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

Fetch public Steam store game reviews via the official appreviews JSON API. Returns recommendationid, public author steamid, review text, voted\_up, timestamp\_created, and playtime. Lightweight HTTP — no browser required.

- **URL**: https://apify.com/joseolmedosotoaguirre/steam-game-reviews.md
- **Developed by:** [jose olmedo soto aguirre](https://apify.com/joseolmedosotoaguirre) (community)
- **Categories:** Games, Social media, AI
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $1.20 / 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 Game Reviews Scraper

Fetch **public Steam store game reviews** via the official Store API — no browser, no HTML scraping.

```
GET https://store.steampowered.com/appreviews/{appid}?json=1&num_per_page=20
```

> **Responsible use & Terms of Service:** This actor reads only **publicly available** review text and public author Steam IDs. Use for legitimate research (sentiment, game intel, market analysis). Respect [Steam Subscriber Agreement](https://store.steampowered.com/subscriber_agreement/) / Valve terms, rate limits, and applicable law. Do **not** harvest private profile data, bypass age gates abusively, or hammer the API.

***

### What you get

| Field | Description |
| --- | --- |
| `recommendationid` | Steam recommendation id |
| `steamid` | Public author SteamID64 |
| `review` | Public review text |
| `voted_up` | `true` = recommended |
| `timestamp_created` | Unix seconds |
| `timestamp_created_iso` | ISO-8601 |
| `playtime_forever` / `_hours` | Author lifetime playtime (minutes / hours) |
| `playtime_at_review` / `_hours` | Playtime at review time |
| `language` | Review language |
| `appId` | Steam app id used for the run |
| `scrapedAt` | ISO timestamp of the run |

***

### Input

| Field | Required | Default | Notes |
| --- | --- | --- | --- |
| `appId` | yes | — | Numeric id (`730` CS2, `570` Dota 2) |
| `maxReviews` | | `20` | Max **100** reviews |
| `language` | | `english` | Steam language filter (`all` allowed) |
| `filter` | | `recent` | `recent` · `updated` · `all` |

#### Example input

```json
{
  "appId": "730",
  "maxReviews": 20,
  "language": "english",
  "filter": "recent"
}
```

***

### Sample output (real run)

App **730** (Counter-Strike 2) · `maxReviews: 20` — local `apify run`, **2026-07-29**. Extracted **20** public reviews (`query_summary.total_reviews` ≈ 2.5M, score “Very Positive”).

```json
{
  "recommendationid": "231560947",
  "steamid": "76561198769876625",
  "review": "very good",
  "voted_up": true,
  "timestamp_created": 1785294375,
  "timestamp_created_iso": "2026-07-29T03:06:15.000Z",
  "playtime_forever": 11350,
  "playtime_forever_hours": 189.2,
  "playtime_at_review": 11350,
  "playtime_at_review_hours": 189.2,
  "language": "english",
  "appId": "730",
  "scrapedAt": "2026-07-29T05:25:56.901Z"
}
```

***

### How it works

1. `GET /appreviews/{appId}?json=1&num_per_page=…`
2. Maps public fields; paginates with Steam `cursor` until `maxReviews`
3. Deduplicates by `recommendationid`

Stack: **Apify SDK + got**, Docker image `apify/actor-node:20`.

***

### Pricing (suggested)

| Plan | Price | Best for |
| --- | --- | --- |
| Pay per result | **$0.80–$2 / 1,000 reviews** | Occasional sentiment / game checks |
| Rental | **$15–$29 / month** | Recurring game monitoring |

Cheap compute (HTTP JSON). No residential proxy required for the public API.

***

### Local development

```bash
cd steam-game-reviews
export APIFY_TOKEN=$(grep '^APIFY_TOKEN=' ../.env | cut -d= -f2-)
npm install --registry https://registry.npmjs.org/
apify run
```

On Apify Cloud:

```bash
apify push -f
apify call joseolmedosotoaguirre/steam-game-reviews --input '{"appId":"730","maxReviews":20}'
```

# Actor input Schema

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

Numeric Steam store app id. Examples: 730 (Counter-Strike 2), 570 (Dota 2), 440 (Team Fortress 2).

## `maxReviews` (type: `integer`):

Maximum number of public reviews to return (1–100). Steam serves up to 100 per page; this actor paginates with the API cursor when needed. Default 10 keeps Store auto-tests fast (<5 min, non-empty dataset).

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

Steam language filter for reviews (e.g. english, spanish, all).

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

Steam filter parameter: recent, updated, or all.

## Actor input object example

```json
{
  "appId": "730",
  "maxReviews": 10,
  "language": "english",
  "filter": "recent"
}
```

# Actor output Schema

## `results` (type: `string`):

Items pushed to the default dataset.

# 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 = {
    "appId": "730",
    "maxReviews": 5,
    "language": "english",
    "filter": "recent"
};

// Run the Actor and wait for it to finish
const run = await client.actor("joseolmedosotoaguirre/steam-game-reviews").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 = {
    "appId": "730",
    "maxReviews": 5,
    "language": "english",
    "filter": "recent",
}

# Run the Actor and wait for it to finish
run = client.actor("joseolmedosotoaguirre/steam-game-reviews").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 '{
  "appId": "730",
  "maxReviews": 5,
  "language": "english",
  "filter": "recent"
}' |
apify call joseolmedosotoaguirre/steam-game-reviews --silent --output-dataset

```

## MCP server setup

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

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/acts/3iG4AnT0KyQyuteJC/builds/9usUHKC35JDHylB2i/openapi.json