Workflow Templates

This n8n workflow captures Partnerstack events via a webhook, logs the event data into a Google Sheet, and sends a Telegram notification. How it Works: Webhook Node (Trigger): Listens for incoming POST requests. When an event occurs in Partnerstack (e.g., a new referral signs up), the workflow is triggered, capturing the event data. Append Row in Sheets Node: Takes the received Partnerstack event data and appends it as a new row to a designated Google Sheet. This creates a historical log of all captured events. Set Chat ID Node: Defines the specific Telegram chat ID where notifications will be sent. Send Notification Node (Telegram): Sends a message to the specified Telegram chat. The message content includes details from the Partnerstack event, providing real-time alerts. Setup Requirements: Partnerstack Postback: Configure a postback in Partnerstack (My account > Postbacks > Create a postback). Paste the URL provided by n8n's **Webhook node. Select the Partnerstack events you wish to track. Google Sheets Authentication**: Provide n8n with Google credentials that have write access to your target Google Sheet. Specify the sheet name. Telegram Integration**: You'll need a Telegram bot token (from BotFather) and the specific chat ID for the destination Telegram chat/channel. Additional Notes: This workflow efficiently automates logging of Partnerstack activities and provides immediate team awareness through Telegram notifications, streamlining event monitoring and response. 👉 Need Help? Feel free to contact us at 1 Node. Get instant access to a library of free resources we created.

Daily Company News Bot This n8n template demonstrates how to use Free FinnHub API to retrieve the company news from a list stock tickers and post messages in Slack channel with a pre-scheduled time. How it works We firstly define the list of stock tickers you are interested Loop over items to call FinnHub API to get the latest company news for the ticker Then we format the company news as a markdown text content which could be sent to Slack Post a new message in Slack channel Wait for 5 seconds, then move to the next ticker How to use Simply setup a scheduler trigger to automatically trigger the workflow Requirements FinnHub API Key Slack channel webhook Need Help? Contact me via My Blog or ask in the Forum! Happy Hacking!

This n8n template allows you to instantly fetch a random dog image from the Dog CEO API by simply sending a webhook request. It's a fun and simple way to integrate random dog photos into your projects, whether for websites, applications, or playful automations. 🔧 How it works Trigger Webhook: This node acts as the entry point for the workflow. It listens for any incoming POST request. No specific data is required in the webhook body, as the workflow fetches a random image. Fetch Random Dog Image: This node makes an HTTP GET request to https://dog.ceo/api/breeds/image/random. The API responds with a JSON object containing the URL of a random dog image. Respond with Image URL: This node sends the URL of the random dog image back to the service that initiated the webhook. 👤 Who is it for? This workflow is ideal for: Developers: Quickly integrate random dog images into web applications, bots, or prototypes. Content Creators: Get fresh, random dog photos for social media, blogs, or presentations. Learning n8n: A straightforward example of using a webhook to trigger an API call and return data. Anyone who loves dogs! 📑 Data Structure When you trigger the webhook, you can send an empty POST request body. The workflow will return a JSON response similar to this (the message URL will vary): { "message": "https://images.dog.ceo/breeds/hound-walker/n02089867_2626.jpg", "status": "success" } ⚙️ Setup Instructions Import Workflow: In your n8n editor, click "Import from JSON" and paste the provided workflow JSON. Configure Webhook Path: Double-click the Trigger Webhook node. In the 'Path' field, set a unique and descriptive path (e.g., /get-dog-image). Activate Workflow: Save and activate the workflow. 📝 Tips Download the Image: Instead of just returning the URL, you can download the image and then process it. Insert another HTTP Request node after Fetch Random Dog Image to download the image binary. Set the HTTP Request node's 'Response Format' to 'Binary'. Use the expression ={{ $json.message }} for the URL. Save to Cloud Storage: After downloading the image (as described above), you can save it to various cloud storage services: Google Drive: Add a Google Drive node. Connect it to the output of the image download node. Configure it to upload the binary data to a specific folder. Amazon S3: Add an AWS S3 node. Configure it to upload the binary data, specifying your bucket and desired filename. Dropbox: Use the Dropbox node to upload the image file. Send as a Message: Share the dog image directly in a chat or email: Slack/Discord/Telegram: Use the respective integration node to send the image URL or the downloaded image as an attachment. Email: Attach the downloaded image to an email using an Email or Gmail node. Display on a Web Page: If you're embedding this into a web application, you can simply use the returned URL in an tag to display the image. Error Handling: You can add an Error Trigger node to catch any issues during the image fetching process (e.g., if the Dog CEO API is down) and send notifications.

Customer Support Analysis Dashboard with AI and Automated Insights 🎯 Target Audience Customer support managers and team leads Customer success teams monitoring satisfaction Product managers analyzing user feedback Business analysts measuring support metrics Operations managers optimizing support processes Quality assurance teams monitoring support quality Customer experience (CX) professionals 🚀 Problem Statement Manual analysis of customer support tickets and feedback is time-consuming and often misses critical patterns or emerging issues. This template solves the challenge of automatically collecting, analyzing, and visualizing customer support data to identify trends, improve response times, and enhance overall customer satisfaction. 🔧 How it Works This workflow automatically monitors customer support channels using AI-powered analysis, processes tickets and feedback, and provides actionable insights for improving customer support operations. Key Components Scheduled Trigger - Runs the workflow at specified intervals to maintain real-time monitoring AI-Powered Ticket Analysis - Uses advanced NLP to categorize, prioritize, and analyze support tickets Multi-Channel Integration - Monitors email, chat, help desk systems, and social media Automated Insights - Generates reports on trends, response times, and satisfaction scores Dashboard Integration - Stores all data in Google Sheets for comprehensive analysis and reporting 📊 Google Sheets Column Specifications The template creates the following columns in your Google Sheets: | Column | Data Type | Description | Example | |--------|-----------|-------------|---------| | timestamp | DateTime | When the ticket was processed | "2024-01-15T10:30:00Z" | | ticket_id | String | Unique ticket identifier | "SUP-2024-001234" | | customer_email | String | Customer contact information | "john@example.com" | | subject | String | Ticket subject line | "Login issues with new app" | | description | String | Full ticket description | "I can't log into the mobile app..." | | category | String | AI-categorized ticket type | "Technical Issue" | | priority | String | Calculated priority level | "High" | | sentiment_score | Number | Customer sentiment (-1 to 1) | -0.3 | | urgency_indicator | String | Urgency classification | "Immediate" | | response_time | Number | Time to first response (hours) | 2.5 | | resolution_time | Number | Time to resolution (hours) | 8.0 | | satisfaction_score | Number | Customer satisfaction rating | 4.2 | | agent_assigned | String | Support agent name | "Sarah Johnson" | | status | String | Current ticket status | "Resolved" | 🛠️ Setup Instructions Estimated setup time: 20-25 minutes Prerequisites n8n instance with community nodes enabled ScrapeGraphAI API account and credentials Google Sheets account with API access Help desk system API access (Zendesk, Freshdesk, etc.) Email service integration (optional) Step-by-Step Configuration 1. Install Community Nodes Install required community nodes npm install n8n-nodes-scrapegraphai npm install n8n-nodes-slack 2. Configure ScrapeGraphAI Credentials Navigate to Credentials in your n8n instance Add new ScrapeGraphAI API credentials Enter your API key from ScrapeGraphAI dashboard Test the connection to ensure it's working 3. Set up Google Sheets Connection Add Google Sheets OAuth2 credentials Grant necessary permissions for spreadsheet access Create a new spreadsheet for customer support analysis Configure the sheet name (default: "Support Analysis") 4. Configure Support System Integration Update the websiteUrl parameters in ScrapeGraphAI nodes Add URLs for your help desk system or support portal Customize the user prompt to extract specific ticket data Set up categories and priority thresholds 5. Set up Notification Channels Configure Slack webhook or API credentials for alerts Set up email service credentials for critical issues Define alert thresholds for different priority levels Test notification delivery 6. Configure Schedule Trigger Set analysis frequency (hourly, daily, etc.) Choose appropriate time zones for your business hours Consider support system rate limits 7. Test and Validate Run the workflow manually to verify all connections Check Google Sheets for proper data formatting Test ticket analysis with sample data 🔄 Workflow Customization Options Modify Analysis Targets Add or remove support channels (email, chat, social media) Change ticket categories and priority criteria Adjust analysis frequency based on ticket volume Extend Analysis Capabilities Add more sophisticated sentiment analysis Implement customer churn prediction models Include agent performance analytics Add automated response suggestions Customize Alert System Set different thresholds for different ticket types Create tiered alert systems (info, warning, critical) Add SLA breach notifications Include trend analysis alerts Output Customization Add data visualization and reporting features Implement support trend charts and graphs Create executive dashboards with key metrics Add customer satisfaction trend analysis 📈 Use Cases Support Ticket Management**: Automatically categorize and prioritize tickets Response Time Optimization**: Identify bottlenecks in support processes Customer Satisfaction Monitoring**: Track and improve satisfaction scores Agent Performance Analysis**: Monitor and improve agent productivity Product Issue Detection**: Identify recurring problems and feature requests SLA Compliance**: Ensure support teams meet service level agreements 🚨 Important Notes Respect support system API rate limits and terms of service Implement appropriate delays between requests to avoid rate limiting Regularly review and update your analysis parameters Monitor API usage to manage costs effectively Keep your credentials secure and rotate them regularly Consider data privacy and GDPR compliance for customer data 🔧 Troubleshooting Common Issues: ScrapeGraphAI connection errors: Verify API key and account status Google Sheets permission errors: Check OAuth2 scope and permissions Ticket parsing errors: Review the Code node's JavaScript logic Rate limiting: Adjust analysis frequency and implement delays Alert delivery failures: Check notification service credentials Support Resources: ScrapeGraphAI documentation and API reference n8n community forums for workflow assistance Google Sheets API documentation for advanced configurations Help desk system API documentation Customer support analytics best practices

❓ What Problem Does It Solve? Manual exporting or copying of leads and newsletter signups from web forms to spreadsheets is time-consuming, error-prone, and delays follow-ups or marketing activities. Traditional workflows can lose data due to mistakes or lack of automation. The Fluentform Export workflow automates the capture and organization of form submissions and newsletter signups into Google Sheets 💡 Why Use this workflow? Save Time:** Automate tedious manual data entry for form leads and newsletter signups Avoid Data Loss:** Ensure all submissions are reliably logged with real-time updates Organized Data:** Separate sheets for newsletter and contact form data maintain clarity Easy Integration:** Works seamlessly with Fluentform submissions and Google Sheets Flexible & Scalable:** Quickly adapt to changes in form structure or spreadsheet columns ⚡ Who Is This For? Marketers & Growth Teams:** Automatically gather leads and newsletter contacts to fuel campaigns Small to Medium Businesses:** Reduce overhead from manual data management and errors Customer Support Teams:** Keep track of form submissions in a centralized, accessible place Website Admins:** Simplify data workflow from Fluentform plugins without coding 🔧 What This Workflow Does ⏱ Trigger:** Listens for incoming POST requests from Fluentform via webhook 📎 Step 2:** Evaluates if the submission is a newsletter signup or a form based on a specific token 🔄 Step 3 (Newsletter Path):** Maps email from newsletter submissions and appends/updates Google Sheets "News Letter" tab 🔄 Step 3 (Form Path):** Extracts full name, email, phone, subject, and message fields and appends/updates the Google Sheets "form" tab 💌 Step 4:** Sends a JSON success response back to Fluentform confirming receipt 🔐 Setup Instructions Import the provided .json workflow file into your n8n instance Set up credentials: Google Sheets OAuth2 credential with access to your target spreadsheets Customize workflow elements: Update Fluentform webhook URL in your Fluentform settings to the n8n webhook URL generated Adjust field names or spreadsheet columns if your form structure changes Update spreadsheet IDs and sheet names used in the Google Sheets nodes to match your own Sheets Test workflow thoroughly with actual Fluentform submissions to verify data flows correctly 🧩 Pre-Requirements Running n8n instance (Cloud or self-hosted) Google account with access to Google Sheets and OAuth credentials Fluentform installed on your website with ability to set webhook URL Target Google Sheets prepared with tabs named "News Letter" and "form" with expected columns 🧠 Nodes Used Webhook (POST - Retrieve Leads) If (Form or newsletter?) Set (newsletter and form data preparation) Google Sheets (Append/update for newsletter and form sheets) Respond to Webhook 📞 Support Made by: khaisa Studio Tag: automation, Google Sheets, Fluentform, Leads Category: Marketing Need a custom? Contact Me

✨ What It Does Mello is a Claude-powered Slack assistant that helps you stay on top of unread messages across all your channels. It: Summarizes conversations contextually using Claude AI. Generates reply suggestions and sends them as private (ephemeral) Slack messages. Lets you respond instantly with one-click AI-suggested replies. Perfect for busy teams, founders, and anyone looking to reduce Slack noise and save hours each week. 🔧 Setup Instructions Create a Slack App Go to Slack API → Your Apps Click Create New App and set it up for your workspace Under OAuth & Permissions, add: Bot Token Scopes: commands, chat:write, channels:history, users:read User Token Scopes: channels:history, chat:write Enable Interactivity, and point the Request URL to your n8n webhook (e.g. /slash-summarize) Add Claude API Get an API key from Claude (Anthropic) In n8n, set up the Claude API credential (or switch to OpenAI) Import This Workflow Go to your n8n instance, click Import, and paste this template Update any placeholders (Slack app, Claude key, webhook URLs) Follow the inline sticky notes for guidance Test It Type /summarize in any Slack channel Mello will fetch unread messages, summarize them, and show reply buttons in a private message ⏱ Setup time: ~10 minutes 🛠 Workflow Highlights Slash command trigger (/summarize) Slack API integration to fetch messages Claude AI for contextual summaries Reply suggestions with smart buttons Private Slack delivery (ephemeral messages) Designed to be easily extended (e.g. add support for OpenAI, custom storage) 🔒 Note This is a lite preview of the full Mello workflow. ✅ The full version includes: Slack reply buttons with thread context Full OAuth flow with token storage MongoDB integration Custom Claude/OpenAI configuration Hosted version with onboarding, branding & support 💡 Want access to the complete version? 📩 Email nina@baloon.dev

✅💬Build Your Own WhatsApp Fact-Checking Bot with AI Tired of misinformation spreading on WhatsApp? 🤨 This workflow transforms your n8n instance into a powerful, automated fact-checking bot\! Send any news, claim, or question to a designated WhatsApp number, and this bot will use AI to research it, provide a verdict, and send back a summary with direct source links. Fight fake news with the power of automation and AI\! 🚀 How it works ⚙️ This workflow uses a simple but powerful three-step process: 📬 WhatsApp Gateway (Webhook node): This is the front door. The workflow starts when the Webhook node receives an incoming message from a user via a Twilio WhatsApp number. 🕵️ The Digital Detective (Perplexity node): The user's message is sent to the Perplexity node. Here, a powerful AI model, instructed by a custom system prompt, analyzes the claim, scours the web for reliable information, and generates a verdict (e.g., ✅ Likely True, ❌ Likely False). 📲 WhatsApp Reply (Twilio node): The final, formatted response, complete with the verdict, a simple summary, and source citations, is sent back to the original user via the Twilio node. Setup Guide 🛠️ Follow these steps carefully to get your fact-checking bot up and running. Prerequisites A Twilio Account with an active phone number or access to the WhatsApp Sandbox. A Perplexity AI Account to get an API key. 1\. Configure Credentials You'll need to add API keys for both Perplexity and Twilio to your n8n instance. Perplexity AI: Go to your Perplexity AI API Settings. Generate and copy your API Key. In n8n, go to Credentials \& New, search for "Perplexity," and add your key. Twilio: Go to your Twilio Console Dashboard. Find and copy your Account SID and Auth Token. In n8n, go to Credentials \& New, search for "Twilio," and add your credentials. 2\. Set Up the Webhook and Tunnel To allow Twilio's cloud service to communicate with your n8n instance, you need a public URL. The n8n tunnel is perfect for this. Start the n8n Tunnel: If you are running n8n locally, you'll need to expose it to the web. Open your terminal and run: n8n start --tunnel Copy Your Webhook URL: Once the tunnel is active, open your n8n workflow. In the Receive Whatsapp Messages (Webhook) node, you will see two URLs: Test and Production. Copy the Test/Production URL. This is the public URL that Twilio will use. 3\. Configure Your Twilio WhatsApp Sandbox Go to the Twilio Console and navigate to Messaging \& Try it out \& Send a WhatsApp message. Select the Sandbox Settings tab. In the section "WHEN A MESSAGE COMES IN," paste your n8n Production Webhook URL. Make sure the method is set to HTTP POST. Click Save. How to Use Your Bot 🚀 Activate the Sandbox: To start, you (and any other users) must send a WhatsApp message with the join code (e.g., join given-word) to your Twilio Sandbox number. Twilio provides this phrase on the same Sandbox page. Fact-Check Away\! Once joined, simply send any claim or question to the Twilio number. For example: Did Elon Musk discover a new planet? Within moments, the workflow will trigger, and you'll receive a formatted reply with the verdict and sources right in your chat\! Further Reading & Resources 🔗 n8n Tunnel Documentation Twilio for WhatsApp Quickstart Perplexity AI API Documentation

The Prompt converter workflow tackles the challenge of turning your natural language video ideas into perfectly formatted JSON prompts tailored for Veo 3 video generation. By leveraging Langchain AI nodes and Google Gemini, this workflow automates and refines your input to help you create high-quality videos faster and with more precision—think of it as your personal video prompt translator that speaks fluent cinematic! 💡 Why Use Prompt Converter? Save time: Automate converting complex video prompts into structured JSON, cutting manual formatting headaches and boosting productivity. Avoid guesswork: Eliminate unclear video prompt details by generating detailed, cinematic descriptions that align perfectly with Veo 3 specs. Improve output quality: Optimize every parameter for Veo 3's video generation model to get realistic and stunning results every time. Gain a creative edge: Turn vague ideas into vivid video concepts with AI-powered enhancement—your video project's secret weapon. ⚡ Perfect For Video creators: Content developers wanting quick, precise video prompt formatting without coding hassles. AI enthusiasts: Developers and hobbyists exploring Langchain and Google Gemini for media generation. Marketing teams: Professionals creating video ads or visuals who need consistent prompt structuring that saves time. 🔧 How It Works ⏱ Trigger: User submits a free text prompt via message or webhook. 📎 Process: The text goes through an AI model that understands and reworks it into detailed JSON parameters tailored for Veo 3. 🤖 Smart Logic: Langchain nodes parse and optimize the prompt with cinematic details, set reasonable defaults, and structure the data precisely. 💌 Output: The refined JSON prompt is sent to Google Gemini for video generation with optimized settings. 🔐 Quick Setup Import the JSON file to your n8n instances Add credentials: Azure OpenAI, Gemini API, OpenRouter API Customize: Adjust prompt templates or default parameters in the Prompt converter node Test: Run your workflow with sample text prompts to see videos come to life 🧩 You'll Need Active n8n instances Azure OpenAI API Gemini API Key OpenRouter API (alternative AI option) 🛠️ Level Up Ideas Add integration with video hosting platforms to auto-upload generated videos 🧠 Nodes Used Prompt Input** (Chat Trigger) OpenAI** (Azure OpenAI GPT model) Alternative** (OpenRouter API) Prompt converter** (Langchain chain LLM for JSON conversion) JSON parser** (structured output extraction) Generate a video** (Google Gemini video generation) Made by: Khaisa Studio Tags: video generation, AI, Langchain, automation, Google Gemini Category: Video Production Need custom work? Contact me

This n8n template offers a simple yet capable chatbot assistant who can answer course enquiries over SMS. Given the right access to data, AI Agents are capable of planning and performing relatively complex research tasks to get their answers. In this example, the agent must first understand the database schema, retrieve lists of values before generating it's own query to search over the database. Checkout the example database here - https://airtable.com/appO5xvP1aUBYKyJ7/shr8jSFDaghubDOrw How it works A Twilio trigger gives us the ability to receive SMS input into our workflow via webhook. The message is then directed to our AI agent who is instructed to assist the user and use the course database as reference. The database is an Airtable base. The agent autonomously figures out which tool it needs to use and generates it's own "filter_by_formula" query to search over the available courses. On successful search results, the Agent can then use this information to answer the user's query. The Agent's output is logged in a second sheet of the Airtable base. We can use this later for analysis and lead gen. Finally, the response is sent back to the user through SMS using Twilio. How to use Ensure your Twilio number is set to forward messages to this workflow's webhook URL. Configure and update the course database as required. If you're not interested in courses, you can swap this out for inventory, deliveries or any other data relevant to your business. Ask questions like: "Can you help me find suitable courses to fill my Wednesday mornings?" "Which courses are being instructed by profession Lee?" "I'm interested in creative arts. What courses are available which could be relevant to me?" Requirements Twilio for SMS receiving and sending OpenAI for LLM and Agent Airtable for Course Database Customising this workflow Add additional tools and expand the range of queries the agent is able to answer or assist with. Not using Airtable? This technique also works with SQL databases like PostgreSQL.

Who this is for? Extract Amazon Best Seller Electronic Info is an automated workflow that extracts best seller data from Amazon's Electronics section using Bright Data Web Unlocker, transform it into structured JSON using Google Gemini's LLM, and forwards a fully structured JSON response to a specified webhook for downstream use. This workflow is tailored for: eCommerce Analysts** Who need to monitor Amazon best-seller trends in the Electronics category and track changes in real-time or on a schedule. Product Intelligence Teams** Who want structured insights on competitor offerings, including rankings, prices, ratings, and promotions. AI-powered Chatbot Developers** Who are building assistants capable of answering product-related queries with fresh, structured data from Amazon. Growth Hackers & Marketers** Looking to automate competitive research and surface trending product data to inform pricing strategies. Data Aggregators and Price Trackers** Who need reliable and smart scraping of Amazon data enriched with AI-driven parsing. What problem is this workflow solving? Keeping up with Amazon's best sellers in Electronics is a time-consuming, error-prone task when done manually.This workflow automates the process, ensuring:​ Automating Data Extraction from Amazon Best Sellers using Bright Data, ensuring reliable access to real-time, structured data. Enhancing Raw Data with Google Gemini, turning product lists into structured JSON using the Google Gemini LLM. Sending Results to a Webhook, enabling seamless integration into dashboards, databases, or chatbots. What this workflow does The workflow performs the following steps:​ Extracts Amazon Best Seller Electronics page info using Bright Data's Web Unlocker API. Processes the unstructured content using Google Gemini's Flash Exp model to extract structured product data. Sends the structured information to a webhook endpoint. Setup Sign up at Bright Data. Navigate to Proxies & Scraping and create a new Web Unlocker zone by selecting Web Unlocker API under Scraping Solutions. In n8n, configure the Header Auth account under Credentials (Generic Auth Type: Header Authentication). The Value field should be set with the Bearer XXXXXXXXXXXXXX. The XXXXXXXXXXXXXX should be replaced by the Web Unlocker Token. In n8n, configure the Google Gemini(PaLM) Api account with the Google Gemini API key (or access through Vertex AI or proxy). Update the Amazon URL with the Bright Data zone by navigating to the Amazon URL with the Bright Data Zone node. Update the Webhook HTTP Request node with the Webhook endpoint of your choice. How to customize this workflow to your needs This workflow is built to be flexible - whether you're a market researcher, e-commerce entrepreneur, or data analyst. Here's how you can adapt it to fit your specific use case: Change the Amazon Category** Update the Amazon URL with the topic of your interest such as Computers & Accessories, Home Audio, etc. Customize the Gemini Prompt** Update the Gemini prompt to get different styles of output — comparison tables, summaries, feature highlights, etc. Send Output to Other Destinations** Replace the Webhook URL to forward output to: Google Sheets Airtable Slack or Discord Custom API endpoints

A lightweight no-code workflow that captures student check-in data via a mobile app or webhook, stores it in a Google Sheet, and instantly notifies the class teacher via email. 🎯 What This Does Students check in using a mobile app or QR code Their data is formatted and saved to a Google Sheet A notification email is sent to the class teacher in real time 🔧 Workflow Steps | Step | Description | | ------------------------------ | ----------------------------------------------------------- | | Student Check-in (Webhook) | Triggered via POST request from mobile app or QR scanner | | Format Data | Cleans and prepares incoming JSON into structured format | | Append or Update Row | Saves student check-in data into Google Sheets | | Email Teacher | Sends formatted check-in email to the class teacher | | Success Response | Returns a confirmation response to the mobile app or system | 📱 Example Check-in Input (Webhook Body) { "student_name": "Aarav Mehta", "student_id": "STU025", "class_name": "Grade 6B" } 📊 Google Sheets Format | Student Name | Student ID | Class | Date | Time | | ------------ | ---------- | -------- | ---------- | ----- | | Aarav Mehta | STU025 | Grade 6B | 2025-08-06 | 08:35 | Date and time are added dynamically in the workflow. ⚙️ Setup Requirements n8n Instance** – Deployed with public webhook support Google Sheets** – Sheet with columns as shown above Email SMTP Settings** – For sending teacher notification ✅ Quick Setup Instructions Import the workflow into your n8n instance Replace the webhook URL in your mobile app Set your Google Sheet ID and range Enter the teacher’s email in the “Email Teacher” node Test with mock data Deploy and use live!

This n8n template empowers you to instantly fetch a list of public holidays for any given year and country using the Nager.Date API. This is incredibly useful for scheduling, planning, or integrating holiday data into various business and personal automation workflows. 🔧 How it works Receive Holiday Request Webhook: This node acts as the entry point, listening for incoming POST requests. It expects a JSON body containing the year (e.g., 2025) and countryCode (e.g., US for United States, PH for Philippines, DE for Germany) for which you want to retrieve public holidays. Get Public Holidays: This node makes an HTTP GET request to the Nager.Date API (date.nager.at). It dynamically uses the year and countryCode from your webhook request to query the API. The API responds with a JSON array, where each object represents a public holiday with details like its date, name, and type. Respond with Holiday Data: This node sends the full list of public holidays received from Nager.Date back to the service that initiated the webhook. 👤 Who is it for? This workflow is ideal for: Businesses with International Operations: Automatically check holidays for different country branches to adjust production schedules, customer service hours, or delivery estimates. HR & Payroll Departments: Accurately calculate workdays, plan leave schedules, or process payroll taking public holidays into account. Event Planners: Avoid scheduling events on public holidays, which could impact attendance or venue availability. Travel Agencies: Inform clients about holidays in their destination country that might affect local business hours or attractions. Content & Social Media Schedulers: Plan content around national holidays to maximize engagement or avoid insensitive postings. Personal Productivity & Travel Planning: Integrate holiday data into your calendar or task management tools to plan trips or personal time off more effectively. Developers: Easily integrate a reliable source of public holiday data into custom applications, dashboards, or internal tools without managing complex datasets. 📑 Data Structure When you trigger the webhook, send a POST request with a JSON body structured as follows: { "year": 2025, "countryCode": "PH" // Example: "US", "DE", "GB", etc. } You can find a comprehensive list of supported country codes on the Nager.Date API documentation: https://www.nager.at/Country The workflow will return a JSON array, where each element is a holiday object, like this example for a single holiday: [ { "date": "2025-01-01", "localName": "New Year's Day", "name": "New Year's Day", "countryCode": "PH", "fixed": true, "global": true, "counties": null, "launchYear": null, "types": [ "Public" ] } // ... more holiday objects ] ⚙️ Setup Instructions Import Workflow: In your n8n editor, click "Import from JSON" and paste the provided workflow JSON. Configure Webhook Path: Double-click the Receive Holiday Request Webhook node. In the 'Path' field, set a unique and descriptive path (e.g., /public-holidays). Activate Workflow: Save and activate the workflow. 📝 Tips This workflow is a foundation for many powerful automations: Conditional Branching for Specific Holidays: Add an IF node after "Get Public Holidays" to check for a specific holiday (e.g., "Christmas Day"). You can then trigger different actions (e.g., send a reminder, adjust a schedule) only for that particular holiday. Filtering and Aggregating Data: Use a Filter node to only keep holidays of a certain type (e.g., "Public"). Use a Code or Function node to count the number of public holidays, or extract just the names and dates into a simpler list. Storing Holiday Data: Google Sheets/Airtable: Automatically append new holidays to a spreadsheet for easy reference or further analysis. Database: Store holiday data in a database (like PostgreSQL or MySQL) to build a custom holiday calendar application. Scheduling and Reminders: Connect this workflow to a Cron or Schedule node to run periodically (e.g., once a year at the start of the year). Use the retrieved holiday dates to set up reminders in your calendar (Google Calendar node) or send notifications (Slack, Email, SMS) a few days before an upcoming holiday. Integrate with Business Logic: Employee Leave Management: Cross-reference employee leave requests with public holidays to ensure accuracy. Automated Messages: Schedule automated "Happy Holiday" messages to customers or employees. E-commerce Shipping: Adjust estimated shipping times based on upcoming non-working days. API Key (Not needed for Nager.Date free tier): The Nager.Date API used here does not require an API key for basic public holiday lookups, which makes this template very easy to use out-of-the-box.