# Steam Reviews Scraper - Official API, No Key (`pinkish_gallop/steam-reviews-scraper`) Actor

Export Steam user reviews for any game via Valve's official IUserReviewsService API (the replacement for the retired appreviews endpoint) plus store app details. Filter by language, sentiment, purchase type, playtime and date. No login, no proxy, no browser.

- **URL**: https://apify.com/pinkish_gallop/steam-reviews-scraper.md
- **Developed by:** [Sai](https://apify.com/pinkish_gallop) (community)
- **Categories:** Games, Developer tools
- **Security:** Limited permissions
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

Pay per event

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

## Steam Reviews Scraper - Official API, No Key

Export Steam user reviews for any game via Valve's official IUserReviewsService API (the replacement for the retired appreviews endpoint) plus store app details. Filter by language, sentiment, purchase type, playtime and date. No login, no proxy, no browser.

### What does this Actor do?

Steam is the biggest PC game store in the world, and its user reviews are the most honest signal of how players feel about a game. On 22 October 2026 Valve switched off the old `store.steampowered.com/appreviews?json=1` endpoint that most scripts and scrapers relied on - it now silently redirects to the store homepage. This Actor already uses the official replacement, **IUserReviewsService/GetAppReviews**, which returns public reviews without any API key, and enriches each review with the game's store details (name, developer, publisher, price, genres).

Key features:

- Plain HTTP against official public endpoints - no browser, no proxy, no login, runs on 128 MB memory.
- Pay only for results: one charge per row saved; your maximum charge per run is always respected.
- `maxItems` hard cap (default 100) and bounded pagination - runs can never loop forever.
- Incremental mode via a since-date so scheduled runs only fetch new data.
- Polite rate limiting, retries with exponential backoff and `Retry-After` support.
- Clean, flat, consistently named JSON fields ready for Excel, Google Sheets, BigQuery or your API.

### Who is it for?

- **Game studios and publishers** - track sentiment after a patch, sale or launch and catch negative review bombs early.
- **Market researchers** - compare review volume and positivity across competitors in a genre.
- **Data scientists / NLP** - build labelled sentiment datasets (each review carries `votedUp`) in dozens of languages.
- **Steam Deck & hardware analysis** - every review has `primarilySteamDeck` and, when Steam exposes it, the reviewer's OS and GPU.
- **Community managers** - export the most helpful reviews to plan FAQ, roadmap and store-page copy.

### How it works

For each app ID the Actor calls `appdetails` once (optional) and then pages through `GetAppReviews` 100 reviews at a time using Steam's cursor. Requests are spaced by `delayMs`, retried with exponential backoff on 429/5xx, and duplicates are dropped. When you set `sinceDate`, the date range is sent to Valve's server so only new reviews are downloaded - ideal for a daily or hourly schedule.

### Input

| Field | Type | Default | Description |
|---|---|---|---|
| `appIds` | array | - | Numeric app IDs (e.g. 730) or store URLs like https://store.steampowered.com/app/1145360/Hades/. |
| `maxItems` | integer | 100 | Hard cap on reviews saved and charged across all apps. |
| `maxItemsPerApp` | integer | 0 | 0 = no per-app cap (only the total cap applies). |
| `filter` | string | "recent" | recent = newest first (best for incremental runs), updated, helpful, funny. |
| `language` | string | "all" | Steam API language code (english, schinese, german...) or 'all'. |
| `reviewType` | string | "all" | all, positive or negative. |
| `purchaseType` | string | "all" | all, steam (bought on Steam) or non_steam_purchase (keys). |
| `sinceDate` | string | - | ISO date (YYYY-MM-DD). Uses the API's server-side date range so incremental runs stay cheap. |
| `minPlaytimeHours` | integer | 0 | Skip reviews from players with less playtime. |
| `includeAppDetails` | boolean | true | Adds name, developer, publisher, price, genres from the store appdetails API (1 extra request per app). |
| `delayMs` | integer | 500 | Polite rate limit. |

#### Example input

```json
{
  "appIds": [
    "1145360",
    "https://store.steampowered.com/app/730/"
  ],
  "maxItems": 500,
  "filter": "recent",
  "language": "english",
  "sinceDate": "2026-10-01"
}
```

### Output

Each result is one row in the default dataset. You can download it as JSON, CSV, Excel, XML or HTML, or read it through the Apify API. A real row from a test run on 26 October 2026:

```json
{
  "appId": 730,
  "appName": "Counter-Strike 2",
  "appType": "game",
  "developers": [
    "Valve"
  ],
  "publishers": [
    "Valve"
  ],
  "releaseDate": "Aug 21, 2012",
  "priceUsd": 0,
  "genres": [
    "Action",
    "Free To Play"
  ],
  "reviewId": "238567914",
  "language": "russian",
  "review": "Ебаное говно не регает",
  "votedUp": true,
  "votesUp": 0,
  "votesFunny": 0,
  "weightedVoteScore": 0.5,
  "commentCount": 0,
  "steamPurchase": true,
  "receivedForFree": false,
  "writtenDuringEarlyAccess": false,
  "primarilySteamDeck": false,
  "refunded": false,
  "hardwareOs": null,
  "hardwareGpu": null,
  "createdAt": "2026-10-25T19:55:28.000Z",
  "updatedAt": "2026-10-25T19:55:28.000Z",
  "authorSteamId": "76561199813609579",
  "authorNumReviews": 1,
  "authorPlaytimeHours": 413.4,
  "authorPlaytimeAtReviewHours": 413.4,
  "appReviewScoreDesc": "Very Positive",
  "appTotalReviews": 9944731,
  "url": "https://steamcommunity.com/profiles/76561199813609579/recommended/730/"
}
```

### Tips

- Use `filter: recent` plus `sinceDate` on a schedule for cheap incremental monitoring.
- Use `filter: helpful` to get the reviews Steam shows first on the store page.
- `language: all` returns every language; use codes like `schinese`, `german`, `brazilian` to focus.
- Playtime fields are converted to hours to make filtering easy in spreadsheets.

### Pricing

This Actor uses pay-per-event pricing: about **$0.50 per 1,000 results**. There is no monthly rental fee. Platform usage is minimal because the Actor runs on 128 MB with plain HTTP requests. Set **Maximum cost per run** in the run options and the Actor stops cleanly as soon as the limit is reached - you are never charged beyond it.

### Scheduling and integrations

Create an Apify Schedule (for example daily at 08:00) and pass a since-date to get only new items each time. Connect the dataset to Google Sheets, Slack, Zapier, Make, n8n or a webhook to receive results automatically, or call the Actor from Python or JavaScript using the Apify API client.

### Limitations

Only public reviews are available. Anonymous calls are rate-limited by Valve and responses may be cached up to 10 minutes, so very fresh reviews can appear with a short delay. `appTotalReviews` reflects the active filters (e.g. date range).

### FAQ

**Do I need an account or API key on the source site?** No. Only public, unauthenticated endpoints are used.

**Do I need proxies?** No. The Actor makes a small number of well-spaced requests to official APIs, so datacenter IPs work fine.

**Why did my run return fewer items than maxItems?** The source simply had no more items matching your filters and date range, or your maximum cost per run was reached.

**Is this legal?** The Actor only reads publicly available data through documented public endpoints. You are responsible for using the data in line with the source's terms and applicable laws such as GDPR, especially for personal data.

**Something broke?** Open an issue on the Actor's Issues tab with your run ID and we will fix it quickly.

# Actor input Schema

## `appIds` (type: `array`):

Numeric app IDs (e.g. 730) or store URLs like https://store.steampowered.com/app/1145360/Hades/.

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

Hard cap on reviews saved and charged across all apps.

## `maxItemsPerApp` (type: `integer`):

0 = no per-app cap (only the total cap applies).

## `filter` (type: `string`):

recent = newest first (best for incremental runs), updated, helpful, funny.

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

Steam API language code (english, schinese, german...) or 'all'.

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

all, positive or negative.

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

all, steam (bought on Steam) or non_steam_purchase (keys).

## `sinceDate` (type: `string`):

ISO date (YYYY-MM-DD). Uses the API's server-side date range so incremental runs stay cheap.

## `minPlaytimeHours` (type: `integer`):

Skip reviews from players with less playtime.

## `includeAppDetails` (type: `boolean`):

Adds name, developer, publisher, price, genres from the store appdetails API (1 extra request per app).

## `delayMs` (type: `integer`):

Polite rate limit.

## Actor input object example

```json
{
  "appIds": [
    "1145360"
  ],
  "maxItems": 100,
  "maxItemsPerApp": 0,
  "filter": "recent",
  "language": "all",
  "reviewType": "all",
  "purchaseType": "all",
  "minPlaytimeHours": 0,
  "includeAppDetails": true,
  "delayMs": 500
}
```

# Actor output Schema

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

No description

## `resultsView` (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 = {
    "appIds": [
        "1145360"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("pinkish_gallop/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 = { "appIds": ["1145360"] }

# Run the Actor and wait for it to finish
run = client.actor("pinkish_gallop/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 '{
  "appIds": [
    "1145360"
  ]
}' |
apify call pinkish_gallop/steam-reviews-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,pinkish_gallop/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/WHHAKhEhfWI81qPJH/builds/Pael6gmFmJt1I9yQV/openapi.json