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

Scrape Steam user reviews for any game by app ID: review text, recommended or not, playtime, helpful votes, language, purchase type and dates, plus the review score summary. Public JSON endpoint, no login.

- **URL**: https://apify.com/literate\_universe/steam-reviews-scraper.md
- **Developed by:** [John Rutherford](https://apify.com/literate_universe) (community)
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.50 / 1,000 review rows

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 Game Reviews Scraper

Scrape **Steam user reviews for any game** by app ID: full review text, recommended or not, playtime at review, helpful and funny votes, language, purchase type, early-access flag and dates, plus the per-game review score summary. Public JSON endpoint, no login.

For game studios tracking sentiment after a patch, market researchers, ML datasets, and players who want to read the newest reviews in bulk.

### What you get

One row per review:

| Field | Meaning |
|---|---|
| `app_id`, `app_name`, `review_id`, `url` | Identity and link to the review |
| `recommended`, `review`, `language` | The verdict and text |
| `created_at`, `updated_at` | ISO timestamps |
| `votes_up`, `votes_funny`, `weighted_vote_score`, `comment_count` | Community reaction |
| `playtime_hours`, `playtime_at_review_hours`, `playtime_last_2w_hours` | Author playtime |
| `steam_purchase`, `received_for_free`, `written_during_early_access` | Context flags |
| `author_games_owned`, `author_reviews`, `author_steamid` | Reviewer profile stats |

The run's key-value store holds `SUMMARY` with each app's `review_score_desc`, `total_positive`, `total_negative` and `total_reviews`.

Sample row:

```json
{
  "app_id": 570,
  "app_name": "Dota 2",
  "recommended": true,
  "review": "Still the deepest game I own. 3,000 hours and counting.",
  "language": "english",
  "created_at": "2026-09-08T21:14:03.000Z",
  "votes_up": 42,
  "playtime_hours": 3012.4
}
```

### Input

| Option | Default | What it does |
|---|---|---|
| **Steam app IDs** | | One or more app IDs |
| **Order** | Most recent | Recent, recently updated, or most helpful |
| **Language** | all | Steam language code |
| **Review type** | all | Positive or negative only |
| **Purchase type** | all | Steam purchases or non-Steam keys |
| **Days back** | 0 | Last N days, up to 365 |
| **Max reviews per app / total** | 500 / 20000 | Caps |

### Pricing

Pay per event: one small charge per review row.

### Notes and limits

- Steam returns up to 100 reviews per page; a 400 ms pause between pages is built in.
- Very large games have millions of reviews. Use **Days back** or the caps to scope a run.

# Actor input Schema

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

The number in the store URL, e.g. store.steampowered.com/app/570 is 570 (Dota 2).

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

Recent = newest first. Updated = recently edited first. All = Steam's helpfulness ranking.

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

Steam language code, e.g. english, german, schinese, or all.

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

Positive, negative or all.

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

Steam purchases only, non-Steam keys only, or all.

## `daysBack` (type: `integer`):

Only reviews from the last N days (0 = no limit; Steam caps this at 365).

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

Stop each app after this many reviews.

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

Stop after this many reviews across all apps.

## Actor input object example

```json
{
  "appIds": [
    "570"
  ],
  "filter": "recent",
  "language": "all",
  "reviewType": "all",
  "purchaseType": "all",
  "daysBack": 0,
  "maxReviewsPerApp": 500,
  "maxItems": 20000
}
```

# Actor output Schema

## `reviews` (type: `string`):

One row per review. Append ?format=csv for CSV.

## `summary` (type: `string`):

Per-app review score summary, stored in the key-value store under SUMMARY.

# 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"
    ]
};

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

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

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,literate_universe/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/BogNoHMmkNi9z9pam/builds/PE06AwNICisdQLV7r/openapi.json