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

Scrape reviews for any Steam game: recommendation (thumbs up/down), text, playtime, helpfulness, author and dates, by app ID or game name. Official Steam API, no key needed.

- **URL**: https://apify.com/straightforward\_hydra/steam-reviews-scraper.md
- **Developed by:** [Dev D](https://apify.com/straightforward_hydra) (community)
- **Categories:** Social media, Automation, Developer tools
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $2.00 / 1,000 reviews

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/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 🎮

**Scrape reviews for any Steam game — recommendation (thumbs up/down), text, playtime, helpfulness, author and dates — by app ID or game name. Official Steam API, no key required.**

Steam reviews are a goldmine for game developers, publishers and market researchers. This Actor pulls reviews for one or more games straight from Steam's official public reviews endpoint, with filters for language, review type and sort order, and returns clean structured records — including each reviewer's **playtime** and whether they recommend the game.

> Uses Steam's official public reviews API — no key, no login, no browser.

***

### What you can do with it

- 🎮 **Track your game's reviews** — monitor sentiment, catch complaints, measure updates.
- 🕵️ **Competitor analysis** — see what players love and hate about other games.
- 🗣️ **Voice of player** — mine feedback, bugs and feature requests.
- 📊 **Market research** — analyze reviews, playtime and recommendation rates.
- 🔔 **Review alerts** — run on a schedule and push negative reviews to Slack.

### Features

- ✅ **No API key** — official Steam endpoint, works out of the box.
- ✅ **By app ID or game name** — pass IDs, or let it resolve names.
- ✅ **Rich records** — recommendation, text, playtime, helpful/funny votes, purchase type, Steam Deck flag, author history.
- ✅ **Filters** — language, positive/negative, sort by recent / updated / helpful.
- ✅ **Low-maintenance** — official Steam API with cursor pagination.

***

### Finding a game's app ID

The **app ID** is the number in the Steam store URL:
`store.steampowered.com/app/`**`1245620`**`/ELDEN_RING` → app ID is `1245620`.
Or just pass the game **name** and the Actor resolves it.

### Input

| Field | Description |
|---|---|
| **Steam app IDs** | Numeric app IDs, e.g. `730`, `1245620`. |
| **Game names** | Names to resolve automatically, e.g. `Elden Ring`. |
| **Review language** | `all`, `english`, `german`, … |
| **Sort / filter** | Most recent / recently updated / most helpful. |
| **Review type** | All / positive only / negative only. |
| **Purchase type** | All / Steam / non-Steam. |
| **Max reviews per game** | Cap per game (default 200). |
| **Max results** | Overall cap. |

#### Example — recent negative reviews for a game

```json
{
  "gameNames": ["Cyberpunk 2077"],
  "language": "english",
  "sortBy": "recent",
  "reviewType": "negative",
  "maxReviewsPerApp": 300
}
```

### Output

Each row is one review:

```json
{
  "app_id": "1245620",
  "game_name": "ELDEN RING",
  "recommendation_id": "123456789",
  "language": "english",
  "review": "Incredible game, brutal but fair…",
  "voted_up": true,
  "votes_up": 42,
  "votes_funny": 3,
  "weighted_vote_score": 0.86,
  "comment_count": 1,
  "steam_purchase": true,
  "received_for_free": false,
  "written_during_early_access": false,
  "primarily_steam_deck": false,
  "created_at": "2026-07-10T18:03:22+00:00",
  "updated_at": "2026-07-10T18:03:22+00:00",
  "author_steamid": "7656119…",
  "author_num_games_owned": 120,
  "author_num_reviews": 8,
  "playtime_forever_min": 4200,
  "playtime_at_review_min": 4100,
  "playtime_last_two_weeks_min": 320
}
```

### Run it on a schedule

Schedule the Actor to pull new reviews daily, and connect a **Slack / email / webhook / Google Sheets** integration to route negative reviews to your team.

### Notes & limitations

- Uses Steam's official public reviews API — no key needed.
- Playtime is reported in minutes.
- `voted_up` = the reviewer recommends the game (Steam has thumbs up/down, not star ratings).
- This is **public review data**.

***

#### Keywords

Steam reviews, Steam scraper, game reviews, Steam review scraper, game reviews scraper, Steam data, game analytics, player reviews, gaming market research, review scraper, Steam API, game sentiment, voice of player, game feedback, Steam game data, review monitoring, gaming intelligence, user reviews, Steam store, game intelligence.

# Actor input Schema

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

Steam app IDs, e.g. 730 (Counter-Strike 2), 1245620 (Elden Ring). Find it in the store URL: store.steampowered.com/app/<APPID>.

## `gameNames` (type: `array`):

Game names to look up instead of IDs, e.g. "Elden Ring". The top matching game is used. Merged with the App IDs above.

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

Steam language filter, e.g. all, english, french, german, schinese. Default all.

## `sortBy` (type: `string`):

recent = newest first; updated = recently updated; all = by helpfulness.

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

Keep positive (recommended), negative (not recommended), or all reviews.

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

Filter by how the reviewer got the game.

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

Cap the number of reviews returned per game. Default 200.

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

Stop after this many reviews in total. Leave empty for no limit.

## Actor input object example

```json
{
  "appIds": [
    "1245620"
  ],
  "language": "all",
  "sortBy": "recent",
  "reviewType": "all",
  "purchaseType": "all",
  "maxReviewsPerApp": 200
}
```

# 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": [
        "1245620"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("straightforward_hydra/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": ["1245620"] }

# Run the Actor and wait for it to finish
run = client.actor("straightforward_hydra/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 '{
  "appIds": [
    "1245620"
  ]
}' |
apify call straightforward_hydra/steam-reviews-scraper --silent --output-dataset

```

## MCP server setup

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

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/PTfyQqVbvedbAUfgr/builds/7MkVY0XFK1m7eI9sG/openapi.json