# Steam Reviews Scraper — Game Reviews & Ratings (`hipersoft/steam-reviews-scraper`) Actor

Scrape user reviews and ratings for any game on Steam. Get the review text, recommended/not-recommended, helpful & funny votes, author playtime, purchase type, language, early-access flag and dates. One clean row per review as JSON, CSV or Excel.

- **URL**: https://apify.com/hipersoft/steam-reviews-scraper.md
- **Developed by:** [hiper soft](https://apify.com/hipersoft) (community)
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.0004 / review scraped

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?

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

## Steam Reviews Scraper — Game Reviews & Ratings

Extract **user reviews and ratings** for any game on **Steam**. Paste one or more store links (or App IDs), choose your filters, and get one clean row per review — the review text, whether it's recommended, helpful and funny votes, the author's playtime, purchase type, language, early-access flag and dates. Export to **JSON, CSV or Excel**, or pull straight from the API.

Perfect for **game market research**, competitor analysis, community sentiment tracking, spotting bugs and feature requests, review monitoring around launches and updates, and building review datasets for dashboards or LLMs.

***

### What you get

One flat, ready-to-use record per review:

| Field | Description |
|---|---|
| `appId` / `appName` | Steam App ID and game title |
| `recommendationId` | Unique review ID |
| `steamId` | Reviewer's Steam ID |
| `language` | Review language |
| `votedUp` | `true` = Recommended, `false` = Not Recommended |
| `review` | Full review text |
| `votesUp` / `votesFunny` | "Helpful" and "Funny" vote counts |
| `weightedScore` | Steam's helpfulness score (0–1) |
| `commentCount` | Comments on the review |
| `playtimeForeverMin` / `playtimeAtReviewMin` | Author playtime, total and at review time (minutes) |
| `authorGamesOwned` / `authorReviews` | Reviewer's library size and review count |
| `steamPurchase` / `receivedForFree` / `earlyAccess` / `steamDeck` | Review context flags |
| `createdAt` / `updatedAt` | Posted and last-edited dates (ISO 8601) |
| `reviewUrl` | Link to the review |
| `collectedAt` | When the row was scraped |

***

### How to use

#### 1. Add games

Paste Steam store links or numeric App IDs:

```json
{
  "appUrls": [
    "https://store.steampowered.com/app/570/Dota_2/",
    "730"
  ],
  "filterBy": "recent",
  "maxItems": 500
}
```

#### 2. Filter & order

- **Order reviews by** — Most recent, Recently updated, or All (helpfulness).
- **Recommendation** — all reviews, positive (recommended) only, or negative (not recommended) only.
- **Purchase type** — all, players who bought on Steam, or key activations only.
- **Language** — `all`, or a Steam language code such as `english`, `spanish`, `german`, `french`, `schinese`, `russian`, `japanese`, `koreana`, `brazilian`.
- **Max reviews** — cap the total (0 = no limit).

***

### Example output

```json
{
  "appId": "570",
  "appName": "Dota 2",
  "recommendationId": "187654321",
  "language": "english",
  "votedUp": true,
  "review": "Best MOBA out there once it clicks.",
  "votesUp": 42,
  "votesFunny": 3,
  "weightedScore": 0.61,
  "playtimeForeverMin": 69765,
  "playtimeAtReviewMin": 41230,
  "steamPurchase": true,
  "earlyAccess": false,
  "createdAt": "2026-09-19T14:10:00.000Z",
  "reviewUrl": "https://steamcommunity.com/profiles/7656119.../recommended/570/",
  "collectedAt": "2026-09-20T03:15:00.000Z"
}
```

***

### Common use cases

- **Game market research** — measure sentiment, review volume and recommendation ratio across titles.
- **Competitor analysis** — pull rivals' reviews to find complaints, praised features and churn drivers.
- **Launch & patch monitoring** — track how each update lands by filtering recent and updated reviews.
- **QA & feedback** — surface bug reports and feature requests straight from players.
- **Player insight** — segment by playtime, purchase type and language.
- **Datasets** — build clean, labelled review corpora for analysis or model training.

***

### Frequently asked questions

**Do I need any login, account or key?** No. Just paste game links and run.

**How many reviews can I get?** Set **Max reviews** to whatever you need (0 = no limit) — the scraper pages through a game's entire review history.

**Can I get only positive or only negative reviews?** Yes — use the Recommendation filter.

**Can I scrape reviews in one language only?** Yes — set the Language field to a Steam language code.

**What format is the data?** A flat table you can export as JSON, CSV or Excel, or fetch from the Apify API.

***

### Related scrapers

Building review intelligence across platforms? Pair this with our App Store reviews scraper and Google Play reviews scraper for mobile, all with the same clean, one-row-per-review output.

# Actor input Schema

## `appUrls` (type: `array`):

One or more Steam games to scrape reviews for. Paste the store page URL (e.g. https://store.steampowered.com/app/570/Dota\_2/) or a bare numeric App ID (570).

## `filterBy` (type: `string`):

Recent (newest first), Updated (recently edited first), or All (Steam's relevance/helpfulness order).

## `reviewType` (type: `string`):

Keep all reviews, only positive (recommended), or only negative (not recommended).

## `purchaseType` (type: `string`):

All reviews, only reviews from players who bought the game on Steam, or only those who activated a key elsewhere.

## `language` (type: `string`):

Review language — use 'all' for every language, or a Steam language code such as english, spanish, german, french, schinese, russian, japanese, koreana, brazilian.

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

Maximum number of reviews to collect across all games (0 = no limit; collect everything).

## Actor input object example

```json
{
  "appUrls": [
    "https://store.steampowered.com/app/570/Dota_2/"
  ],
  "filterBy": "recent",
  "reviewType": "all",
  "purchaseType": "all",
  "language": "all",
  "maxItems": 200
}
```

# Actor output Schema

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

The results as dataset items.

# 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 = {
    "appUrls": [
        "https://store.steampowered.com/app/570/Dota_2/"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("hipersoft/steam-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 '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = { "appUrls": ["https://store.steampowered.com/app/570/Dota_2/"] }

# Run the Actor and wait for it to finish
run = client.actor("hipersoft/steam-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 '{
  "appUrls": [
    "https://store.steampowered.com/app/570/Dota_2/"
  ]
}' |
apify call hipersoft/steam-reviews-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,hipersoft/steam-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 <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/4gVpNrYtO2RyV9TAp/builds/eut6qLXGK4YoHcjcG/openapi.json