# The Fastest N8n Templates Scraper (`intelecta/n8n-templates-scraper`) Actor Scrapes and collects n8n.io workflow templates by category and apps. Flexible sorting, structured output, and easy filtering. Perfect for automation experts, developers, and businesses seeking workflow inspiration or analysis. - **URL**: https://apify.com/intelecta/n8n-templates-scraper.md - **Developed by:** [Intelecta.ai](https://apify.com/intelecta) (community) - **Categories:** Agents, Automation, AI - **Stats:** 30 total users, 0 monthly users, 100.0% runs succeeded, 4 bookmarks - **User rating**: 4.00 out of 5 stars ## Pricing $15.00/month + usage To use this Actor, you pay a monthly rental fee to the developer. The rent is subtracted from your prepaid usage every month after the free trial period.You also pay for the Apify platform usage, which gets cheaper the higher Apify subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#rental-actors ## 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 ## n8n Workflow Template Scraper Automatically collect workflow templates from the n8n.io platform, filter by category, and get structured data for analysis or direct import into your n8n instance. Perfect for developers, automation experts, and businesses looking to streamline workflow development or analyze automation trends. ### Features - 🔄 **Automated Collection:** Gathers workflow templates from n8n.io - 🏷️ **Category & Subcategory Filtering:** Filter by main categories and subcategories (see below) - 🔍 **App Filtering:** Filter workflows by apps used - 🔀 **Flexible Sorting:** Sort by relevancy, popularity, or most recent, in ascending or descending order - 📊 **Structured Output:** Clean, organized data in Apify dataset - ⚡ **Fast & Scalable:** Optimized for performance on Apify ### Input Parameters | Parameter | Type | Description | |-------------------|----------|---------------------------------------------------------------------------------------------| | `category` | string | Main category or subcategory to filter workflows (see list below). | | `apps` | array | List of app names to filter by (e.g., `["Google Sheets", "Slack"]`). Leave empty for all. | | `sortBy` | string | Field to sort by: `relevancy` (most relevant), `popularity` (most viewed), `recent` (most recent). | | `sortDirection` | string | Sort direction: `asc` (ascending) or `desc` (descending). | | `max_results` | integer | Maximum number of workflows to collect (default: 500). | ### Categories & Subcategories - **Main categories:** - sales - AI - it ops - marketing - document ops - other - support - **Subcategories:** (examples) - sales: CRM, lead generation, lead nurturing - AI: AI chatbot, AI rag, AI summarization, multimodal AI - it ops: secops, engineering, devops - marketing: content creation, market research, social media - document ops: document extraction, file management, invoice processing - other: crypto trading, HR, miscellaneous, personal productivity, project management - support: internal wiki, support chatbot, ticket management **Example:** ```` sales CRM lead generation lead nurturing AI AI chatbot AI rag AI summarization multimodal AI it ops secops engineering devops marketing content creation market research social media document ops document extraction file management invoice processing other crypto trading HR miscellaneous personal productivity project management support internal wiki support chatbot ticket management ```` ### Example Input ```json { "category": "AI", "apps": ["Google Sheets", "OpenAI"], "sortBy": "relevancy", "sortDirection": "desc", "max_results": 100 } ```` ### Output The collected data is saved to the Apify dataset. The output data includes the following fields: - `id`: Workflow ID - `name`: Workflow name - `totalViews`: Total number of views - `purchaseUrl`: Purchase URL (if available) - `user`: Publisher information: - `id`: User ID - `name`: User name - `username`: System username - `bio`: User biography - `verified`: Whether the user is verified - `links`: User links - `avatar`: Profile picture URL - `description`: Workflow description - `createdAt`: Creation date - `nodes`: Nodes used in the workflow ### Example Output ```json { "id": 6442, "name": "Automated Gmail Reply Drafts with OpenAI Assistant for Labeled Emails", "totalViews": 0, "purchaseUrl": null, "user": { "id": 96776, "name": "Hichul", "username": "melikahichul", "bio": "Water Engineer, learning to integrate AI, ML, DL, NNA into Water Engineering for LMI Countries.", "verified": false, "links": "[\"https://www.youtube.com/@greatcommissionerofking?sub_confirmation=1\"]", "avatar": "https://gravatar.com/avatar/fdb72903c343b1bf682743e9338f65b407909cb5e9d0b76c5077958d41c4873d?r=pg&d=retro&size=200" }, "description": "n8n workflow template description [template]\nThis workflow automatically drafts replies to your emails using an OpenAI Assistant, streamlining your inbox management. ...", "createdAt": "2025-07-25T13:39:00.752Z", "nodes": [ { "id": 19, "icon": "file:httprequest.svg", "name": "n8n-nodes-base.httpRequest", "codex": { "data": { "alias": ["API", "Request", "URL", "Build", "cURL"], ... } }, "group": "[\"output\"]", "defaults": { "name": "HTTP Request", "color": "#0004F5" }, "iconData": { "type": "file", "fileBuffer": "data:image/svg+xml;base64,..." }, "displayName": "HTTP Request", "typeVersion": 4, "nodeCategories": [ { "id": 5, "name": "Development" }, { "id": 9, "name": "Core Nodes" } ] } // ...more nodes ] } ``` ### Usage 1. Deploy and run the actor in the Apify console. 2. Provide your input parameters (see above). 3. The actor will collect and store workflow templates in the default Apify dataset. 4. Download or analyze the results as needed. ### Notes - The actor does **not** require authentication for n8n.io. - For best results, use specific categories and app filters. - All data is saved in a structured format for easy import or analysis. *** **Need help?** [Contact Apify Support](https://help.apify.com/) or visit the [n8n documentation](https://docs.n8n.io/). # Actor input Schema ## `category` (type: `string`): The category to filter n8n workflows by (e.g., 'AI', 'CRM', etc.). ## `apps` (type: `array`): A list of app names to filter workflows (e.g., \['Google Sheets', 'Google Drive', 'Gmail', 'OpenAI', 'Telegram', 'Discord', 'Slack']). Leave empty to include all apps. ## `sortBy` (type: `string`): Sort by: 'Relevancy' (most relevant), 'Popularity' (most viewed), 'Recent' (most recent). ## `sortDirection` (type: `string`): Sort direction: 'asc' for ascending, 'desc' for descending. ## `max_results` (type: `integer`): The maximum number of workflows to return. Default is 500. ## Actor input object example ```json { "category": "AI", "apps": [ "Google Sheets", "Google Drive", "Gmail", "OpenAI", "Telegram", "Discord", "Slack" ], "sortBy": "relevancy", "sortDirection": "desc", "max_results": 500 } ``` # 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 = { "category": "AI", "apps": [ "Google Sheets", "Google Drive", "Gmail", "OpenAI", "Telegram", "Discord", "Slack" ], "sortBy": "relevancy", "sortDirection": "desc" }; // Run the Actor and wait for it to finish const run = await client.actor("intelecta/n8n-templates-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 = { "category": "AI", "apps": [ "Google Sheets", "Google Drive", "Gmail", "OpenAI", "Telegram", "Discord", "Slack", ], "sortBy": "relevancy", "sortDirection": "desc", } # Run the Actor and wait for it to finish run = client.actor("intelecta/n8n-templates-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 '{ "category": "AI", "apps": [ "Google Sheets", "Google Drive", "Gmail", "OpenAI", "Telegram", "Discord", "Slack" ], "sortBy": "relevancy", "sortDirection": "desc" }' | apify call intelecta/n8n-templates-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=intelecta/n8n-templates-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "The Fastest N8n Templates Scraper", "description": "Scrapes and collects n8n.io workflow templates by category and apps. Flexible sorting, structured output, and easy filtering. Perfect for automation experts, developers, and businesses seeking workflow inspiration or analysis.", "version": "0.1", "x-build-id": "Xfx1QB52pTD0o0KZw" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/intelecta~n8n-templates-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-intelecta-n8n-templates-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/intelecta~n8n-templates-scraper/runs": { "post": { "operationId": "runs-sync-intelecta-n8n-templates-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/intelecta~n8n-templates-scraper/run-sync": { "post": { "operationId": "run-sync-intelecta-n8n-templates-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": [ "category", "apps" ], "properties": { "category": { "title": "Workflow Category", "enum": [ "Sales", "CRM", "Lead Generation", "Lead Nurturing", "AI", "AI Chatbot", "AI Rag", "AI Summarization", "Multimodal AI", "IT Ops", "SecOps", "Engineering", "DevOps", "Marketing", "Content Creation", "Market Research", "Social Media", "Document Ops", "Document Extraction", "File Management", "Invoice Processing", "Other", "Crypto Trading", "HR", "Miscellaneous", "Personal Productivity", "Project Management", "Support", "Internal Wiki", "Support Chatbot", "Ticket Management" ], "type": "string", "description": "The category to filter n8n workflows by (e.g., 'AI', 'CRM', etc.)." }, "apps": { "title": "Apps to Filter By", "type": "array", "description": "A list of app names to filter workflows (e.g., ['Google Sheets', 'Google Drive', 'Gmail', 'OpenAI', 'Telegram', 'Discord', 'Slack']). Leave empty to include all apps.", "items": { "type": "string" } }, "sortBy": { "title": "Sort Workflows By", "enum": [ "relevancy", "popularity", "recent" ], "type": "string", "description": "Sort by: 'Relevancy' (most relevant), 'Popularity' (most viewed), 'Recent' (most recent)." }, "sortDirection": { "title": "Sort Direction", "enum": [ "asc", "desc" ], "type": "string", "description": "Sort direction: 'asc' for ascending, 'desc' for descending." }, "max_results": { "title": "Maximum Number of Results", "type": "integer", "description": "The maximum number of workflows to return. Default is 500.", "default": 500 } } }, "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 } } } } } } } } } } ```