# Steam Reviews Scraper (`alleserojje/steam-reviews-scraper`) Actor

Scrape Steam game reviews and the positive/negative summary via Steam's official API — rating, playtime, author, sentiment. No key. Pay per review.

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

## Pricing

from $1.00 / 1,000 steam reviews scrapers

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

**Steam Reviews Scraper** pulls user reviews and the overall positive/negative summary for any Steam game using Steam's official public JSON endpoints. Rating, playtime, author, sentiment, and (optionally) full game details. No API key, no anti-bot, no rental. Pay only per review.

### What it does

- Fetch **user reviews** for any game by Steam **App ID**, cursor-paginated.
- Get the aggregate **review summary** (total / positive / negative, score description).
- Filter by **language**, **positive/negative**, and **purchase type**.
- Optionally include **game details** (developer, publisher, genres, price, Metacritic, release date).
- Each review includes reviewer **playtime**, games owned, votes and dates.

### Input

| Field | Description |
|---|---|
| `appIds` | Steam game App IDs (e.g. `730` for CS2). |
| `language` | Review language (`english`, `all`, `brazilian`, …). |
| `reviewType` | `all` / `positive` / `negative`. |
| `purchaseType` | `all` / `steam` / `non_steam_purchase`. |
| `maxReviewsPerApp` | Reviews per game. |
| `includeGameDetails` | Also fetch game metadata. |

### Output

A `game` summary row per app (totals + details) followed by `review` rows: `votedUp`, `review`, `authorName`, `authorPlaytimeHours`, `votesUp`, `createdAt`, `steamPurchase`, and more.

### Pricing

**Pay per event:** billed once per row (review or game) returned. No monthly rental.

# Actor input Schema

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

Steam game App IDs (the number in the store URL, e.g. 730 for CS2).

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

Steam review language filter, e.g. english, all, brazilian.

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

Which reviews to return.

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

Filter by how the reviewer got the game.

## `maxReviewsPerApp` (type: `integer`):

Max reviews to fetch per game (cursor-paginated).

## `includeGameDetails` (type: `boolean`):

Also fetch game name, developer, price, genres, Metacritic.

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

Stop after this many items across all games. 0 = no limit.

## `proxy` (type: `object`):

Not required — Steam endpoints are open.

## Actor input object example

```json
{
  "appIds": [
    "730"
  ],
  "language": "english",
  "reviewType": "all",
  "purchaseType": "all",
  "maxReviewsPerApp": 200,
  "includeGameDetails": true,
  "maxItems": 0,
  "proxy": {
    "useApifyProxy": false
  }
}
```

# 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 '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "appIds": [
        "730"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("alleserojje/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": ["730"] }

# Run the Actor and wait for it to finish
run = client.actor("alleserojje/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": [
    "730"
  ]
}' |
apify call alleserojje/steam-reviews-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,alleserojje/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/WtSty66eMb6B3VFo4/builds/FQDrRDiChGM4FEM0F/openapi.json