🚀 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.

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🎯 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.

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⚡ 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

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💡 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

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📂 Output Data

1️⃣ Dataset (Structured Workflow Data)

Each workflow includes:

{
  "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

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2️⃣ Key-Value Store (Analysis & ML Data)

📈 analysis - Comprehensive Metrics

{
  "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)

[
  {
    "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

---

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📸 Example Output

What You'll Get After Running

When your actor finishes, you'll find data in two places:

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1️⃣ Dataset Tab - Raw Workflow Data

Location: Run → Dataset tab

Sample workflow item:

{
  "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

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2️⃣ Key-Value Store - Analysis & Insights

Location: Run → Key-Value Stores → default → analysis

Sample analysis output:

{
  "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

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3️⃣ ML Training Data (Optional)

Location: Run → Key-Value Stores → default → training_data_alpaca

When enabled (generateMLData: true), you'll get:

[
  {
    "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!

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📊 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

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🎯 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

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💡 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

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⚙️ 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

{
  "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

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🎓 Example Inputs

Quick Start (50 workflows)

{
  "mode": "scrape_only",
  "maxWorkflows": 50
}

Full Analysis (1,000 workflows)

{
  "mode": "scrape_and_analyze",
  "maxWorkflows": 1000
}

Category-Specific with ML Data

{
  "mode": "full_with_ml",
  "maxWorkflows": 500,
  "category": "AI",
  "generateMLData": true
}

Maximum Analysis (All Workflows)

{
  "mode": "scrape_and_analyze",
  "maxWorkflows": 10000
}

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💰 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! 🎯

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🤖 API & Automation

Trigger this actor programmatically and integrate with:

• n8n (meta!)
• Make.com
• Zapier
• Custom scripts
• Cron jobs

Node.js Example:

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:

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:

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
  }'

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📊 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

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🎯 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

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🛠️ 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)

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🔄 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

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📈 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

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💬 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

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🎓 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

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🚀 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:

{
  "mode": "scrape_and_analyze",
  "maxWorkflows": 100
}

Click "Try for Free" above to start! 🎉

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⭐ 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

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📋 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	⭐⭐	⭐⭐⭐⭐⭐	⭐⭐⭐

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🔗 Related Resources

• n8n Documentation
• n8n Community
• Apify Documentation
• n8nlearninghub.com
• r/n8nLearningHub

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📜 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

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🎉 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.

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⭐ Star this actor if you find it useful!

💬 Questions? Issues? Contact us anytime!

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Last updated: January 2025 Version: 1.0.0 Maintained by: MuLIAICHI (mustaphaliaichi@gmail.com)