# Skool Followers Scraper (`scraper-engine/skool-followers-scraper`) Actor 🔍 Skool Followers Scraper extracts followers and group members from Skool communities—names, profile URLs & basic info—for fast prospecting and audience research. 👥 Export CSV/JSON. 📊 Ideal for growth, competitor analysis, outreach & community intelligence. 🚀 - **URL**: https://apify.com/scraper-engine/skool-followers-scraper.md - **Developed by:** [Scraper Engine](https://apify.com/scraper-engine) (community) - **Categories:** Lead generation, Social media, Automation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $4.99 / 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 a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. 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. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use 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 Followers Scraper Skool Followers Scraper is a purpose-built Apify actor that turns public Skool profile follower pages into clean, structured data for fast prospecting, analysis, and enrichment. It fetches the profile URL with the followers tab, parses the embedded __NEXT_DATA__ JSON, and streams each follower as a dataset row—perfect for marketers, developers, data analysts, and researchers. At scale, it enables bulk audience research, outreach targeting, and automated workflows with reliable, repeatable results. 🚀 ### What data / output can you get? Below are the exact fields pushed to the dataset for each follower. Values are mapped from Skool’s embedded JSON and stored as flat keys so you can export to CSV or JSON with ease. | Data type | Description | Example value | | --------------- | ------------------------------------------------------- | ------------- | | id | Unique Skool user ID | "123456" | | name | Username/handle used to build the profile link | "janedoe" | | linkToProfile | Direct link to the follower’s Skool profile | "https://www.skool.com/@janedoe" | | pictureProfile | Profile photo URL from metadata | "https://cdn.skool.com/profile/janedoe.jpg" | | lastName | Last name (if available) | "Doe" | | firstName | First name (if available) | "Jane" | | bio | Short bio/description from metadata | "Founder @ Acme. Building community-driven products." | | online | Online status placeholder | "N/A" | | lastOffline | Last seen timestamp formatted as HH:MM:SS - DD/MM/YYYY | "13:24:41 - 18/04/2026" | | pictureBubble | Secondary image/avatar URL from metadata | "https://cdn.skool.com/bubble/janedoe.png" | | createdAt | Account created timestamp (raw, as provided) | "2025-06-10T12:34:56.000Z" | | updatedAt | Last updated timestamp (raw, as provided) | "2026-04-18T09:12:03.000Z" | Notes: - Rows are written one at a time, so you’ll see new followers appear live in the Output tab. - Export your results as JSON or CSV at any time from the dataset tab. ### Key features - ⚡ Boldly simple HTML parsing (no login) Reads the followers tab directly and parses the embedded __NEXT_DATA__ for reliable, structured extraction without cookies or session handling. - 📥 Live, row-by-row streaming to the dataset Each follower is saved immediately with Actor.push_data, so your Output table updates in real time as the run progresses. - 📚 Bulk input & normalization Paste one or many Skool profile URLs; supports plain strings or requestListSources objects with a url key. Add as many profiles as your plan allows. - 🎯 Per-profile caps for speed or depth Control how many followers to keep per profile with maxItems (schema default 100; runtime falls back to 30 if unset or 0) for quick tests or full exports. - 🛰️ Smart proxy escalation (optional) Starts direct, falls back to Apify datacenter when needed, and uses residential proxies with automatic retries. After a successful residential fetch, a “sticky” residential path is used for the rest of the run. - 📊 Easy exports Download clean JSON or CSV from the Apify dataset at any time—ready for sheets, CRMs, or analytics tools. - 🛠️ Developer-friendly Apify Actor Built on the Apify platform with Python and httpx; consume results programmatically from the Dataset API or connect to your automation stack. - 🧱 Production-ready reliability Robust request headers, retry logic, and proxy handling designed for stable runs across multiple profiles. ### How to use Skool Followers Scraper - step by step 1) Sign in to Apify Create or log in to your Apify account to run the actor. 2) Open the actor Find “Skool Followers Scraper” in your workspace and click Try it. 3) Add input URLs In the urls field, paste one or many Skool profile links (one per line works). You can provide: - Plain strings like "https://www.skool.com/@yourcreator" - Objects with a url property (requestListSources format) 4) Set limits Adjust maxItems to cap how many followers to keep per profile. The schema default is 100; if left unset or set to 0, the runtime uses 30 for quick tests. 5) (Optional) Configure proxy Expand proxyConfiguration only if your workspace uses Apify Proxy. The run starts direct, may fall back to datacenter, then residential if needed. 6) Start the run Click Start. Watch the Log for step-by-step progress and see the Output tab fill with follower rows in real time. 7) Export your data Open the dataset and export your results as JSON or CSV for immediate use in spreadsheets, CRMs, or pipelines. Pro Tip: Automate downstream workflows by consuming the dataset via the Apify API, or trigger exports to your data tools for enrichment and reporting. ### Use cases | Use case name | Description | | --- | --- | | Sales prospecting & outreach | Build targeted lead lists from Skool follower communities and export to CSV/JSON for personalized outreach. | | Competitor community analysis | Benchmark community size and activity by pulling recent followers from competitor profiles. | | Audience research & segmentation | Discover audience interests via follower bios and segment by creator or niche. | | CRM enrichment (CSV/JSON export) | Enrich records with profile links and photos by importing the dataset into your CRM or data warehouse. | | Data pipeline ingestion (API) | Consume the dataset programmatically from the Apify API to feed internal dashboards or workflows. | | Academic & community research | Study community growth and patterns using structured follower data captured at intervals. | ### Why choose Skool Followers Scraper? Skool Followers Scraper focuses on accurate, fast follower extraction from public Skool profile pages with automation-ready output. - 🎯 Precision from embedded JSON: Parses __NEXT_DATA__ for clean, structured fields without brittle HTML scraping. - 🚀 Scales with bulk inputs: Paste many profile URLs and control row caps per profile for fast iteration or full exports. - 💻 Developer access: Use the Apify Dataset to download JSON/CSV or consume programmatically in your pipelines. - 🛡️ Safe & public-only: Designed for publicly available pages—no login or cookies required. - 🔁 Robust connectivity: Direct first, then datacenter, then residential with sticky mode for stable runs. - 💸 Efficient operations: Streamed writes let you validate results early and export anytime. - 🧩 Workflow-friendly: Results slot neatly into spreadsheets, CRMs, and analytics without extra transformation. Compared to browser extensions and unstable scripts, this Apify-based actor provides consistent output, proxy-aware routing, and production-grade reliability. ### Is it legal / ethical to use Skool Followers Scraper? Yes—when done responsibly. This actor reads public Skool profile pages and extracts follower data that’s embedded client-side. Guidelines for compliant use: - Scrape only publicly accessible pages you’re allowed to access. - Review and respect Skool’s terms of service. - Use exported data responsibly and in line with applicable regulations (e.g., GDPR, CCPA). - Do not attempt to access private or authenticated content. - Consult your legal team for edge cases or regulated use. ### Input parameters & output format #### Example JSON input ```json { "urls": [ { "url": "https://www.skool.com/@liamottley" }, "https://www.skool.com/@yourcreator" ], "maxItems": 100, "proxyConfiguration": { "useApifyProxy": false } } ```` | Field | Type | Required | Default | Description | | --- | --- | --- | --- | --- | | urls | array | Yes | — | Paste Skool profile links (supports plain strings or requestListSources objects with a url key). Bulk is supported. | | maxItems | integer | No | 100 | Cap how many follower rows to keep for each profile (newest first). Tip: Leave unset or 0 for a 30-row quick test at runtime. | | proxyConfiguration | object | No | useApifyProxy: false (prefill) | Optional Apify Proxy configuration block. Leave off for typical runs; the actor still runs end-to-end. | #### Example JSON output ```json [ { "id": "123456", "name": "janedoe", "linkToProfile": "https://www.skool.com/@janedoe", "pictureProfile": "https://cdn.skool.com/profile/janedoe.jpg", "lastName": "Doe", "firstName": "Jane", "bio": "Founder @ Acme. Building community-driven products.", "online": "N/A", "lastOffline": "13:24:41 - 18/04/2026", "pictureBubble": "https://cdn.skool.com/bubble/janedoe.png", "createdAt": "2025-06-10T12:34:56.000Z", "updatedAt": "2026-04-18T09:12:03.000Z" } ] ``` Field notes: - online is set to "N/A" as a placeholder. - lastOffline is formatted for readability; if missing, it appears as "N/A". - createdAt and updatedAt are passed through as provided by the page and may be empty strings when unavailable. ### FAQ #### Do I need to log in to scrape followers? No. The actor reads public Skool profile pages and parses the embedded JSON—no login, cookies, or session handling required. #### What fields does the scraper return? It outputs a structured follower record with id, name, linkToProfile, pictureProfile, lastName, firstName, bio, online, lastOffline, pictureBubble, createdAt, and updatedAt. These appear in the Output tab as rows you can export. #### How many profiles or followers can I process at once? You can paste multiple profile URLs into urls—bulk is supported. Use maxItems to control how many followers are kept per profile (default 100 in the schema; the runtime uses 30 if unset or 0 for quick tests). #### What export formats are supported? You can export your dataset as JSON or CSV directly from the Apify platform at any time during or after the run. #### How does proxy handling work? The run starts direct. If the page doesn’t load cleanly, it falls back to an Apify datacenter connection, then residential with retries. After a successful residential fetch, a sticky residential path is used for the remainder of the run. #### What types of input URLs are accepted? Provide Skool profile links either as plain strings or as objects with a url property (requestListSources format). The actor normalizes both. #### How quickly will I see results? Rows are pushed one at a time as followers are parsed. You’ll see the Output table populate live, with progress visible in the Log. #### Is this compliant with Skool’s terms? It extracts data from public pages only. You are responsible for ensuring your use complies with Skool’s terms and applicable laws. ### Closing CTA / Final thoughts Skool Followers Scraper is built for fast, reliable extraction of public follower lists from Skool profile pages. It delivers structured fields, streams results live to your dataset, and supports bulk inputs with smart connectivity handling. Whether you’re a marketer, developer, analyst, or researcher, you can export JSON/CSV for sheets and CRMs or consume results programmatically. Start extracting cleaner follower data today and turn Skool communities into actionable insights. # Actor input Schema ## `urls` (type: `array`): 📋 **Paste profile links** (one per line is fine). Example: `https://www.skool.com/@yourcreator` ✅ Supports **bulk** — add as many profiles as your plan allows. ## `maxItems` (type: `integer`): 🔢 **Cap** how many follower rows to keep **for each** profile in your list (newest / first on the page first). 💡 Use a smaller number for quick tests; raise it when you’re ready for a full export. ## `proxyConfiguration` (type: `object`): 🎛️ **Optional.** Expand only if you route traffic through **Apify Proxy** (e.g. workspace policy or geo needs). 🙌 **Leave off** for typical runs — the Actor still runs end-to-end. ▸ This block is the right place to toggle Apify Proxy settings when you need them. ## Actor input object example ```json { "urls": [ { "url": "https://www.skool.com/@liamottley" } ], "maxItems": 100, "proxyConfiguration": { "useApifyProxy": false } } ``` # 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 '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "urls": [ { "url": "https://www.skool.com/@liamottley" } ], "proxyConfiguration": { "useApifyProxy": false } }; // Run the Actor and wait for it to finish const run = await client.actor("scraper-engine/skool-followers-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 '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "urls": [{ "url": "https://www.skool.com/@liamottley" }], "proxyConfiguration": { "useApifyProxy": False }, } # Run the Actor and wait for it to finish run = client.actor("scraper-engine/skool-followers-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 '{ "urls": [ { "url": "https://www.skool.com/@liamottley" } ], "proxyConfiguration": { "useApifyProxy": false } }' | apify call scraper-engine/skool-followers-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scraper-engine/skool-followers-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Skool Followers Scraper", "description": "🔍 Skool Followers Scraper extracts followers and group members from Skool communities—names, profile URLs & basic info—for fast prospecting and audience research. 👥 Export CSV/JSON. 📊 Ideal for growth, competitor analysis, outreach & community intelligence. 🚀", "version": "1.0", "x-build-id": "ryM4IdcjQdKHEB7rf" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scraper-engine~skool-followers-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scraper-engine-skool-followers-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/scraper-engine~skool-followers-scraper/runs": { "post": { "operationId": "runs-sync-scraper-engine-skool-followers-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/scraper-engine~skool-followers-scraper/run-sync": { "post": { "operationId": "run-sync-scraper-engine-skool-followers-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "urls" ], "properties": { "urls": { "title": "🎯 Skool profile URLs", "type": "array", "description": "📋 **Paste profile links** (one per line is fine). Example: `https://www.skool.com/@yourcreator`\n\n✅ Supports **bulk** — add as many profiles as your plan allows.", "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } }, "maxItems": { "title": "🧮 Max followers per profile", "minimum": 1, "maximum": 500, "type": "integer", "description": "🔢 **Cap** how many follower rows to keep **for each** profile in your list (newest / first on the page first).\n\n💡 Use a smaller number for quick tests; raise it when you’re ready for a full export.", "default": 100 }, "proxyConfiguration": { "title": "🔐 Advanced — Apify Proxy (optional)", "type": "object", "description": "🎛️ **Optional.** Expand only if you route traffic through **Apify Proxy** (e.g. workspace policy or geo needs).\n\n🙌 **Leave off** for typical runs — the Actor still runs end-to-end.\n\n▸ This block is the right place to toggle Apify Proxy settings when you need them." } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```