🚀 n8n Marketplace Intelligence & Analytics The most comprehensive n8n workflow analyzer on Apify – Go beyond basic scraping with built-in analytics, professional insights, and ML training data generation. --- ## 🎯 Why This Actor is Different Most n8n scrapers just collect data and stop there. This actor goes further: | Feature | Basic Scrapers | This Actor | |---------|---------------|------------| | Scrape workflows | ✅ | ✅ | | Advanced analytics | ❌ | ✅ | | ML training data | ❌ | ✅ | | Creator insights | ❌ | ✅ | | Complexity metrics | ❌ | ✅ | | Professional reports | ❌ | ✅ | Perfect for: Content creators, ML engineers, market researchers, product teams, and automation experts. --- ## ⚡ Key Features ### 🔍 Smart Scraping - Collect 1 to 10,000 workflows from n8n marketplace - Optional category filtering (AI, DevOps, Marketing, etc.) - Rate-limited scraping (API-friendly) - Automatic pagination handling - Error recovery & retry logic ### 📊 Advanced Analytics Get comprehensive insights automatically: - Top 30 most-used nodes with usage percentages - Top 15 categories distribution - Pricing analysis (free vs paid breakdown) - Complexity metrics (simple to very complex) - Top 20 creators by workflow count - Most viewed workflows with engagement data ### 🤖 ML Training Data Generate fine-tuning datasets in multiple formats: - Alpaca format (Llama, Mistral compatible) - OpenAI format (GPT fine-tuning ready) - 4,000+ training examples from real workflows - Clean, structured, ready to use ### 📈 Professional Output All data structured and export-ready: - Clean JSON format - Normalized fields - Comprehensive metadata - Multiple export options --- ## 💡 Use Cases ### 📚 Content Creation Find trending workflows → Analyze patterns → Create tutorials Example: Discover that "AI + Telegram" workflows get 10x more views → Create tutorial series on AI chatbots ### 🤖 Machine Learning Scrape workflows → Generate training data → Fine-tune LLM Example: Build an AI that generates n8n workflows from natural language descriptions ### 📊 Market Research Scrape quarterly → Compare trends → Strategic insights Example: Track which integrations are growing fastest to guide product decisions ### 🛠️ Product Development Analyze workflow patterns → Identify user needs → Build solutions Example: See that 70% of workflows use HTTP Request → Prioritize API features --- ## 📂 Output Data ### 1️⃣ Dataset (Structured Workflow Data) Each workflow includes: json { "id": 123, "name": "AI Chatbot Workflow", "description": "Build a Telegram bot using OpenAI...", "totalViews": 50000, "price": null, "nodes": [ { "name": "n8n-nodes-base.telegram", "displayName": "Telegram", "categories": ["Communication"] } ], "workflowCategories": [ {"name": "AI"}, {"name": "Communication"} ], "user": { "username": "creator123", "name": "John Doe", "verified": true } } Download as: JSON, CSV, or Excel from the Dataset tab --- ### 2️⃣ Key-Value Store (Analysis & ML Data) #### 📈 analysis - Comprehensive Metrics json { "metadata": { "total_workflows": 1000, "analysis_date": "2025-01-15T10:30:00Z" }, "top_nodes": [ {"node": "HTTP Request", "count": 730, "percentage": 73.0}, {"node": "Code", "count": 520, "percentage": 52.0} ], "top_categories": [ {"category": "AI", "count": 320}, {"category": "DevOps", "count": 180} ], "pricing_analysis": { "free_workflows": 860, "paid_workflows": 140, "free_percentage": 86.0, "average_price": 12.50 }, "complexity_analysis": { "average_nodes": 8.5, "distribution": { "simple_1_5": {"count": 400, "percentage": 40.0}, "medium_6_10": {"count": 350, "percentage": 35.0} } }, "top_creators": [ { "username": "n8n_master", "workflow_count": 45, "total_views": 250000, "verified": true } ], "top_viewed": [ { "name": "Build Your First AI Agent", "views": 150000, "url": "https://n8n.io/workflows/123" } ] } #### 🤖 training_data_alpaca - ML Training Data (Alpaca Format) json [ { "instruction": "Create an n8n workflow for: AI Email Assistant\n\nDescription: Automatically categorize and respond to emails using AI", "input": "", "output": "{\n \"nodes\": [\n {\"type\": \"Gmail Trigger\"},\n {\"type\": \"OpenAI Chat Model\"},\n {\"type\": \"Gmail\"}\n ]\n}" } ] #### 🤖 training_data_openai - ML Training Data (OpenAI Format) For GPT fine-tuning via OpenAI API --- --- ## 📸 Example Output ### What You'll Get After Running When your actor finishes, you'll find data in two places: --- ### 1️⃣ Dataset Tab - Raw Workflow Data Location: Run → Dataset tab Sample workflow item: json { "id": 6270, "name": "Build Your First AI Agent", "description": "Learn how to build an AI agent that can understand natural language, access tools, and make decisions...", "totalViews": 156789, "price": null, "createdAt": "2024-03-15T10:30:00.000Z", "updatedAt": "2024-12-01T15:45:00.000Z", "nodes": [ { "name": "n8n-nodes-base.telegram", "displayName": "Telegram Trigger", "nodeCategories": [ {"name": "Communication"}, {"name": "Trigger"} ] }, { "name": "@n8n/n8n-nodes-langchain.agent", "displayName": "AI Agent", "nodeCategories": [ {"name": "AI"}, {"name": "LangChain"} ] }, { "name": "@n8n/n8n-nodes-langchain.lmChatOpenAi", "displayName": "OpenAI Chat Model", "nodeCategories": [ {"name": "AI"}, {"name": "Language Models"} ] } ], "workflowCategories": [ {"name": "AI"}, {"name": "Communication"}, {"name": "AI Agent"} ], "user": { "username": "n8n_creator", "name": "John Doe", "verified": true, "avatar": "https://gravatar.com/..." } } ↓ Download as: - JSON file - CSV spreadsheet - Excel workbook --- ### 2️⃣ Key-Value Store - Analysis & Insights Location: Run → Key-Value Stores → default → analysis Sample analysis output: json { "metadata": { "total_workflows": 1000, "analysis_date": "2025-01-15T14:30:00.000Z", "scraper_version": "1.0.0" }, "top_nodes": [ { "node": "HTTP Request", "count": 730, "percentage": 73.0 }, { "node": "Code", "count": 520, "percentage": 52.0 }, { "node": "Set", "count": 480, "percentage": 48.0 }, { "node": "IF", "count": 450, "percentage": 45.0 }, { "node": "OpenAI Chat Model", "count": 320, "percentage": 32.0 } ], "top_categories": [ {"category": "AI", "count": 320}, {"category": "DevOps", "count": 180}, {"category": "Marketing", "count": 165}, {"category": "Communication", "count": 140}, {"category": "Data Processing", "count": 125} ], "pricing_analysis": { "free_workflows": 860, "paid_workflows": 140, "free_percentage": 86.0, "paid_percentage": 14.0, "average_price": 12.50, "price_range": { "min": 5.00, "max": 49.00 } }, "complexity_analysis": { "average_nodes": 8.5, "min_nodes": 2, "max_nodes": 45, "distribution": { "simple_1_5": { "count": 400, "percentage": 40.0 }, "medium_6_10": { "count": 350, "percentage": 35.0 }, "complex_11_20": { "count": 180, "percentage": 18.0 }, "very_complex_20plus": { "count": 70, "percentage": 7.0 } } }, "top_creators": [ { "username": "n8n_master", "name": "Sarah Johnson", "workflow_count": 45, "total_views": 250000, "verified": true }, { "username": "automation_pro", "name": "Mike Chen", "workflow_count": 38, "total_views": 180000, "verified": true }, { "username": "workflow_wizard", "name": "Emma Davis", "workflow_count": 32, "total_views": 145000, "verified": false } ], "top_viewed": [ { "name": "Build Your First AI Agent", "views": 156789, "price": null, "creator": "n8n_creator", "url": "https://n8n.io/workflows/6270" }, { "name": "Automated Social Media Manager", "views": 142500, "price": 19.99, "creator": "marketing_guru", "url": "https://n8n.io/workflows/5834" }, { "name": "Email Processing with AI", "views": 128000, "price": null, "creator": "ai_specialist", "url": "https://n8n.io/workflows/4921" } ] } ↓ Download from Key-Value Store as JSON --- ### 3️⃣ ML Training Data (Optional) Location: Run → Key-Value Stores → default → training_data_alpaca When enabled (generateMLData: true), you'll get: json [ { "instruction": "Create an n8n workflow for: AI Email Assistant\n\nDescription: Automatically categorize and respond to emails using AI", "input": "", "output": "{\n \"nodes\": [\n {\n \"name\": \"Gmail Trigger\",\n \"type\": \"Gmail Trigger\",\n \"category\": [\"Communication\", \"Trigger\"]\n },\n {\n \"name\": \"OpenAI\",\n \"type\": \"OpenAI Chat Model\",\n \"category\": [\"AI\", \"Language Models\"]\n },\n {\n \"name\": \"Gmail\",\n \"type\": \"Gmail\",\n \"category\": [\"Communication\"]\n }\n ],\n \"node_count\": 3,\n \"node_types\": [\"Gmail Trigger\", \"OpenAI Chat Model\", \"Gmail\"]\n}" }, { "instruction": "Create an n8n workflow for: Social Media Scheduler\n\nDescription: Schedule and post content across multiple social media platforms", "input": "", "output": "{\n \"nodes\": [\n {\n \"name\": \"Schedule Trigger\",\n \"type\": \"Schedule Trigger\",\n \"category\": [\"Core Nodes\", \"Trigger\"]\n },\n {\n \"name\": \"Google Sheets\",\n \"type\": \"Google Sheets\",\n \"category\": [\"Productivity\"]\n },\n {\n \"name\": \"Twitter\",\n \"type\": \"Twitter\",\n \"category\": [\"Communication\", \"Social Media\"]\n },\n {\n \"name\": \"LinkedIn\",\n \"type\": \"LinkedIn\",\n \"category\": [\"Communication\", \"Social Media\"]\n }\n ],\n \"node_count\": 4,\n \"node_types\": [\"Schedule Trigger\", \"Google Sheets\", \"Twitter\", \"LinkedIn\"]\n}" } ] ↓ Ready for fine-tuning Llama 3, Mistral, or GPT! --- ### 📊 Visual Guide After your actor runs, you'll see: Run #12345 (Succeeded) ├── 📊 Dataset (1,000 items) │ └── Download as JSON/CSV/Excel │ ├── 🗂️ Key-Value Stores │ ├── analysis.json ← Analytics │ ├── training_data_alpaca.json ← ML data (Alpaca) │ └── training_data_openai.jsonl ← ML data (OpenAI) │ └── 📝 Log └── Execution details --- ### 🎯 Quick Access To download your data: 1. Go to your run page 2. Click "Dataset" tab → Download workflows 3. Click "Key-Value Stores" tab → Download analysis 4. Export format: Choose JSON, CSV, or Excel --- ### 💡 What You Can Do With This Data Dataset (Raw workflows): - ✅ Import into spreadsheet - ✅ Build workflow library - ✅ Feed into database - ✅ Create dashboards Analysis (Insights): - ✅ Create reports - ✅ Identify trends - ✅ Guide content strategy - ✅ Support business decisions ML Training Data: - ✅ Fine-tune LLMs - ✅ Build AI assistants - ✅ Train workflow generators - ✅ Create recommendation systems --- ## ⚙️ Input Configuration ### Analysis Mode Choose your level of depth: | Mode | Description | Use Case | |------|-------------|----------| | scrape_only | Just workflow data | Quick data collection | | scrape_and_analyze | Data + insights ⭐ | Most common use case | | full_with_ml | Everything + ML data | AI/ML projects | ### Parameters json { "mode": "scrape_and_analyze", "maxWorkflows": 1000, "category": "AI", "generateMLData": false } | Parameter | Type | Default | Description | |-----------|------|---------|-------------| | mode | String | scrape_and_analyze | Analysis mode (see above) | | maxWorkflows | Integer | 1000 | Max workflows to scrape (1-10,000) | | category | String | null | Optional category filter (e.g., "AI") | | generateMLData | Boolean | false | Generate ML training datasets | --- ## 🎓 Example Inputs ### Quick Start (50 workflows) json { "mode": "scrape_only", "maxWorkflows": 50 } ### Full Analysis (1,000 workflows) json { "mode": "scrape_and_analyze", "maxWorkflows": 1000 } ### Category-Specific with ML Data json { "mode": "full_with_ml", "maxWorkflows": 500, "category": "AI", "generateMLData": true } ### Maximum Analysis (All Workflows) json { "mode": "scrape_and_analyze", "maxWorkflows": 10000 } --- ## 💰 Pricing $0.50 per 1,000 workflows scraped ### What You Get for $0.50: - ✅ 1,000 complete workflow records - ✅ Comprehensive analysis included - ✅ All insights and metrics - ✅ Optional ML training data ### Cost Examples: - 50 workflows: ~$0.03 - 500 workflows: ~$0.25 - 1,000 workflows: $0.50 - 5,000 workflows: $2.50 ### Compare to Basic Scrapers ($0.25/1K): - ❌ Data only - ❌ No analysis - ❌ No ML data - ❌ No insights This actor: 2x the price, 10x the value! 🎯 --- ## 🤖 API & Automation Trigger this actor programmatically and integrate with: - n8n (meta!) - Make.com - Zapier - Custom scripts - Cron jobs ### Node.js Example: javascript import { ApifyClient } from 'apify-client'; const client = new ApifyClient({ token: 'YOUR_API_TOKEN' }); const run = await client.actor('YOUR_USERNAME/n8n-marketplace-analyzer').call({ mode: 'scrape_and_analyze', maxWorkflows: 1000 }); const dataset = await client.dataset(run.defaultDatasetId).listItems(); console.log(dataset.items); ### Python Example: python from apify_client import ApifyClient client = ApifyClient('YOUR_API_TOKEN') run = client.actor('YOUR_USERNAME/n8n-marketplace-analyzer').call( run_input={ 'mode': 'scrape_and_analyze', 'maxWorkflows': 1000 } ) dataset = client.dataset(run['defaultDatasetId']).list_items() print(dataset.items) ### cURL Example: bash curl -X POST https://api.apify.com/v2/acts/YOUR_USERNAME~n8n-marketplace-analyzer/runs \ -H "Authorization: Bearer YOUR_API_TOKEN" \ -H "Content-Type: application/json" \ -d '{ "mode": "scrape_and_analyze", "maxWorkflows": 1000 }' --- ## 📊 Performance & Efficiency - Fast: Scrapes 1,000 workflows in ~2-3 minutes - Efficient: Low compute usage (no browser needed) - Reliable: Error handling and automatic retries - Scalable: Handle 1 to 10,000 workflows easily - Cost-effective: Uses minimal Apify compute units --- ## 🎯 Real-World Applications ### For Content Creators Weekly Workflow: 1. Run actor with maxWorkflows: 500 2. Analyze top trending workflows 3. Identify content gaps 4. Create tutorial series 5. Repeat weekly Result: Always know what's hot in n8n community ### For ML Engineers Dataset Creation: 1. Run with full_with_ml mode 2. Download training_data_alpaca.json 3. Fine-tune Llama 3 or Mistral 4. Build AI workflow generator 5. Publish as SaaS Result: AI-powered n8n workflow assistant ### For Market Researchers Quarterly Analysis: 1. Scrape all workflows (10,000) 2. Export analysis to CSV 3. Create visualizations 4. Compare to last quarter 5. Present insights to stakeholders Result: Data-driven automation strategy ### For Product Teams Feature Prioritization: 1. Analyze most-used nodes 2. Identify integration gaps 3. Study workflow complexity 4. Plan roadmap 5. Validate with data Result: Build what users actually need --- ## 🛠️ Technical Details ### Built With: - Apify SDK - Actor framework - Python 3.11 - Core language - Requests - HTTP client - asyncio - Async operations ### Data Sources: - n8n.io public API - n8n marketplace workflows - Creator profiles - Usage statistics ### Output Formats: - JSON (structured) - CSV (spreadsheets) - Excel (business reports) --- ## 🔄 Workflow Integration ### Use with n8n (Ironic!) Trigger: Schedule (weekly) ↓ Action: Run Apify Actor ↓ Action: Get Dataset Items ↓ Action: Analyze Trends ↓ Action: Send Slack Notification ### Use with Make.com Schedule → Apify → Google Sheets → Email Report ### Use with Zapier New Actor Run → Get Results → Update Airtable --- ## 📈 Success Stories > "Used this to identify trending workflow patterns for my n8n tutorial series. Views increased 3x!" > > — Content Creator > "Generated 5,000 training examples and fine-tuned an LLM to generate workflows. Game changer!" > > — ML Engineer > "Quarterly reports from this actor guide our entire automation strategy." > > — Product Manager --- ## 💬 Support & Custom Development ### Need Help? - 📧 Email: mustaphaliaichi@gmail.com - 💬 GitHub: https://github.com/MuLIAICHI - 🌐 Website: n8nlearninghub.com ### Custom Services Available: - 🎨 Custom analysis reports - 🤖 ML model fine-tuning - 🔧 Bespoke scrapers - 📊 Data visualization - 🚀 Automation consulting --- ## 🎓 About the Creator Built by MuLIAICHI, an AI Engineer and n8n community contributor with: - 📚 Popular tutorial website (n8nlearninghub.com) - 🔬 Open-source projects on GitHub - 🤖 Expertise in LLM fine-tuning - 🎯 Deep n8n automation knowledge Other Projects: - n8n Workflow Analysis Project - Open-source analysis of 6,000+ workflows - FreelancerBot Pro - AI-powered freelancing assistant - n8n tutorial series - Weekly educational content --- ## 🚀 Get Started Now 1. Try it free with Apify's free tier ($5 credit) 2. Run a test with 50 workflows 3. See the insights in minutes 4. Scale up as needed ### Quick Start: json { "mode": "scrape_and_analyze", "maxWorkflows": 100 } Click "Try for Free" above to start! 🎉 --- ## ⭐ Why Choose This Actor? ✅ Most comprehensive - More features than any competitor ✅ Professional quality - Production-ready output ✅ Great value - 10x features for 2x price ✅ Active support - Built by community expert ✅ Proven results - Based on 6,000+ workflow analysis ✅ Regular updates - Maintained and improved --- ## 📋 Comparison Table | Feature | Basic Scrapers | This Actor | Premium | |---------|---------------|------------|---------| | Scrape workflows | ✅ | ✅ | ✅ | | Category filtering | ✅ | ✅ | ✅ | | Analytics | ❌ | ✅ | ✅ | | ML training data | ❌ | ✅ | ✅ | | Creator insights | ❌ | ✅ | ✅ | | Complexity analysis | ❌ | ✅ | ✅ | | Price per 1K | $0.25 | $0.50 | $2.00+ | | Value Score | ⭐⭐ | ⭐⭐⭐⭐⭐ | ⭐⭐⭐ | --- ## 🔗 Related Resources - n8n Documentation - n8n Community - Apify Documentation - n8nlearninghub.com - r/n8nLearningHub --- ## 📜 License & Terms - License: Apache-2.0 - Terms: Follow Apify Terms of Service - Usage: Respect n8n's API rate limits - Data: Public n8n marketplace data only --- ## 🎉 Ready to Get Insights? Try it now with 50 free workflows! This actor transforms raw workflow data into actionable intelligence. Perfect for anyone serious about n8n automation. --- ⭐ Star this actor if you find it useful! 💬 Questions? Issues? Contact us anytime! --- Last updated: January 2025 Version: 1.0.0 Maintained by: MuLIAICHI (mustaphaliaichi@gmail.com)