Workflow Templates

This workflow allows you to trigger a build in Travis CI when code changes are pushed to a GitHub repo or a pull request gets opened. GitHub Trigger node: This node will trigger the workflow when changes are pushed or when a pull request is created, updated, or deleted. IF node: This node checks for the action type. We want to trigger a build when code changes are pushed or when a pull request is opened. We don't want to build the project when a PR is closed or updated. TravisCI node: This node will trigger the build in Travis CI. If you're using CircleCI in your pipeline, replace the node with the CircleCI node. NoOp node: Adding this node is optional.

Do you want to avoid bounces in your Email Marketing campaigns? This workflow verifies emails using the uProc.io email verifier. You need to add your credentials (Email and API Key - real -) located at Integration section to n8n. Node "Create Email Item" can be replaced by any other supported service with email value, like Mailchimp, Calendly, MySQL, or Typeform. The "uProc" node returns a status per checked email (deliverable, undeliverable, spamtrap, softbounce,...). "If" node checks if "deliverable" status exists. If value is not present, you can mark email as invalid to discard bounces. If "deliverable" status is present, you can use email in your Email Marketing campaigns. If you need to know detailed indicators of any email, you can use the tool "Communication" > "Check Email Exists (Extended)" to get advanced information.

This workflow enables seamless, bidirectional communication between WhatsApp and Slack using n8n. It automates the reception, processing, and forwarding of messages (text, media, and documents) between users on WhatsApp and private Slack channels. Key Features & Flow: 1. WhatsApp to Slack Flow Trigger: The workflow starts with a WhatsApp Trigger node that listens for new incoming messages via a webhook. Channel Handling: It checks if a Slack channel with the WhatsApp sender’s number exists If not, it creates a private Slack channel with the sender's number as the name. Message Type Routing: A Switch Node (Message Type) inspects the message type (text, image, audio, document). Based on type: Text: Sends the message directly to Slack. Image/Audio/Document: Retrieves media URL via WhatsApp API → downloads the media → uploads it to the appropriate Slack channel. 2. Slack to WhatsApp Flow Trigger: A Slack Trigger listens for new messages or file uploads in Slack. Message Type Routing: A second Switch Node (Checking Message Type) checks if the message is text or media. Routing Logic: Text Message: Extracts and forwards it to the WhatsApp contact (identified by the Slack channel name). Media/File Message: Retrieves media file URL from Slack → downloads it → sends it as a document via WhatsApp API. Key Integrations: WhatsApp Cloud API: For receiving messages, downloading media, and sending messages. Slack API: For creating/getting channels, posting messages, and uploading files. HTTP Request Node: Used to securely download media from Slack and WhatsApp servers with proper authentication. Automation Use Case: This workflow is ideal for businesses that handle customer support or conversations over WhatsApp and wish to log, respond, and collaborate using Slack as their internal communication tool.

This workflow allows you to send position updates of the ISS every minute to a table in Google BigQuery. Cron node: The Cron node will trigger the workflow every minute. HTTP Request node: This node will make a GET request to the API https://api.wheretheiss.at/v1/satellites/25544/positions to fetch the position of the ISS. This information gets passed on to the next node in the workflow. Set node: We will use the Set node to ensure that only the data that we set in this node gets passed on to the next nodes in the workflow. Google BigQuery: This node will send the data from the previous node to the position table in Google BigQuery. If you have created a table with a different name, use that table instead.

This workflow is a supporting automation to a common Airtable situation, that as of this writing, has no direct solution but has great demand. Interfaces are your secret weapon for managing a variety of tasks – from sales funnels and task tracking to creating dynamic dashboards. But here's a common situation: how do you efficiently bulk upload records (like contacts, leads, or clients) from an interface with just a click? Once set up, you'll be able to upload CSV files directly to your tables from the Interfaces with ease. Workflow Key Points: 1. Bulk Upload Functionality: Say goodbye to the limitations of standard Airtable interfaces. Now, you can upload multiple leads or contacts simultaneously, making your work swift and efficient. 2. Customizable Fields: Tailor the base to meet your specific data needs. This ensures seamless integration with your existing systems and simplifies data management. ​ Perfect for teams in e-commerce, CRM, or any sector where managing a high volume of leads or contacts is key. Our Airtable Base is designed to eliminate the tediousness of importing contacts. It makes large-scale data management straightforward, saving you precious time and hassle. ​ Get ready to streamline your operations and boost your productivity! 🚀💡

🚀 LinkedIn Video to MP4 Automation with Google Drive & Sheets | RapidAPI Integration This n8n workflow automatically converts LinkedIn video URLs into downloadable MP4 files using the LinkedIn Video Downloader API, uploads them to Google Drive with public access, and logs both the original URL and Google Drive link into Google Sheets. It leverages the LinkedIn Video Downloader service for fast and secure video extraction. 📝 Node Explanations (Single-Line) 1️⃣ On form submission → Captures LinkedIn video URL from the user via a web form. 2️⃣ HTTP Request → Calls LinkedIn Video Downloader to fetch downloadable MP4 links. 3️⃣ If → Checks for API errors and routes workflow accordingly. 4️⃣ Download mp4 → Downloads the MP4 video file from the API response URL. 5️⃣ Upload To Google Drive → Uploads the downloaded MP4 file to Google Drive. 6️⃣ Google Drive Set Permission → Makes the uploaded file publicly accessible. 7️⃣ Google Sheets → Logs successful conversions with LinkedIn URL and sharable Drive link. 8️⃣ Wait → Delays execution before logging failed attempts. 9️⃣ Google Sheets Append Row → Logs failed video downloads with N/A Drive link. 📄 Google Sheets Columns URL** → Original LinkedIn video URL entered in the form. Drive_URL** → Publicly sharable Google Drive link to the converted MP4 file. (For failed downloads) → Drive_URL will display N/A. 💡 Use Case Automate LinkedIn video downloading and sharing using LinkedIn Video Downloader for social media managers, marketers, and content creators without manual file handling. ✅ Benefits Time-saving* (auto-download & upload), *Centralized tracking* in Sheets, *Easy sharing* via Drive links, and *Error logging* for failed downloads—all powered by *RapidAPI LinkedIn Video Downloader**.

This workflow allows you to compress binary files to zip format. HTTP Request node: The workflow uses the HTTP Request node to fetch files from the internet. If you want to fetch files from your local machine, replace it with the Read Binary File or Read Binary Files node. Compression node: The Compression node compresses the file into a zip. If you want to compress the files to gzip, then select the gzip format instead. Based on your use-case, you may want to write the files to your disk or upload it to Google Drive or Box. If you want to write the compressed file to your disk, replace the Dropbox node with the Write Binary File node, or if you want to upload the file to a different service, use the respective node.

Overview This workflow automatically converts CSV or Excel files into a production-ready database schema using AI and rule-based validation. It analyzes uploaded data, detects column types, relationships, and data quality, then generates a normalized schema. The output includes SQL DDL scripts, ERD diagrams, a data dictionary, and a load plan. This eliminates manual schema design and accelerates database setup from raw data. How It Works File Upload (Webhook) Accepts CSV or XLSX files via webhook endpoint Initializes workflow configuration (thresholds, retry limits) File Extraction Detects file format (CSV or Excel) Extracts rows into structured JSON Merges extracted datasets Data Cleaning & Profiling Removes duplicates and normalizes values Detects data types (integer, float, date, boolean, string) Computes column statistics (nulls, uniqueness, distributions) Generates file hash and sample dataset Column Profiling Engine Identifies potential primary keys Detects cardinality and uniqueness levels Suggests foreign key relationships based on value overlap AI Schema Generation Uses an AI agent to design normalized tables Assigns SQL data types based on real data Defines primary keys, foreign keys, constraints, and indexes Validation Layer Ensures schema matches actual data Validates: Data types Primary key uniqueness Foreign key overlap (>70%) Constraint consistency Detects circular dependencies Revision Loop If validation fails: Sends feedback to AI agent Regenerates schema Retries up to configured limit Schema Output Generation Generates: SQL DDL scripts ERD (Mermaid format) Data dictionary Load plan with dependency graph Load Plan Engine Computes optimal table insertion order Detects circular dependencies Suggests batching strategy Combine & Explain Merges all outputs Optional AI explanation of schema decisions Response Output Returns structured JSON via webhook: SQL schema ERD summary Data dictionary Load plan Optional explanation Setup Instructions Activate the workflow and copy the webhook URL Send a POST request with a CSV or XLSX file Configure OpenAI credentials (used by AI agent) Adjust thresholds if needed (FK overlap, retries, confidence) Execute workflow and review generated outputs Use Cases Auto-generate database schema from CSV/Excel files Data migration and onboarding pipelines Rapid database prototyping Reverse engineering datasets AI-assisted data modeling Requirements n8n (latest version recommended) OpenAI API credentials LangChain nodes enabled CSV or XLSX input file

This workflow connects a USB scanner to Nextcloud via ScanservJS and the integrated API. It checks for new scans at a scheduled time (e.g., every 5 minutes). If there are any, they are automatically retrieved via HTTP request and then saved to a desired Nextcloud folder. Ideal for home offices, offices, or maker projects with Raspberry Pi and network scanners. Nodes used: Schedule Trigger – starts the flow cyclically HTTP Request – retrieves document data from ScanservJS Nextcloud Node – uploads the file directly to your Nextcloud account Requirements: Local installation of ScanservJS (e.g., on a Raspberry Pi) Configured USB scanner Nextcloud access with write permissions in the target folder

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. OAuth Token Generator and Validator This n8n template helps you generate, validate, and store tokens for your customers securely using: n8n** as your backend automation engine Airtable** as your lightweight client and token store 🚀 What It Does Accepts client_id and client_secret via POST webhook. Validates client credentials against Airtable. Generates a long token on success. Stores the generated token in Airtable with metadata. Responds with a JSON containing the token, expiry, and type. Returns clear error messages if validation fails. How It Works Webhook node receives client_id and client_secret. Validator (Code node) checks: Body contains only client_id and client_secret. Rejects missing or extra fields. Airtable search: Looks up the client_id. Rejects if not found. Secret validation (If node): Compares provided client_secret with stored value. Rejects if incorrect. Token generation (Code node): Generates a 128-character secure token. Airtable create: Stores token, client ID, creation date, and type. Webhook response: Returns JSON { access_token, expires_in, token_type } on success. Returns appropriate JSON error messages on failure. Related Workflow You can also use it with the published Bearer Token Validation workflow: 👉 Validate API Requests with Bearer Token Authentication and Airtable to securely validate tokens you generate with this workflow across your protected endpoints. Why Use This Provides OAuth-like flows without a complex backend. Uses n8n + Airtable for client management and token storage. Clean, modular, and ready for your SaaS or internal API automations. Extendable for token expiry, refresh, and rotation handling. Enjoy building secure token-based APIs using n8n + Airtable! 🚀 Built by: Nazmy

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