An app store for scrapers — prebuilt, maintained actors for LinkedIn, Instagram, YouTube and hundreds of other platforms.
Pick this whenThe target is a major platform someone has already solved — buying the maintained scraper beats writing one that breaks.
What makes it different
Platform-specific scrapers that survive the sites' defences, maintained by their authors
Free credits to try before committing
The trainer's explicit choice over DIY for LinkedIn
What it does
Runs prebuilt scrapers for named platforms and returns structured data
Handles the platform-specific anti-bot work for you
What it does not do
Common wrong expectationsDoesn't do arbitrary pages as cleanly as Firecrawl
Doesn't solve geo-blocking alone — pair with proxies for LinkedIn
Where it sits in a stack
Platform data extraction where the maintenance burden of DIY is the real cost.
ShelfScraping & data sources · Marketplaces & directories
Our status · not-usingNo social-platform data in scope.
For your projectsNone currently.
| Session | Coverage | Moment | What happened |
|---|
| Session 6: Building an AI-Powered Lead Gen Machine | demonstrated | 1:47:51 | Profile-posts-scraper actor for LinkedIn (no cookies, URL input): run-actor → dataset-ID → get-dataset-items (native n8n node, learner-suggested); ~50 posts fetched |
| Session 17: Facebook Ads Competitor Research & Replication | demonstrated | 2:08:20 | Official Facebook Ads Scraper actor (~29k users), free plan; called via API from an n8n HTTP node using a ChatGPT-generated curl |
| Session 19: Content Strategy Pipeline — the YouTube Growth Stack, Built by an Agent Team of Chats | demonstrated | | YouTube Scraper actor (100k users); actors-as-APIs explained; agent-invented approval gate for paid runs |
| Day 9: Webhook vs API for Good — Apify Scraper, cURL Import, Structured Output, Gmail Drafts, then the Native-Node Rewrite | demonstrated | | Google Maps email actor; Integrations webhook; API token; native n8n nodes |
| Day 3: Markdown Prompting, Content DNA and Skills, MCP Everywhere (Vapi Call, Zomato, Apify), Goose and Local Models, a Voice Agent, and the Full n8n Customer-Support Build | demonstrated | | Scraper actor via MCP |
| AI Automation Mastery II: an AI LinkedIn Pipeline with Human-in-the-Loop Approval and Nano Banana Images, Apify Lead Scraping to Personalised Cold Drafts, an AI Job-Match Scorer, Telegram Bots, and the Six-Level AI Generalist Roadmap | demonstrated | | Harvest API actors; $5 free; run limits hit |
| Scenarios and Modules: Recipes, Employees, and the Relay Baton | demonstrated | | Example trigger |
| Day 2: Custom GPTs and Gems, Markdown Prompting, Cloning Your Writing Style, MCP in Daily Use, a Vibe-Coded Calorie Counter, and the Consultant-to-SaaS Road | demonstrated | | Instagram scraping via MCP |
| Basecamp 4: Introduction to n8n — II | explained | 2:58:23 | 'App store for APIs' — LinkedIn/Instagram/YouTube scrapers with free credits; pair with geo-proxies for LinkedIn |
| Session 2: How to Plan, Scope and Sell your AI Projects | explained | 1:20:04 | The scraping layer in the lead-qual design (LinkedIn lead + company profiles, websites); also the ToS-safe answer to 'is scraping LinkedIn legal?' — 'not legal; use Apify or another account' |
| Day 10: Principles for Building Agents — Three Levels of AI, the 7-Question Workflow-vs-Agent Test, Goldilocks Scope, Agent Prompting, and Tool Design | explained | | Scientist outreach, Instagram scraping |
| Day 11: Two Alternatives to n8n — Google Workspace Studio (VIP-Email Demo) and Lyzr Agent Studio (Knowledge Bases, Sub-Agents, a Manager, and API Deployment) | explained | | Dataset variable, unpin, community nodes, rotating IPs |
| AI Sprint: Meet GrokBot — Stop Prompting, Start Delegating (One Cloud Computer, a Chief of Staff, Four Specialist Bots, and the Reversible/Irreversible Rule) | explained | | Deeper scraping for the job bot |
| AI Sprint: Windsurf & Devin — Day 2 (Building Superplexity: Plan with Opus, Execute with Cascade, Review with Devin) | explained | | The Twitter access lane vs the $200/month X API; budget-gated, on-demand only |
| Basecamp 3: Introduction to n8n — I | mentioned | 3:00:53 | Trainer's choice for LinkedIn scraping instead of DIY |
| Office Hours I: Vetting an Idea, Niching Against the Frontier Labs, and Paul's Aircraft-Parts App (PWA, and 'What If I Get Hit by a Bus') | mentioned | | LinkedIn scraping; blocks increasing |
| Office Hours IV: PostHog over Plausible, the Launch-Fast Loop, Scraping Ethics, Agent Swarms with Memory, and Why You Never Give Credits Away Free | mentioned | | LinkedIn scraper actor |
| Office Hours V: Paul's Compliance Scanner Meets Firecrawl, Painkillers vs Vitamins, What a Real Second Brain Costs, and Why Selling Got Harder | mentioned | | Alternative scraping MCP |
| Session 5: Mastering Lead Generation | mentioned | 2:43:07 | Confirmed as a Google Maps scraping alternative |
| Session 9: Introduction to Cursor & its principles | mentioned | 0:49:59 | The credit-burner whose Reddit complaint thread led him to YT-DLP |
| Session 14: Claude Code — Advanced Workflows | mentioned | 1:23:29 | Cited as marketplace precedent in the scraping-legality gray-area answer |
| Session 25: Product Hunt Launch Playbook — Engineering as Marketing, Rules That Get You Banned, and a Real Launch Scheduled Live | mentioned | 1:17 | Scrape competitor launches |
| Session 26: Product-Led Activation & Lifecycle Growth — Turning a Free Tool into a Growth Machine | mentioned | 0:32 | Scrape YouTube engagers for personalized outreach - the 41K-views answer |
| Day 8: AI Workflows — Chaining Tools, the IDEA(L) Analysis Framework, Claude Skills vs MCP vs Projects, and the Reel-Cloning Pipeline | mentioned | | Scraper marketplace; cookie-login risk |
| AI Sprint: The Hermes Agent — Day 1 (Always-On Agents, the Employee-on-Day-One System, and the Self-Improving Ghostwriter) | mentioned | | The comparison point Scrape Creators replaces ('I'd have to remember which scraper is which') |
| AI Sprint: The Hermes Agent — Day 2 (Loop Engineering: the Scheduling Loop, the Delegation Loop, and the Skill Auditor) | mentioned | | Comparison point carried over from Day 1 |
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