changes its layout?

Open an issue on the **Issues** tab and it gets fixed. The Actor is actively maintained.

### Is it legal?

This Actor reads only publicly available pages on CheapShark — the same content any visitor sees without logging in. It does not bypass authentication, does not collect private data and does not attempt to defeat access controls. You are responsible for how you use the output: respect the source's terms of service, applicable copyright, and data-protection law such as GDPR where personal data is involved. Scraping public data is generally lawful in the EU and the US, but the responsibility for the downstream use of that data sits with you.

### Related scrapers

- [Steam Store Scraper](https://apify.com/logiover/steam-store-scraper) — List prices straight from Steam
- [GOG Scraper](https://apify.com/logiover/gog-catalog-scraper) — DRM-free pricing
- [Idealo Scraper](https://apify.com/logiover/idealo-de-price-comparison-scraper) — General price comparison
- [Amazon Product Scraper](https://apify.com/logiover/amazon-product-scraper) — Retail pricing

# Actor input Schema

## `storeId` (type: `string`):

CheapShark store ID to restrict the run to, e.g. 1 for Steam. Leave empty for every store.

## `minSteamRating` (type: `integer`):

Drop deals whose Steam positive-review percentage is below this. 0 keeps everything.

## `maxPrice` (type: `integer`):

Only return deals at or below this price. 0 means no limit.

## `maxPagesPerSearch` (type: `integer`):

How many result pages to walk for each search. Set 0 for no limit.

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

Stop after this many deals. Set 0 for no limit.

## `maxConcurrency` (type: `integer`):

Parallel requests. Lower this if the site rate-limits you.

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

Proxy used to fetch pages. Defaults to Apify Proxy (automatic). You usually do not need to change this.

## Actor input object example

```json
{
  "storeId": "",
  "minSteamRating": 0,
  "maxPrice": 0,
  "maxPagesPerSearch": 4,
  "maxItems": 200,
  "maxConcurrency": 2,
  "proxyConfiguration": {
    "useApifyProxy": true
  }
}
```

# Actor output Schema

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

All deals extracted in this run.

# 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 = {
    "minSteamRating": 0,
    "maxPrice": 0,
    "maxPagesPerSearch": 4,
    "maxItems": 200,
    "maxConcurrency": 2
};

// Run the Actor and wait for it to finish
const run = await client.actor("logiover/cheapshark-game-deals-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 = {
    "minSteamRating": 0,
    "maxPrice": 0,
    "maxPagesPerSearch": 4,
    "maxItems": 200,
    "maxConcurrency": 2,
}

# Run the Actor and wait for it to finish
run = client.actor("logiover/cheapshark-game-deals-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 '{
  "minSteamRating": 0,
  "maxPrice": 0,
  "maxPagesPerSearch": 4,
  "maxItems": 200,
  "maxConcurrency": 2
}' |
apify call logiover/cheapshark-game-deals-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,logiover/cheapshark-game-deals-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/RZvvU73TKmyNK7wAu/builds/ZKjC5bnm9wHeWscCH/openapi.json