Workflow Templates

This n8n workflow template uses community nodes and is only compatible with the self-hosted version of n8n. Title: n8n Credentials and Workflows Backup on Change Detection Purpose: Never lose track of your n8n changes again! This workflow smartly backs up all your workflows and credentials, automatically detects any changes using hash comparison, and pushes updates to GitHub—but only when something has actually changed. Set your own interval and stop cluttering your repo with redundant commits. Walkthrough Video on YouTube Trigger: Schedule Trigger**: Executes the entire process at a user-defined interval. No need to worry about traceability or managing countless backups, as the workflow only commits changes when a difference is detected. Workflow Backup Process: Set Workflow Path: Defines the local backup file path for workflows. Get Old Workflow Hash: Executes a helper workflow to retrieve the previous hash. Execute Workflow Backup: Runs n8n export:workflow to export all workflows to the defined file path. Get New Workflow Hash: Executes a helper workflow to generate the new hash from the exported file. Compare Hashes (If Workflow Updated): Checks if the new hash differs from the old one. If Updated: Read Workflow Data → Extract Text → Push to GitHub: Reads, extracts, and commits the updated workflow JSON to GitHub under a timestamped filename. Credential Backup Process: Set Credential Path: Defines the local backup file path for credentials. Get Old Credential Hash: Executes a helper workflow to retrieve the previous hash. Execute Credential Backup: Runs n8n export:credentials to export all credentials. Get New Credential Hash: Executes a helper workflow to generate the new hash from the exported file. Compare Hashes (If Credential Updated): Checks for changes. If Updated: Read Credential Data → Extract Text → Push to GitHub: Commits the new credentials JSON to GitHub if changes are found. Hash Generator (Helper Flow): Used in both workflow and credential backup paths: Read File* → *Extract Text* → *Hash Data** Outputs SHA-256 hash used for comparison GitHub Integration: Commits are created with ISO timestamp in the filename and message. Repository: https://github.com/your-github-name/n8n-onchange-bachup File paths: backups/WorkFlow Backup -timestamp-.json and backups/Credential Backup -timestamp-.json Change Detection Logic: Only commits files when hash changes are detected (i.e., actual content change). Avoids unnecessary GitHub commits and storage use. Error Handling: GitHub nodes are set to continue workflow execution on error, avoiding full process interruption.

Overview The n8n Workflow Cloner is a powerful automation tool designed to copy, sync, and migrate workflows across different n8n instances or projects. Whether you're managing multiple environments (development, staging, production) or organizing workflows within a team, this workflow automates the transfer process, ensuring seamless workflow deployment with minimal manual effort. By automatically detecting and copying only the missing workflows, this tool helps maintain consistency, improve collaboration, and streamline workflow migration between projects or instances. How to Use 1️⃣ Set Up API Credentials Configure API credentials for both source and destination n8n instances. Ensure the credentials have read and write access to manage workflows. 2️⃣ Select Source & Destination Update the "GET - Workflows" node to define the source instance. Set the "CREATE - Workflow" node to specify the destination instance. 3️⃣ Run the Workflow Click "Test Workflow" to start the transfer. The system will fetch all workflows from the source, compare them with the destination, and copy any missing workflows. 4️⃣ Change the Destination Project (Optional) By default, workflows are moved to the "KBB Workflows" project. Modify the "Filter" node to transfer workflows to a different project. 5️⃣ Monitor & Verify The Loop Over Items node ensures batch processing for multiple workflows. Log outputs provide details on transferred workflows and statuses. Key Benefits ✅ Automate Workflow Transfers – No more manual exports/imports. ✅ Sync Workflows Across Environments – Keep workflows up to date in dev, staging, and production. ✅ Effortless Team Collaboration – Share workflows across projects seamlessly. ✅ Backup & Migration Ready – Easily move workflows between n8n instances. Use Cases 🔹 CI/CD for Workflows – Deploy workflows between development and production environments. 🔹 Team Workflow Sharing – Share workflows across multiple n8n projects. 🔹 Workflow Backup Solution – Store copies of workflows in a dedicated backup project. Tags 🚀 Workflow Migration 🚀 n8n Automation 🚀 Sync Workflows 🚀 Backup & Deployment

Paul Graham Essay Search & Chat with Milvus Vector Database How It Works This workflow creates a RAG (Retrieval-Augmented Generation) system using Milvus vector database to search Paul Graham essays: Scrape & Load: Fetches Paul Graham essays, extracts text, and stores them as vector embeddings in Milvus Chat Interface: Enables semantic search and AI-powered conversations about the essays Set Up Steps Set up Milvus server following the official installation guide, then create a collection Execute the workflow to scrape essays and load them into your Milvus collection Chat with the AI agent using the Milvus tool to query and discuss essay content

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

This workflow automates currency rate uploads into SAP Business One via Service Layer, using flexible input sources such as JSON (API), SQL Server, Google Sheets, or manual values. It leverages logic branching, AI validation, and logging for complete control and traceability. ++⚙️ HOW IT WORKS:++ 🔹 1. Receive Data via Webhook The workflow listens on the endpoint /formulario-datos via HTTP POST. The request body should include: origen: one of JSON, SQL, GoogleSheets, or Manual Depending on the value, the flow branches accordingly. 🔹 2. Authenticate with SAP Business One A POST request is sent to SAP B1’s Login endpoint. A session cookie (B1SESSION) is retrieved and used in all subsequent API calls. 🔹 3. Switch by Origin The flow branches into four processing paths based on origen: JSON: The payload is normalized using OpenAI to extract an array of rates. Each rate is sent to SAP individually after parsing. SQL: The SQL query provided in the payload is executed on a connected Microsoft SQL Server. The results are checked by AI to validate the date format. If valid, rates are sent to SAP. GoogleSheets: Rates are pulled from a connected spreadsheet. Each entry is sent to SAP in sequence. Manual: Uses currency, rate, and rateDate directly from the webhook payload. Sends the result directly to SAP. 🔹 4. AI-Powered Enhancements (Optional but enabled) Normalize JSON: Uses OpenAI (LangChain node) to convert any messy structure into a uniform array under the key rate. Date Formatting: Another OpenAI call ensures RateDate is in yyyyMMdd format (required by SAP), converting from ISO, timestamp, or other formats. 🔹 5. Send to SAP Business One (Service Layer) All paths send a POST request to: /SBOBobService_SetCurrencyRate With a payload such as: { "Currency": "USD", "Rate": "0.92", "RateDate": "20250612" } 🔹 6. Log Results All success/failure results are appended to a Google Sheets log (LOGS_N8N) The log includes method, URL, sent payload, status code, and message. ++🛠 SETUP STEPS:++ 1️⃣ Create Required Credentials: Go to Credentials > + New Credential and configure: SAP Business One (Service Layer) Type: HTTP Request Auth or Token Base URL: https://<your-host>:50000/b1s/v1/ Provide Username, Password, and CompanyDB via variables or fields Google Sheets OAuth2 connection to a Google account with access Microsoft SQL Server SQL login credentials and host OpenAI API key with access to models like GPT-4o 2️⃣ Environment Variables (Recommended) Set these variables in n8n → Settings → Variables: SAP_URL=https://<host>:50000/b1s/v1/ SAP_USER=your_username SAP_PASSWORD=your_password SAP_COMPANY_DB=your_companyDB 3️⃣ Prepare Google Sheets Sheet 1: RATE (for charging the data) Columns: Currency, Rate, RateDate Sheet 2: LOGS_N8N (to save the logs, success or failed) Columns: workflow, method, url, json, status_code, message 4️⃣ Activate and Test Deploy the webhook and grab the URL. ++✅ BONUS++ Built-in AI assistance for input validation and structure Logs all results for compliance and audit Flexible integration paths: perfect for hybrid or transitional systems

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

Using PostBin to Test Webhooks Without Changing WEBHOOK_URL How it Works Many new n8n users struggle with testing webhooks when running n8n on localhost, as external services cannot reach localhost. This workflow introduces a technique using PostBin, which provides a temporary, publicly accessible URL to receive webhook requests. Generates a temporary webhook endpoint via PostBin. Uses this endpoint in place of localhost to test webhooks. Captures and displays the incoming webhook request data. Enables debugging and iterating without modifying the WEBHOOK_URL environment variable. Set Up Steps Estimated time:** ~5–10 minutes Create a PostBin instance to generate a publicly accessible webhook URL. Copy the PostBin URL and use it as the webhook destination in n8n. Trigger the webhook from an external service or manually. Inspect the request payload in PostBin to verify data reception. (EXAMPLE) Using PostBin for Webhook Testing in a BambooHR Integration How it Works In this example, we apply the PostBin technique to a BambooHR integration. Instead of manually configuring a webhook in BambooHR, this workflow automates webhook registration using the BambooHR API. The workflow: Uses the BambooHR API to programmatically register the PostBin URL as a webhook. Retrieves the most recent webhook calls made by BambooHR to the PostBin URL. (Optional) Sends a personalized Slack message for new employees using OpenAI. Set Up Steps Estimated time:** ~15–20 minutes Set up PostBin using the steps from the first section. Log into BambooHR to generate an API key for authentication. Run the workflow to register the PostBin URL as a webhook in BambooHR via the API. Retrieve recent webhook calls from PostBin to validate data reception. (Optional) Send a Slack notification using the processed data.

💡🌐 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.

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.