# Steam Games Scraper - Low-cost๐ฒ๐ฅ๐ฎ๐ค (`delectable_incubator/steam-games-scraper-low-cost`) Actor
๐ฎ๐ Extract Steam game listings by keyword with ease. Collect game titles, release dates, prices, ratings, supported platforms, genres, developers, publishers, Steam URLs, and game metadata. Ideal for gaming market research, competitor analysis, trend monitoring, and game database creation. ๐๐
- **URL**: https://apify.com/delectable\_incubator/steam-games-scraper-low-cost.md
- **Developed by:** [Prime Scrape](https://apify.com/delectable_incubator) (community)
- **Categories:** Lead generation, E-commerce, Automation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet
## Pricing
from $0.00005 / actor start
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/platform/actors/running/actors-in-store#pay-per-event
## What's an Apify Actor?
Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases.
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.
In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md):
```bash
npm install apify-client
```
In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md):
```bash
pip install apify-client
```
In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md):
````bash
# MacOS / Linux
curl -fsSL https://apify.com/install-cli.sh | bash
# Windows
irm https://apify.com/install-cli.ps1 | iex
```bash
In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md).
If your project is in a different language, use 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
---
## ๐ฎ๐ฅ Steam Game Search Scraper | Bulk Steam Games Scraper | Apify Actor
### ๐ Extract Steam Game Data in Seconds (No Code)
The **Steam Game Search Scraper** is a powerful, scalable and SEO-optimized Apify Actor built to scrape **Steam game search results** in bulk.
Extract game listings, Steam App IDs, prices, discounts, review scores, release dates, supported platforms, images, and game URLs for market research, gaming analytics, AI datasets, competitor monitoring, and automation.
---
## ๐ฅ Why This Steam Scraper?
โ Best Steam game scraper on Apify
โ Bulk keyword scraping (multi-search)
โ Fast & scalable game extraction
โ 100% structured JSON / CSV / Excel output
โ Ideal for gaming market intelligence
โ Perfect for developers, publishers & data analysts
โ No coding required
---
## ๐ฏ What This Scraper Does
This Apify Actor extracts real-time game listings directly from **Steam Search**.
Simply provide one or multiple keywords and the scraper automatically collects matching games.
#### ๐ Core Features
โ
Scrape Steam game search results
โ
Bulk keyword scraping (SEO BOOST ๐)
โ
Multiple keyword support
โ
Extract prices & discounts
โ
Extract review scores
โ
Extract release dates
โ
Extract supported platforms
โ
Export clean structured datasets
โ
High-speed cloud extraction
---
## โก Input Configuration (Simple & Powerful)
### ๐ฅ BULK KEYWORD MODE (SEO BOOST ๐)
````
{
"keywords": \[
"strategy",
"racing",
"survival",
"open world",
"roguelike",
"anime",
"simulation",
"horror"
],
"max\_items": 100
}
```
---
## ๐ Extracted Game Data (Structured Output)
| Field | Description |
|------|-------------|
| title | Game title |
| link | Steam game URL |
| app_id | Steam App ID |
| platforms | Supported platforms |
| release_date | Official release date |
| review_score | Steam review score |
| price | Current price |
| original_price | Original price |
| discount | Discount percentage |
| image_url | Game thumbnail |
---
## ๐ก Use Cases (High Demand SEO Keywords)
Perfect for:
๐ฎ Steam game scraping
๐ Gaming market research
๐ฐ Price monitoring
๐ท๏ธ Discount tracking
โญ Review analysis
๐ Steam trend monitoring
๐ค AI training datasets
๐น๏ธ Game catalog aggregation
๐ข Competitor intelligence
โก Bulk game extraction
---
## ๐ Key Features (Apify SEO Optimized)
โก Bulk keyword scraping support
๐ Worldwide Steam marketplace coverage
๐ Smart search engine
๐ง Clean structured output
๐ High-speed extraction engine
๐ Auto retry & stability system
๐พ Export-ready datasets
โ๏ธ Scalable cloud execution
๐ Enterprise-ready architecture
---
## ๐ค Output Formats Supported
โ JSON
โ CSV
โ Excel XLSX
โ XML
โ HTML
---
## ๐ฆ Example Output
```
{
"title": "World of Tanks Blitz",
"link": "https://store.steampowered.com/app/444200/World\_of\_Tanks\_Blitz/",
"app\_id": "444200",
"platforms": "Windows, Mac",
"release\_date": "9 Nov, 2016",
"review\_score": "74%",
"price": "Free",
"original\_price": "Free",
"discount": "N/A",
"image\_url": "https://shared.fastly.steamstatic.com/store\_item\_assets/steam/apps/444200/capsule\_sm\_120.jpg"
}
````
---
## ๐ Preconfigured Dataset Views
#### ๐น Overview
Includes:
- Game Title
- Steam App ID
- Current Price
- Discount
- Review Score
- Release Date
- Platforms
- Steam URL
Perfect for quick game comparisons.
---
#### ๐น Detailed
Includes:
- Complete game metadata
- Steam App ID
- Pricing information
- Discount percentage
- Review score
- Supported platforms
- Release date
- Game image
Ideal for:
๐ Gaming market intelligence
๐ฎ Steam catalog analysis
๐ฐ Price tracking
๐ Game trend monitoring
---
#### ๐น By Keyword
Compare multiple Steam keyword searches.
Includes:
- Search Keyword
- Game Title
- Price
- Discount
- Review Score
- Release Date
- Steam URL
Perfect for comparing:
๐ฎ Genres
๐ท๏ธ Keywords
๐ฐ Pricing
โญ User ratings
---
## ๐ฅ Why This is the BEST Steam Scraper on Apify?
โ Optimized for Apify search ranking
โ Bulk keyword support (rare feature)
โ High-performance extraction engine
โ Enterprise-ready scalability
โ Clean structured datasets
โ Gaming market intelligence ready
โ Perfect for SEO traffic & marketplace visibility
---
## ๐ธ Pricing
This scraper uses a **pay-per-result** pricing model.
๐ณ **Price: $1.98 / 1,000 results**
You only pay for successfully extracted profiles.
---
## โ FAQ (SEO BOOST SECTION)
#### Can I scrape multiple keywords at once?
Yes โ Bulk Keyword Mode is fully supported.
#### Can I search any Steam game genre?
Yes.
#### Can I monitor Steam prices and discounts?
Yes.
#### Can I limit the number of extracted games?
Yes. Simply configure **max_items**.
#### Is coding required?
No โ this is a 100% no-code Apify Actor.
#### Can I export the data?
Yes โ JSON, CSV, Excel, XML and HTML are supported.
---
## โ ๏ธ Disclaimer
This tool is an independent data extraction solution and is **not affiliated with, endorsed by, or sponsored by Steam or Valve Corporation.**
---
## ๐ Related Actors
We are building the complete **PrimeScrape Gaming Intelligence Suite**.
๐ Coming Soon ๐
---
## ๐ PrimeScrape Ecosystem
Built for large-scale scraping, automation, AI datasets and market intelligence.
๐ฎ Gaming intelligence
๐ Market analytics
๐ฐ Price monitoring
๐ท๏ธ Discount tracking
๐ค AI training datasets
โ๏ธ Automation pipelines
๐ Game trend monitoring
---
## ๐ฌ Support
โญโญโญโญโญ Leave a review if you enjoy this actor.
๐ฉ Contact us for custom scraping solutions, enterprise features or private actors.
# Actor input Schema
## `keywords` (type: `array`):
List of keywords or subjects to search for on Steam.
Example: "war", "vr", "football", etc.
## `max_items_per_keyword` (type: `integer`):
The maximum number of items to retrieve from the search results, for each keyword.
## Actor input object example
```json
{
"keywords": [
"war"
],
"max_items_per_keyword": 80
}
````
# 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 '' with your token
const client = new ApifyClient({
token: '',
});
// Prepare Actor input
const input = {
"keywords": [
"war"
],
"max_items_per_keyword": 80
};
// Run the Actor and wait for it to finish
const run = await client.actor("delectable_incubator/steam-games-scraper-low-cost").call(input);
// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`๐พ 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);
});
// ๐ Want to learn more ๐? Go to โ 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 '' with your token.
client = ApifyClient("")
# Prepare the Actor input
run_input = {
"keywords": ["war"],
"max_items_per_keyword": 80,
}
# Run the Actor and wait for it to finish
run = client.actor("delectable_incubator/steam-games-scraper-low-cost").call(run_input=run_input)
# Fetch and print Actor results from the run's dataset (if there are any)
print("๐พ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
print(item)
# ๐ Want to learn more ๐? Go to โ https://docs.apify.com/api/client/python/docs/quick-start
```
## CLI example
```bash
echo '{
"keywords": [
"war"
],
"max_items_per_keyword": 80
}' |
apify call delectable_incubator/steam-games-scraper-low-cost --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=delectable_incubator/steam-games-scraper-low-cost",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "Steam Games Scraper - Low-cost๐ฒ๐ฅ๐ฎ๐ค",
"description": "๐ฎ๐ Extract Steam game listings by keyword with ease. Collect game titles, release dates, prices, ratings, supported platforms, genres, developers, publishers, Steam URLs, and game metadata. Ideal for gaming market research, competitor analysis, trend monitoring, and game database creation. ๐๐",
"version": "0.0",
"x-build-id": "uJLlCGnHUGNgbgByA"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/delectable_incubator~steam-games-scraper-low-cost/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-delectable_incubator-steam-games-scraper-low-cost",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/delectable_incubator~steam-games-scraper-low-cost/runs": {
"post": {
"operationId": "runs-sync-delectable_incubator-steam-games-scraper-low-cost",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/delectable_incubator~steam-games-scraper-low-cost/run-sync": {
"post": {
"operationId": "run-sync-delectable_incubator-steam-games-scraper-low-cost",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
}
},
"components": {
"schemas": {
"inputSchema": {
"type": "object",
"required": [
"keywords",
"max_items_per_keyword"
],
"properties": {
"keywords": {
"title": "Steam Keywords ๐",
"type": "array",
"description": "List of keywords or subjects to search for on Steam.\n\nExample: \"war\", \"vr\", \"football\", etc.",
"items": {
"type": "string"
},
"default": [
"war"
]
},
"max_items_per_keyword": {
"title": "Maximum items to fetch per keyword ๐",
"type": "integer",
"description": "The maximum number of items to retrieve from the search results, for each keyword.",
"default": 80
}
}
},
"runsResponseSchema": {
"type": "object",
"properties": {
"data": {
"type": "object",
"properties": {
"id": {
"type": "string"
},
"actId": {
"type": "string"
},
"userId": {
"type": "string"
},
"startedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"finishedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"status": {
"type": "string",
"example": "READY"
},
"meta": {
"type": "object",
"properties": {
"origin": {
"type": "string",
"example": "API"
},
"userAgent": {
"type": "string"
}
}
},
"stats": {
"type": "object",
"properties": {
"inputBodyLen": {
"type": "integer",
"example": 2000
},
"rebootCount": {
"type": "integer",
"example": 0
},
"restartCount": {
"type": "integer",
"example": 0
},
"resurrectCount": {
"type": "integer",
"example": 0
},
"computeUnits": {
"type": "integer",
"example": 0
}
}
},
"options": {
"type": "object",
"properties": {
"build": {
"type": "string",
"example": "latest"
},
"timeoutSecs": {
"type": "integer",
"example": 300
},
"memoryMbytes": {
"type": "integer",
"example": 1024
},
"diskMbytes": {
"type": "integer",
"example": 2048
}
}
},
"buildId": {
"type": "string"
},
"defaultKeyValueStoreId": {
"type": "string"
},
"defaultDatasetId": {
"type": "string"
},
"defaultRequestQueueId": {
"type": "string"
},
"buildNumber": {
"type": "string",
"example": "1.0.0"
},
"containerUrl": {
"type": "string"
},
"usage": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "integer",
"example": 1
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
},
"usageTotalUsd": {
"type": "number",
"example": 0.00005
},
"usageUsd": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "number",
"example": 0.00005
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
}
}
}
}
}
}
}
}
```