# Steam Game Reviews Scraper (`neuton/steam-game-reviews-scraper`) Actor

Extract public Steam game reviews, review scores, language, votes, playtime, purchase flags, and author summary fields for gaming research.

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

## Pricing

Pay per usage

This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have.

Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage

## 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 Game Reviews Scraper

Extract public Steam game reviews and review-summary signals for player sentiment analysis, game research, competitor monitoring, and gaming AI/RAG datasets.

### Why this actor

Steam reviews are one of the clearest public signals for player sentiment, bugs, feature requests, monetization complaints, localization issues, and competitor positioning. Studios, publishers, analysts, and AI teams can use this actor to collect structured review rows for a single title or a recurring game watchlist.

SEO keywords covered by this Store page include Steam reviews scraper, Steam game sentiment data, Steam review API, player feedback dataset, game review text scraper, gaming market research, and Steam AI dataset.

### Output

- Recommendation ID, language, review text, positive/negative vote, votes, weighted score, comments, purchase flags, playtime, review timestamps, review-score summary, and Steam URL
- Raw Steam review payload and scrape timestamp

### Use cases

- Analyze player sentiment and feature complaints
- Monitor competitor games and community reception
- Build public review datasets for game studios, publishers, and researchers
- Feed AI agents with structured review rows
- Alert support, product, or community teams when new negative-review themes appear

### Example input

```json
{
  "appId": 730,
  "language": "english",
  "purchaseType": "all",
  "maxResults": 100
}
```

### Agent and automation workflows

Send rows into a warehouse, vector database, Airtable, Make, n8n, or a customer-feedback tool. Agents can cluster complaints, summarize positive and negative themes, compare recent review changes, or produce weekly competitor sentiment reports.

### Responsible use

This actor extracts public review content. Use it for research, moderation support, product analytics, and market intelligence. Do not use the output to harass reviewers, deanonymize users, spam communities, or make decisions that require non-public context.

### Pricing

Recommended launch pricing: $3-$4 per 1,000 review rows, increasing toward $5-$7 per 1,000 after recurring sentiment-analysis usage appears.

# Actor input Schema

## `appId` (type: `string`):

Steam app ID, for example 730 for Counter-Strike 2.

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

Review language, or all.

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

Purchase filter, for example all or steam.

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

Maximum review rows to return.

## Actor input object example

```json
{
  "appId": "730",
  "language": "all",
  "purchaseType": "all",
  "maxResults": 100
}
```

# 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 = {};

// Run the Actor and wait for it to finish
const run = await client.actor("neuton/steam-game-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("neuton/steam-game-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 neuton/steam-game-reviews-scraper --silent --output-dataset

```

## MCP server setup

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

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/igyQUfdSHui6zOhaN/builds/N3vqTHcrCoyuecmnx/openapi.json