# Steam Game Reviews Scraper (`scrapers_lat/steam-game-reviews-scraper`) Actor
Scrape Steam game reviews by app ID or game name. Filter by review type, language, purchase type and recency, and export author, playtime, review text, votes, weighted score, timestamps and a per-app review summary. Export to JSON, CSV or Excel.
- **URL**: https://apify.com/scrapers\_lat/steam-game-reviews-scraper.md
- **Developed by:** [Scrapers Lat](https://apify.com/scrapers_lat) (community)
- **Categories:** E-commerce, Social media, Automation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet
## Pricing
from $6.80 / 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/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
## Steam Game Reviews Scraper
> Scrape Steam game reviews at scale and export clean, structured data: the reviewer (SteamID, games owned, playtime), full review text, thumbs up or down, helpful and funny votes, Steam's weighted helpfulness score, created and updated timestamps, early-access and purchase flags, plus a per-app review summary (score and total positive/negative). Search by app ID or game name and filter by review type, language, purchase type and recency.
**📥 [Input](https://apify.com/scrapers_lat/steam-game-reviews-scraper/input-schema) · 📤 [Output](https://apify.com/scrapers_lat/steam-game-reviews-scraper/output-schema) · 💰 [Pricing](https://apify.com/scrapers_lat/steam-game-reviews-scraper/pricing) · ▶️ [Examples](https://apify.com/scrapers_lat/steam-game-reviews-scraper/examples)**
Reviewer & playtime every review
Text, votes & score plus per-app summary
JSON / CSV / Excel output formats
### What you get
Each record includes the **app ID** and **game name**, the unique **recommendation ID**, the **reviewer** (SteamID, games owned, review count and playtime), the full **review text** and **language**, whether it **recommends** the game, **helpful** and **funny** votes, Steam's **weighted vote score**, **created** and **updated** timestamps, flags for **purchased on Steam / received for free / early access / refunded / Steam Deck**, a link to the review, and a **per-app summary** (review score, score description, total positive and total negative).
You only pay for real review records. Empty or failed runs are never charged. No API key required.
### Who is it for
| Use case | Who benefits |
|---|---|
| Player sentiment | Studios and publishers tracking how players react to updates |
| Market research | Analysts mining opinions, playtime and recommendation rates |
| Community & QA | Teams surfacing bugs, complaints and requests from reviews |
| Data & ML | Builders assembling labelled review datasets for analysis |
### How to use it
1. Add one or more **Steam app IDs** (for example `730`), or use **game names** to search Steam.
2. Optionally filter by **review type** (positive/negative), **language**, **purchase type**, a **played** filter, and a **sort** (recent, updated or most helpful).
3. Set **Max Reviews To Scrape** and run. Export as JSON, CSV or Excel, or pull it through the Apify API.
### Frequently Asked Questions
**How do I find an app ID?**
It is the number in a game's store URL (store.steampowered.com/app/**730**/). You can also just type the game name into the search terms field.
**Can I collect reviews for several games at once?**
Yes. Add multiple app IDs or game names; the review cap is shared across all of them.
**Can I get only recent or only most-helpful reviews?**
Yes. Use the sort option: most recent, recently updated, or most helpful. For most helpful you can also set a day range.
**Which languages are supported?**
Any Steam review language (for example english, schinese, spanish), or set language to "all" for every language.
**How fresh is the data?**
Every record is read live at run time, so reviews and summary counts reflect Steam at the moment of the run (see observedAt).
### Export, API and AI agents (x402 + MCP)
Export the scraped data to **JSON, CSV or Excel**, pull it as a **dataset** through the Apify **API**, or wire it into your app with **no code**. This web scraper and data extractor also works for bulk data extraction and scheduled runs.
For AI agents: this Actor is available on **x402**, Apify's agentic payment standard built with Coinbase. An AI agent can discover, pay for and run it on its own with a funded wallet and a single HTTP request: no account, no subscription, no API key and no human in the loop. It also runs as an **MCP** tool inside Claude, Cursor and other AI clients out of the box. Learn more about [x402 agentic payments on Apify](https://docs.apify.com/platform/integrations/x402).
### Related scrapers
- [Steam Games Scraper](https://apify.com/scrapers_lat/steam-games-scraper)
- [Google Play App Reviews & Ratings Scraper](https://apify.com/scrapers_lat/google-play-reviews-scraper)
- [Apple App Store Reviews & Ratings Scraper](https://apify.com/scrapers_lat/app-store-reviews-scraper)
### More scrapers at scrapers.lat
This actor is built and maintained by [scrapers.lat](https://scrapers.lat), where we publish scrapers for public platforms: finance, news, real estate, jobs, e-commerce and government data. Browse the full catalog or ask us for a custom scraper at [scrapers.lat](https://scrapers.lat).
***
> This actor is an independent tool and has no affiliation with Steam or Valve. It only accesses publicly available review data. Use the results in accordance with the source's terms.
# Actor input Schema
## `appIds` (type: `array`):
One or more numeric Steam app IDs (e.g. '730' for Counter-Strike 2). Add several to collect reviews for multiple games in one run.
## `searchTerms` (type: `array`):
Optional. Search Steam by game name instead of app ID; the top matching game is used for each term.
## `reviewType` (type: `string`):
Return all reviews, only positive (thumbs up), or only negative (thumbs down).
## `language` (type: `string`):
Review language (e.g. 'english', 'schinese', 'spanish') or 'all' for every language.
## `purchaseType` (type: `string`):
All reviews, only reviews from copies purchased on Steam, or only non-Steam-purchase reviews.
## `sortBy` (type: `string`):
Order reviews by most recent, most recently updated, or most helpful (within the day range).
## `dayRange` (type: `integer`):
Optional. When sorting by most helpful, only consider reviews from the last N days (1-365).
## `playedFilter` (type: `string`):
Keep all reviews, only reviews from players with playtime at review, or only reviews with no recorded playtime.
## `reviewsFromDate` (type: `string`):
Optional. Only keep reviews created on or after this date (e.g. 2025-01-01).
## `reviewsToDate` (type: `string`):
Optional. Only keep reviews created on or before this date (e.g. 2025-12-31).
## `onlyWithDeveloperResponse` (type: `boolean`):
Optional. Only keep reviews the developer/publisher has replied to.
## `includeReviewBombing` (type: `boolean`):
Optional. Steam hides off-topic review-bombing activity by default; enable to include it.
## `maxReviews` (type: `integer`):
Maximum number of review records to collect across the whole run (spread across all apps).
## Actor input object example
```json
{
"appIds": [
"730"
],
"reviewType": "all",
"language": "english",
"purchaseType": "all",
"sortBy": "recent",
"playedFilter": "any",
"onlyWithDeveloperResponse": false,
"includeReviewBombing": false,
"maxReviews": 40
}
```
# 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 = {
"appIds": [
"730"
],
"maxReviews": 40
};
// Run the Actor and wait for it to finish
const run = await client.actor("scrapers_lat/steam-game-reviews-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 '' with your token.
client = ApifyClient("")
# Prepare the Actor input
run_input = {
"appIds": ["730"],
"maxReviews": 40,
}
# Run the Actor and wait for it to finish
run = client.actor("scrapers_lat/steam-game-reviews-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 '{
"appIds": [
"730"
],
"maxReviews": 40
}' |
apify call scrapers_lat/steam-game-reviews-scraper --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"type": "http",
"url": "https://mcp.apify.com/?tools=fetch-actor-details,scrapers_lat/steam-game-reviews-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 ` 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/8q8CPM0THX2Qi4EOf/builds/mtx85jPZ7ajupncBv/openapi.json