# Steam Reviews Scraper API | $0.10/1K (`angaba92/steam-reviews-scraper`) Actor

Scrape Steam game reviews from up to 20 Steam apps per run. Get recommended/not recommended, review text, playtime hours, votes, language and purchase type. Official Steam API, no browser, no blocking. $0.10 per 1,000 reviews. Export CSV, JSON, Excel or API.

- **URL**: https://apify.com/angaba92/steam-reviews-scraper.md
- **Developed by:** [Andres Garcia-Baquero Leon](https://apify.com/angaba92) (community)
- **Categories:** Developer tools, Automation, Integrations
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.10 / 1,000 steam reviews

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?

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 Reviews Scraper

Extract Steam game reviews at scale from up to **20 Steam apps per run**. Built on Steam's official public review API — no browser, no proxies, no blocking, no login.

Pay only for what you get: **$0.10 per 1,000 reviews**.

### What you get

Every review is returned as a flat, structured record ready for analysis:

| Field | Description |
|---|---|
| `appId`, `appUrl` | Steam app the review belongs to |
| `reviewId`, `reviewUrl` | Stable identifiers and direct link |
| `recommended`, `sentiment` | Thumbs up/down as boolean and as readable label |
| `text` | Full review body |
| `language` | Review language (english, spanish, schinese, …) |
| `authorPlaytimeForeverHours` | Total hours played — filter out drive-by reviews |
| `authorPlaytimeAtReviewHours` | Hours played when the review was written |
| `authorNumGamesOwned`, `authorNumReviews` | Reviewer credibility signals |
| `votesUp`, `votesFunny`, `commentCount`, `weightedVoteScore` | Community reception |
| `steamPurchase`, `receivedForFree` | Whether the copy was bought on Steam or given away |
| `writtenDuringEarlyAccess`, `primarilySteamDeck` | Context flags |
| `timestampCreated`, `timestampUpdated` | Unix timestamps |

### Use cases

- **Game studios** — track sentiment after a patch, a price change, or a launch.
- **Publishers and QA** — mine negative reviews for recurring bug and performance complaints.
- **Market research** — compare reception across competing titles in the same genre.
- **LLM and NLP datasets** — large volumes of opinionated, labelled text with an explicit sentiment column.
- **Refund and churn analysis** — cross playtime against sentiment to see where players give up.

### Input

```json
{
  "appIds": ["570", "730"],
  "maxResultsPerApp": 100,
  "sort": "recent",
  "reviewType": "all",
  "language": "all",
  "purchaseType": "all",
  "minPlaytimeHours": 0
}
```

- **appIds** — numeric Steam app IDs or full `store.steampowered.com/app/...` URLs. Up to 20 per run.
- **maxResultsPerApp** — cap per game (default 100).
- **sort** — `recent`, `updated`, or `most_helpful`.
- **reviewType** — `all`, `positive`, or `negative`. Going straight for negative reviews is the cheapest way to find bugs.
- **language** — Steam language code (`english`, `spanish`, `german`, …) or `all`.
- **purchaseType** — `all`, `steam`, or `non_steam_purchase` to exclude key-activated copies.
- **dayRange** — look-back window in days; applies when sorting by most helpful.
- **minPlaytimeHours** — drop reviews from players below this many hours.

Finding an app ID: it is the number in the store URL. `https://store.steampowered.com/app/570/Dota_2/` → `570`.

### Output

One dataset item per review. Export to **JSON, CSV, Excel, XML** or pull straight from the Apify API. Chain it into your own pipeline with the Apify SDK, webhooks, or a scheduled run.

### Pricing

**$0.10 per 1,000 reviews.** You are charged per delivered review, so a run that returns nothing costs nothing beyond the start.

### Notes and limits

- Uses Steam's public `appreviews` endpoint, which is rate-friendly and does not require authentication.
- Filters such as `reviewType`, `language` and `purchaseType` are applied by Steam; `minPlaytimeHours` is applied locally after fetching.
- Very large catalogues: run the actor per batch of games rather than one enormous run, so partial results are stored progressively.

### Feedback

Found a missing field or a bug? Leave an issue on the actor page — fixes usually ship within a day.

# Actor input Schema

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

Up to 20 numeric Steam app IDs or full store.steampowered.com/app/ URLs.

## `maxResultsPerApp` (type: `integer`):

Maximum matching reviews to return per game.

## `sort` (type: `string`):

Order Steam uses to return reviews.

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

Return only positive, only negative, or all reviews.

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

Steam language code such as english, spanish, german, or 'all' for every language.

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

Filter by how the reviewer obtained the game.

## `dayRange` (type: `integer`):

Look back this many days. Only applies when sort is 'Most helpful'.

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

Only return reviews from players with at least this many hours in the game. 0 disables the filter.

## Actor input object example

```json
{
  "appIds": [
    "570",
    "730"
  ],
  "maxResultsPerApp": 100,
  "sort": "recent",
  "reviewType": "all",
  "language": "all",
  "purchaseType": "all",
  "minPlaytimeHours": 0
}
```

# Actor output Schema

## `reviews` (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": [
        "570",
        "730"
    ],
    "maxResultsPerApp": 100,
    "sort": "recent",
    "reviewType": "all",
    "language": "all",
    "purchaseType": "all",
    "minPlaytimeHours": 0
};

// Run the Actor and wait for it to finish
const run = await client.actor("angaba92/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": [
        "570",
        "730",
    ],
    "maxResultsPerApp": 100,
    "sort": "recent",
    "reviewType": "all",
    "language": "all",
    "purchaseType": "all",
    "minPlaytimeHours": 0,
}

# Run the Actor and wait for it to finish
run = client.actor("angaba92/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": [
    "570",
    "730"
  ],
  "maxResultsPerApp": 100,
  "sort": "recent",
  "reviewType": "all",
  "language": "all",
  "purchaseType": "all",
  "minPlaytimeHours": 0
}' |
apify call angaba92/steam-reviews-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,angaba92/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/mPQsArw3eiJbwBkr7/builds/Llgrt85E62ZaXGhNk/openapi.json