# Skool Comments Scraper 🔍💬- Cheap (`scrapestorm/skool-comments-scraper---cheap`) Actor

Easily extract comments from any Skool post, the go-to platform for learning communities 💬
Just enter a post URL to collect key data like content, author info, upvotes, and timestamps 🔍
Seamlessly integrate with your tools for community insights or engagement analysis! ⚡📊

- **URL**: https://apify.com/scrapestorm/skool-comments-scraper---cheap.md
- **Developed by:** [Storm\_Scraper](https://apify.com/scrapestorm) (community)
- **Categories:** Automation, Social media, Lead generation
- **Stats:** 6 total users, 1 monthly users, 100.0% runs succeeded, 1 bookmarks
- **User rating**: No ratings yet

## Pricing

$19.49/month + usage

To use this Actor, you pay a monthly rental fee to the developer. The rent is subtracted from your prepaid usage every month after the free trial period.You also pay for the Apify platform usage, which gets cheaper the higher Apify subscription plan you have.

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

## 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

### 💬 Skool Comments Scraper 🔍📘

The Skool Comments Scraper is a powerful tool designed to extract structured comment data from any Skool.com post — perfect for community analytics, audience engagement studies, or social listening.

Whether you're analyzing course feedback, tracking sentiment across posts, or researching top contributors, this scraper delivers clean, structured comment data — fast and at scale.

### 🔍 What It Does

Just provide a Skool post URL and specify how many comments you want — the scraper will retrieve:

✅ All comments on the post (up to your chosen limit)
✅ Structured data fields for each comment, including:

🧾 Field Descriptions:

| Field           | Description                                         |
| --------------- | --------------------------------------------------- |
| `comment_id`    | Unique comment identifier (UUID)                    |
| `content`       | Full content of the comment                         |
| `upvotes`       | Number of upvotes on the comment                    |
| `created_at`    | When the comment was originally posted (ISO format) |
| `updated_at`    | When the comment was last edited                    |
| `user_id`       | Unique ID of the user who posted the comment        |
| `user_name`     | Skool username (slug-style)                         |
| `first_name`    | First name of the commenter                         |
| `last_name`     | Last name of the commenter                          |
| `user_bio`      | Bio of the user (usually shows role or expertise)   |
| `user_location` | User’s listed location (if available)               |
| `user_linkedin` | LinkedIn profile URL (if available)                 |
| `user_picture`  | URL to the user's profile picture                   |

### 🛠 How to Use the Scraper

It’s plug-and-play and beginner-friendly:

🔗 Paste the URL of a Skool post

🔢 Set how many comments you want to extract

🚀 Launch the scraper

📦 Export your data to:

JSON

CSV

Excel

HTML / XML

### 💰 Pricing

This scraper uses a pay-per-month model. You’re only charged for successful results.

- **Price**: $19.49 per month.

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- [Zillow (Find a Home Improvement Agent) 🛠️)](https://apify.com/scrapestorm/zillow-find-a-home-improvement-agent)

***

### 🌐 Why Use This Scraper?

🧠 Community Insights — Discover what learners are saying and thinking.

📊 Engagement Tracking — Identify most active or influential members.

🔍 Content Feedback — Analyze reactions to courses, lessons, or challenges.

🤖 Automate Data Collection — Perfect for dashboards, reports, and UGC analysis.

### 📥 Input Schema

Input example :

```
{
  "url": "https://www.skool.com/microsoft-fabric/i-took-the-dp-700-today-and-i-passed",
  "maxitems": 80
}



```

Input Fields:

| Field      | Type    | Description                                                     |
| ---------- | ------- | --------------------------------------------------------------- |
| `url`      | string  | 🔗 Paste the full URL of the Skool post                         |
| `maxitems` | integer | 🔢 Max number of comments to scrape from the post (default: 80) |

### Output

```
{
  "comment_id": "8d1bf35b9f6f4bc79ce05a42eac8a0bc",
  "content": "Congratulations 👏",
  "upvotes": 1,
  "created_at": "2025-01-22T10:17:54.399103Z",
  "updated_at": "2025-01-22T18:58:10.319785Z",
  "user_id": "a3898136f4a5487bb504f3d2c5c30601",
  "user_name": "nijat-hajiyev-9786",
  "first_name": "Nijat",
  "last_name": "Hajiyev",
  "user_bio": "Business Data Analyst",
  "user_location": "Krakow, Poland",
  "user_linkedin": "https://www.linkedin.com/in/nijathajiyevv/",
  "user_picture": "https://assets.skool.com/f/a3898136f4a5487bb504f3d2c5c30601/9e0293c02cc44d33b6762d924fbfbd5c8641af14de9049e18342f0c27fb9813b"
}


```

### 📫 Support

😊 Leave us a star ⭐⭐⭐⭐⭐ if you are satisfied with the product!
🌍 For any questions, specific needs or issues, please reach out through Apify's platform or via email - [Storm\_Scraper 🌪️🌩️](https://apify.com/scrapestorm)

# Actor input Schema

## `startUrls` (type: `array`):

List of Skool post URLs to scrape comments from.
Examples:

- https://www.skool.com/microsoft-fabric/i-took-the-dp-700-today-and-i-passed
- https://www.skool.com/microsoft-fabric/another-post-slug

## `maxitems_per_url` (type: `integer`):

Limits how many comments will be scraped from EACH Skool post.

## Actor input object example

```json
{
  "startUrls": [
    "https://www.skool.com/brendan/video-suggestions?p=2757db8a"
  ],
  "maxitems_per_url": 50
}
```

# 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 = {
    "startUrls": [
        "https://www.skool.com/brendan/video-suggestions?p=2757db8a"
    ],
    "maxitems_per_url": 50
};

// Run the Actor and wait for it to finish
const run = await client.actor("scrapestorm/skool-comments-scraper---cheap").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 = {
    "startUrls": ["https://www.skool.com/brendan/video-suggestions?p=2757db8a"],
    "maxitems_per_url": 50,
}

# Run the Actor and wait for it to finish
run = client.actor("scrapestorm/skool-comments-scraper---cheap").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 '{
  "startUrls": [
    "https://www.skool.com/brendan/video-suggestions?p=2757db8a"
  ],
  "maxitems_per_url": 50
}' |
apify call scrapestorm/skool-comments-scraper---cheap --silent --output-dataset

```

## MCP server setup

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

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/Jwe3OAMVqiRrwWXXs/builds/kbn0dBHcqV3inRo1F/openapi.json
