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

🚀 Effortlessly scrape Steam game reviews with our advanced Actor! 🎮 Collect comprehensive review data, including helpfulness, play time, and reviewer details. Perfect for game developers, marketers, and researchers seeking deep insights into player feedback and experiences. 📊🕹️

- **URL**: https://apify.com/easyapi/steam-reviews-scraper.md
- **Developed by:** [EasyApi](https://apify.com/easyapi) (community)
- **Categories:** Social media
- **Stats:** 57 total users, 2 monthly users, 100.0% runs succeeded, 2 bookmarks
- **User rating**: No ratings yet

## Pricing

from $2.99 / 1,000 results

This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.

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 Reviews Scraper

This Actor scrapes game reviews from Steam based on a given game's review URL. It utilizes Puppeteer with stealth mode to navigate through review pages and extract detailed information about Steam game reviews.

### ✨ Features

- 🔍 Scrape reviews for any Steam game using its review URL
- 📊 Extract comprehensive review data including helpfulness, rewards, and play time
- 👤 Collect reviewer information such as name, avatar, and profile URL
- 🕰️ Gather review posting dates and comment counts
- 🔢 Configurable maximum number of results
- 🕵️‍♂️ Uses stealth mode to avoid detection
- 🔄 Automatic pagination through infinite scrolling

### 📥 Input

The Actor accepts the following input parameters:

- `reviewUrl` (required): The URL of the Steam game reviews to scrape
- `maxResults` (optional): The maximum number of reviews to scrape (default: 100)

### 📤 Output

The Actor outputs a dataset containing the following information for each review:

- 🆔 App ID
- 👍 Helpfulness count
- 🏅 Reward count
- ⭐ Review result (e.g., "Recommended")
- ⏱️ Hours on record
- 📅 Posted date
- 📝 Review text
- 💬 Review comment count
- 👤 Author details (avatar, name, products owned, profile URL)

### 🚀 Usage

To use this Actor, simply provide the review URL of the Steam game you want to scrape and optionally set the maximum number of results. The Actor will then navigate through the review pages, collecting review information until it reaches the specified limit or exhausts all available reviews.

This Actor is perfect for game developers, marketers, or researchers looking to gather insights from Steam game reviews.

### 💡 Use Cases

- 📊 Game Performance Analysis: Track player sentiment and feedback
- 🎯 Marketing Research: Gather insights on player experiences and opinions
- 🔬 User Experience Studies: Analyze player behavior and preferences
- 🏆 Competitive Analysis: Compare reviews across different games

### 🆘 Support

If you encounter any issues or have questions about using this Actor, please don't hesitate to reach out through Apify's support channels.

#### Input Example

A full explanation of an input example in JSON.

```
{
  "maxResults": 100,
  "reviewUrl": "https://steamcommunity.com/app/2195250/reviews/"
}
```

#### Output sample

The results will be wrapped into a dataset which you can always find in the **Storage** tab. Here's an excerpt from the data you'd get if you apply the input parameters above:

And here is the same data but in JSON. You can choose in which format to download your data: JSON, JSONL, Excel spreadsheet, HTML table, CSV, or XML.

```
[
	{
		"appId": "2195250",
		"helpfullNum": "No one has rated this review as helpful yet",
		"rewardNum": "0",
		"reviewResult": "Recommended",
		"hoursOnRecord": "384.5 hrs on record",
		"postedDate": "October 7",
		"reviewText": "idk",
		"reviewCommnetCount": "0",
		"authorAvator": "https://avatars.akamai.steamstatic.com/5c58e903a49f38f82561fd0a3d68d4862cd560a7.jpg",
		"authorName": "AnhBaTraCu",
		"authorProducts": "",
		"authorProfileUrl": "https://steamcommunity.com/profiles/76561198350721055/"
	},
	{
		"appId": "2195250",
		"helpfullNum": "No one has rated this review as helpful yet",
		"rewardNum": "0",
		"reviewResult": "Recommended",
		"hoursOnRecord": "48.7 hrs on record",
		"postedDate": "October 6",
		"reviewText": "Good Game",
		"reviewCommnetCount": "0",
		"authorAvator": "https://avatars.akamai.steamstatic.com/53ea4f7ff2c3fe22217aeae2cda4334f20d62cc8.jpg",
		"authorName": "SANTY",
		"authorProducts": "",
		"authorProfileUrl": "https://steamcommunity.com/id/santy_12/"
	},
    ...
]
```

# Actor input Schema

## `reviewUrl` (type: `string`):

The URL of the Steam game reviews to scrape (e.g., 'https://steamcommunity.com/app/2195250/reviews/')

## `maxResults` (type: `integer`):

Set the maximum number of reviews to scrape. The actor will stop when this limit is reached.

## `proxyConfiguration` (type: `object`):

Optionally, use Apify Proxy or custom HTTP proxy to avoid IP address-based blocking.

## Actor input object example

```json
{
  "reviewUrl": "https://steamcommunity.com/app/2195250/reviews/",
  "maxResults": 100,
  "proxyConfiguration": {}
}
```

# 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 = {};

// Run the Actor and wait for it to finish
const run = await client.actor("easyapi/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 = {}

# Run the Actor and wait for it to finish
run = client.actor("easyapi/steam-reviews-scraper").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{}' |
apify call easyapi/steam-reviews-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=easyapi/steam-reviews-scraper",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/acts/oCJW3Oz8qngPGgf1h/builds/3tb1PvwfC6H97y2OB/openapi.json