Workflow Templates

This n8n workflow helps eCommerce businesses (especially in the Cash on Delivery space) send real-time order events to the Meta (Facebook) Conversions API, ensuring accurate event tracking and better ad attribution. Features Webhook Listener**: Accepts incoming order data (name, phone, IP, user-agent, etc.) via HTTP POST/GET. Data Normalization**: Cleans and formats first_name, last_name, phone, and event_time according to Facebook's strict specs. Data Hashing**: Securely hashes sensitive user data (SHA256), as required by Meta. Full Custom Data Suppor**t: Pass order value, currency, and more. Ideal For: Shopify, WooCommerce, custom stores (Laravel, Node, etc.) Businesses using Meta Ads and needing high-quality server-side tracking Teams without access to full dev resources, but using n8n for automation How It Works: Receive Order from your store via Webhook or API. Format & Normalize fields to match Facebook’s expected structure. Encrypt Sensitive Fields using SHA256 (name, phone, email). Send to Facebook via the Conversions API endpoint. Requirements: A Meta Business Manager account with Conversions API access Your Access Token and Pixel ID set up in n8n credentials

Disclaimer The Execute Command node is only supported on self-hosted (local) instances of n8n. Introduction KOKORO TTS - Kokoro TTS is a compact yet powerful text-to-speech model, currently available on Hugging Face and GitHub. Despite its modest size—trained on less than 100 hours of audio—it delivers impressive results, consistently topping the TTS leaderboard on Hugging Face. Unlike larger systems, Kokoro TTS offers the advantage of running locally, even on devices without GPUs, making it accessible for a wide range of users. Who will benefit from this integration? This will be useful for video bloggers, TikTokers, and it will also enable the creation of a free voice chat bot. Currently, TTS models are mostly paid, but this integration will allow for fully free voice generation. The possibilities are limited only by your imagination. Note Unfortunately, we can't interact with the KOKORO API via browser URL (GET/POST), but we can run a Python script through n8n and pass any variables to it. In the tutorial, the D drive is used, but you can rewrite this for any paths, including the C drive. Step 1 You need to have Python installed. link Also, download and extract the portable version of KOKORO from GitHub. Create a file named voicegen.py with the following code in the KOKORO folder: (C:\KOKORO). As you can see, the output path is: (D:\output.mp3). import sys import shutil from gradio_client import Client Set UTF-8 encoding for stdout sys.stdout.reconfigure(encoding='utf-8') Get arguments from command line text = sys.argv[1] # First argument: input text voice = sys.argv[2] # Second argument: voice speed = float(sys.argv[3]) # Third argument: speed (converted to float) print(f"Received text: {text}") print(f"Voice: {voice}") print(f"Speed: {speed}") Connect to local Gradio server client = Client("http://localhost:7860/") Generate speech using the API result = client.predict( text=text, voice=voice, speed=speed, api_name="/generate_speech" ) Define output path output_path = r"D:\output.mp3" Move the generated file shutil.move(result[1], output_path) Print output path print(output_path) Step 2 Go to n8n and create the following workflow. Step 3 Edit Field Module. { "voice": "af_sarah", "text": "Hello world!" } Step 4 We’ll need an Execute Command module with the command: python C:\KOKORO\voicegen.py “{{ $json.text }}” “{{ $json.voice }}” 1 Step 5 The script is already working, but to listen to it, you can connect a Binary module with the path to the generated MP3 file D:/output.mp3 Step 6 Click “Text workflow” and enjoy the result. There are more voices and accents than in ChatGPT, plus it’s free. P.S. If you want, there is a detailed tutorial on my blog.

Webhook to report through Mailgun phishing websites to Steam and CloudFlare (if the domain is on CloudFlare) You have to set the Credentials for webhook and Mailgun. You have to set the email from for Mailgun. This assumes it is running in n8n's Docker image where bind-tools is not readily available but installable.

Automate Actions After PDF Generation with PDFMonkey in n8n Overview This n8n workflow template allows you to automatically react to PDF generation events from PDFMonkey. When a new PDF is successfully created, this workflow retrieves the file and processes it based on your needs—whether it’s sending it via email, saving it to cloud storage, or integrating it with other apps. How It Works Trigger: The workflow listens for a PDFMonkey webhook event when a new PDF is generated. Retrieve PDF: It fetches the newly generated PDF file from PDFMonkey. Process & Action: Depending on the outcome: ✅ On success: The workflow downloads the PDF and can distribute or store it. ❌ On failure: It handles errors accordingly (e.g., sending alerts, retrying, or logging the issue). Configuration To set up this workflow, follow these steps: Copy the Webhook URL generated by n8n. Go to your PDFMonkey Webhooks dashboard and paste the URL in the appropriate field to define the callback URL. Save your settings and trigger a test to ensure proper integration. 📖 For detailed setup instructions, visit: PDFMonkey Webhooks Documentation Use Cases This workflow is ideal for: Automating invoice processing (e.g., sending PDFs to customers via email). Archiving reports** in cloud storage (e.g., Google Drive, Dropbox, or AWS S3). Sending notifications** via Slack, Microsoft Teams, or WhatsApp when a new PDF is available. Logging generated PDFs** in Airtable, Notion, or a database for tracking. Customization You can customize this workflow to: Add conditional logic** (e.g., different actions based on the document type). Enhance security** (e.g., encrypting PDFs before sharing). Extend integrations** by connecting with CRM tools, task managers, or analytics platforms. Need Help? If you need assistance setting up or customizing this workflow, feel free to reach out to us via chat on pdfmonkey.io—we’ll be happy to help! 🚀

This workflow allows you to store the output of a phantom in Airtable. This workflow uses the LinkedIn Profile Scraper phantom. Configure and launch this phantom from your Phantombuster account before executing the workflow. The workflow uses the following node: Phantombuster node: The Phantombuster node gets the output of the LinkedIn Profile Scraper phantom that ran earlier. You can select a different phantom from the Agent dropdown list, but make sure to configure the workflow accordingly. Set node: Using the Set node we are setting the data for the workflow. The data that we set in this node will be used by the next nodes in the workflow. Based on your use-case, you can modify the node. Airtable node: The Airtable node allows us to append the data in an Airtable. Based on your use-case you can replace this node with any other node. Instead of storing the data in Airtable, you can store the data in a database or Google Sheet, or send it as an email using the Send Email node, Gmail node, or Microsoft Outlook node.

Instructions This automation overlays a background image with another image, making it easy to add watermarks or logos. You can use this automation to watermark your images by overlaying them with a transparent version of your logo. If you'd like to place your logo in a specific corner, feel free to adjust the position of the overlay image in the code node. How it Works Both images are downloaded, so we can process binary files (you can modify the source, tho.) We extract metadata, focusing on the dimensions of each image. The position of the overlay image is calculated (default: dead center of the background image). The two images are composited together. Limitations and Optimisation Opportunities The overlay image must be the same size or smaller than the background image for proper alignment. The overlay image does not automatically scale to match the proportions of the background image. Enjoy the workflow! ❤️ let the work flow — Workflow Automation & Development

Who this template is for This template is for developers or teams who need to convert CSV data into JSON format through an API endpoint, with support for both file uploads and raw CSV text input. Use case Converting CSV files or raw CSV text data into JSON format via a webhook endpoint, with error handling and notifications. This is particularly useful when you need to transform CSV data into JSON as part of a larger automation or integration process. How this workflow works Receives POST requests through a webhook endpoint at /tool/csv-to-json Uses a Switch node to handle different input types: File uploads (binary data) Plain text CSV data JSON format data Processes the CSV data: For files: Uses the Extract From File node For raw text: Converts the text to CSV using a custom Code node that handles both comma and semicolon delimiters Aggregates the processed data and returns: Success response (200): Converted JSON data Error response (500): Error message with details In case of errors, sends notifications to a Slack error channel with execution details and a link to debug Set up steps Configure the webhook endpoint by deploying the workflow Set up Slack integration for error notifications: Update the Slack channel ID (currently set to "C0832GBAEN4") Configure OAuth2 authentication for Slack Test the endpoint using either: CURL for file uploads: bash Copy curl -X POST "https://yoururl.com/webhook-test/tool/csv-to-json" \ -H "Content-Type: text/csv" \ --data-binary @path/to/your/file.csv Or send raw CSV data as text/plain content type

💡🌐 Essential Multipage Website Scraper with Jina.ai Use responsibly and follow local rules and regulations This N8N workflow enables automated multi-page website scraping using Jina.ai's powerful web scraping capabilities, with seamless integration to Google Drive for content storage. Here's how it works: Main Features The workflow automatically scrapes multiple pages from a website's sitemap and saves each page's content as a separate Google Drive document. Key Components Input Configuration Starts with a sitemap URL (default: https://ai.pydantic.dev/sitemap.xml)** Processes the sitemap to extract individual page URLs Includes filtering options to target specific topics or pages Scraping Process Uses Jina.ai's web scraper to extract content from each URL Converts webpage content into clean markdown format Extracts page titles automatically for document naming Storage Integration Creates individual Google Drive documents for each scraped page Names documents using the format "URL - Page Title" Saves content in markdown format for better readability Usage Instructions Set your target website's sitemap URL in the "Set Website URL" node Configure the "Filter By Topics or Pages" node to select specific content Adjust the "Limit" node (default: 20 pages) to control batch size Connect your Google Drive account Run the workflow to begin automated scraping Additional Features Built-in rate limiting through the Wait node to prevent overloading servers Batch processing capability for handling large sitemaps The workflow requires no API key for Jina.ai, making it accessible for immediate use while maintaining responsible scraping practices.

Este workflow es para trabajar con tratamiento de texto usando n8n y poder iniciarte en como funciona. How To, Paso a Paso: https://comunidad-n8n.com/tratamiento-de-textos/ Comunidad de telegram: https://t.me/comunidadn8n

This workflow allows you to insert and retrieve data from a table in Stackby. Set node: The Set node is used to set the values for the name and id fields for a new record. You might want to add data from an external source, for example an API or a CRM. Based on your use-case, add the respective node before the Set node and configure your Set node accordingly. Stackby node: This node appends data from the previous node to a table in Stackby. Based on the values you want add to your table, enter the column names in the Column field. Stackby1 node: This node fetches all the data that is stored in the table in Stackby.

What problem does this solve? It fetches LinkedIn profiles for a multitude of purposes based on a keyword and location via Google search and stores them in an Excel file for download and in a NocoDB database. It tries to avoid using costly services and should be n8n beginner friendly. It uses the serpapi.com to avoid being blocked by Google Search and to process the data in an easier way. What does it do? Based on criteria input, it searches LinkedIn profiles It discards unnecessary data and turns the follower count into a real number The output is provided as an Excel table for download and in a NocoDB database How does it do it? Based on criteria input, it uses serpAPI.com to conduct Google search of the respective LinkedI profiles With OpenAI.com the name of the respective company is being added With OpenAI.com the follower number e.g., 300+ is turned into a real number: 300 All unnecessary metadata is being discarded As an output an Excel file is being created The output is stored in a nocodb.com table Step-by-step instruction Import the Workflow: Copy the workflow JSON from the "Template Code" section below. Import it into n8n via "Import from File" or "Import from URL". Set up a free account at serpapi.com and get API credentials to enable good Google search results Set up an API account at openai.com and get API key Set up a nocodb.com account (or self-host) and get the API credentials Create the credentials for serpapi.com, opemnai.com and nocodb.com in n8n. Set up a table in NocoDB with the fields indicated in the note above the NocoDB node Follow the instructions as detailed in the notes above individual nodes When the workflow is finished, open the Excel node and click download if you need the Excel file

Disclaimer This template only works on n8n local instances! How it Works This workflow allows you to to receive webhooks from the public web and have your local workflow catch them, without any remote proxy. It is very useful for running quick tests without exposing your dev server. All you have to do is activate the workflow and use the public address as defined below. Set up steps If you use the default key-value storage, there are only three steps: Install the @horka.tv/n8n-nodes-storage-kv community node Put your n8n workflow address in Local Webhook Address Activate the workflow and, from Executions, note down your public webhook token from the inputs to Get Latest Requests. You can now use https://webhook.site/[YOUR TOKEN] as a webhook destination, to receive webhook requests from the public web.