n8n Workflow Marketplace Analyzer

Analyze public n8n marketplace workflows and turn raw template metadata into useful automation intelligence. Extract workflow nodes, categories, creators, pricing, views, and dates, then generate reports on popular integrations, complexity, and marketplace demand.

Features

• Collects up to 15,000 public n8n marketplace workflows, enough for the complete current catalogue
• Streams normalized pages directly to the dataset instead of retaining the full raw response in memory
• Saves page-level checkpoints for safe resurrection of long scrape and analysis runs
• Extracts workflow IDs, names, descriptions, nodes, categories, creators, views, and prices
• Calculates top nodes, categories, creators, and viewed workflows
• Compares free and paid templates plus workflow complexity
• Filters marketplace collection by category
• Searches workflow names and descriptions by keyword
• Adds flat node, category, creator, AI, and paid/free fields for easy export
• Optionally generates Alpaca and OpenAI-compatible training data
• Saves workflow rows, analysis, training files, and run statistics separately

Use Cases

• Automation product research: identify popular integrations and workflow patterns
• Template strategy: find high-demand categories and common node combinations
• Competitive intelligence: compare creators, pricing, and workflow popularity
• Content research: discover examples for tutorials and automation guides
• AI datasets: generate structured examples from public workflow descriptions

Ready-Made Examples

• Find n8n Workflows Using Slack
• Research Popular n8n AI Agent Workflows
• Find n8n Marketing Automation Ideas
• Compare Popular n8n Integrations
• Build an n8n AI Training Dataset

Input

{
  "mode": "scrape_and_analyze",
  "maxWorkflows": 100,
  "startPage": 1,
  "searchQuery": "AI agent",
  "category": "",
  "generateMLData": false,
  "resumeFromCheckpoint": true
}

Output

Each default-dataset item is one n8n workflow:

{
  "id": 3124,
  "name": "Summarize support tickets with AI",
  "slug": "summarize-support-tickets-with-ai",
  "description": "Analyze and summarize incoming support tickets...",
  "url": "https://n8n.io/workflows/3124",
  "totalViews": 18420,
  "recentViews": 612,
  "price": 0,
  "featured": true,
  "nodeCount": 2,
  "nodeNames": ["Gmail", "OpenAI"],
  "categoryNames": ["AI", "Communication"],
  "isAI": true,
  "isPaid": false,
  "creatorUsername": "example",
  "creatorName": "Example Creator",
  "creatorVerified": true,
  "nodes": [
    { "name": "n8n-nodes-base.gmail", "displayName": "Gmail", "nodeCategories": [{ "name": "Communication" }] },
    { "name": "@n8n/n8n-nodes-langchain.openAi", "displayName": "OpenAI", "nodeCategories": [{ "name": "AI" }] }
  ],
  "workflowCategories": [{ "name": "AI" }],
  "user": { "username": "example", "verified": true },
  "createdAt": "2026-01-15T10:00:00.000Z",
  "updatedAt": "2026-06-30T10:00:00.000Z"
}

The key-value store separates the valuable derived outputs:

• analysis: top nodes, categories, integration pairs, AI-node adoption, creators, pricing, complexity, creation trends, and popular workflows
• training_data_*: optional ML datasets and metadata
• STATS: mode, filter, duration, records saved, and generated-output flags
• SCRAPE_CHECKPOINT: internal recovery state for resurrected runs

The dataset provides four views: overview, integrationResearch, creatorResearch, and rawDetails.

How to Use

1. Open the Actor and click Try for free.
2. Select an analysis mode.
3. Choose a category or leave it empty for the full marketplace.
4. Enter a search phrase or category, or leave both empty for broad market research.
5. Start with maxWorkflows: 100 for a quick validation run.
6. Enable ML data only when you need the additional training files.
7. Open the Output tab for workflows and the report links.

For a complete marketplace snapshot, use maxWorkflows: 15000. The Actor stops automatically when the n8n API reports that no more workflows are available. Checkpoint recovery applies to scrape_only and scrape_and_analyze; ML generation intentionally rebuilds its complete training set in one run.

from apify_client import ApifyClient

client = ApifyClient("YOUR_API_TOKEN")
run = client.actor("scraper_guru/n8n-marketplace-analyzer").call(run_input={
    "mode": "scrape_and_analyze",
    "maxWorkflows": 100,
    "category": "AI",
    "searchQuery": "AI agent"
})
analysis = client.key_value_store(run["defaultKeyValueStoreId"]).get_record("analysis")

Pricing

This Actor uses pay-per-event pricing, so platform usage is included. You pay for each workflow saved to the default dataset, plus a tiny start charge of $0.00005 per run. The analysis report, charts data and ML files add no extra charges.

Examples on the Free plan: the default 100-workflow run costs about $0.30; a complete marketplace snapshot (around 15,000 workflows) costs about $45. Use searchQuery or category to collect only the slice you need. Apify shows the exact plan-adjusted price before each run.

FAQ

Does this download executable n8n workflow JSON?
It collects the public metadata returned by the n8n marketplace search API. Availability of full workflow definitions depends on the source response.

Where is the analysis report?
Open the analysis record from the Actor Output or key-value store.

Why is the category list limited?
The input exposes common marketplace categories. Leave it empty to collect all categories and filter the dataset afterward.

Can I search for a specific app or use case?
Yes. Use searchQuery for terms such as Slack, HubSpot, RAG, or lead generation. Combine it with a category when you need a narrower dataset.

When should I enable ML training data?
Enable it only when you need prompt-response examples derived from sufficiently detailed workflow descriptions.

Can I schedule market snapshots?
Yes. Save the input as an Apify Task and run it on a weekly or monthly schedule.

For API changes or incorrect marketplace fields, open the Issues tab on this Actor.

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