Workflow Templates

This n8n template demonstrates how to create a comprehensive marketing automation and booking system that combines Excel-based lead management with voice-powered customer interactions. The system utilizes VAPI for voice communication and Excel/Google Sheets for data management, making it ideal for restaurants seeking to automate marketing campaigns and streamline booking processes through intelligent voice AI technology. Good to know Voice processing requires active VAPI subscription with per-minute billing Excel operations are handled in real-time with immediate data synchronization The system can handle multiple simultaneous voice calls and lead processing All customer data is stored securely in Excel with proper formatting and validation Marketing campaigns can be scheduled and automated based on lead data How it works Lead Management & Marketing Automation Workflow New Lead Trigger: Excel triggers capture new leads when customers are added to the lead management spreadsheet Lead Preparation: The system processes and formats lead data, extracting relevant details (name, phone, preferences, booking history) Campaign Loop: Automated loop processes through multiple leads for batch marketing campaigns Voice Marketing Call: VAPI initiates personalized voice calls to leads with tailored restaurant offers and booking invitations Response Tracking: All call results and lead responses are logged back to Excel for campaign analysis Booking & Order Processing Workflow Voice Response Capture: VAPI webhook triggers when customers respond to marketing calls or make direct booking requests Response Storage: Customer responses and booking preferences are immediately saved to Excel sheets Information Extraction: System processes natural language responses to extract booking details (party size, preferred times, special requests) Calendar Integration: Booking information is automatically scheduled in restaurant management systems Confirmation Loop: Automated follow-up voice messages confirm bookings and provide additional restaurant information Excel Sheet Structure Lead Management Sheet | Column | Description | |--------|-------------| | lead_id | Unique identifier for each lead | | customer_name | Customer's full name | | phone_number | Primary contact number | | email | Customer email address | | last_visit_date | Date of last restaurant visit | | preferred_cuisine | Customer's food preferences | | party_size_typical | Usual number of guests | | preferred_time_slot | Preferred dining times | | marketing_consent | Permission for marketing calls | | lead_source | How customer was acquired | | lead_status | Current status (new, contacted, converted, inactive) | | last_contact_date | Date of last marketing contact | | notes | Additional customer information | | created_at | Lead creation timestamp | Booking Responses Sheet | Column | Description | |--------|-------------| | response_id | Unique response identifier | | customer_name | Customer's name from call | | phone_number | Contact number used for call | | booking_requested | Whether customer wants to book | | party_size | Number of guests requested | | preferred_date | Requested booking date | | preferred_time | Requested time slot | | special_requests | Dietary restrictions or special occasions | | call_duration | Length of VAPI call | | call_outcome | Result of marketing call | | follow_up_needed | Whether additional contact is required | | booking_confirmed | Final booking confirmation status | | created_at | Response timestamp | Campaign Tracking Sheet | Column | Description | |--------|-------------| | campaign_id | Unique campaign identifier | | campaign_name | Descriptive campaign title | | target_audience | Lead segments targeted | | total_leads | Number of leads contacted | | successful_calls | Calls that connected | | bookings_generated | Number of bookings from campaign | | conversion_rate | Percentage of leads converted | | campaign_cost | Total VAPI usage cost | | roi | Return on investment | | start_date | Campaign launch date | | end_date | Campaign completion date | | status | Campaign status (active, completed, paused) | How to use Setup: Import the workflow into your n8n instance and configure VAPI credentials Excel Configuration: Set up Excel/Google Sheets with the required sheet structure provided above Lead Import: Populate the Lead Management sheet with customer data from various sources Campaign Setup: Configure marketing message templates in VAPI nodes to match your restaurant's branding Testing: Test voice commands such as "I'd like to book a table for tonight" or "What are your specials?" Automation: Enable triggers to automatically process new leads and schedule marketing campaigns Monitoring: Track campaign performance through the Campaign Tracking sheet and adjust strategies accordingly The system can handle multiple concurrent voice calls and scales with your restaurant's marketing needs. Requirements VAPI account** for voice processing and natural language understanding Excel/Google Sheets** for storing lead, booking, and campaign data n8n instance** with Excel/Sheets and VAPI integrations enabled Valid phone numbers** for lead contact and compliance with local calling regulations Customising this workflow Multi-location Support**: Adapt voice AI automation for restaurant chains with location-specific offers Seasonal Campaigns**: Try popular use-cases such as holiday promotions, special event marketing, or loyalty program outreach Integration Options**: The workflow can be extended to include CRM integration, SMS follow-ups, and social media campaign coordination Advanced Analytics**: Add nodes for detailed campaign performance analysis and customer segmentation

This workflow automates the process of publishing PR News articles to the WordPress website. 🔧 How it works: Uses an RSS Feed Trigger to monitor new PR News articles. Extracts the article content and parses the featured image URL. Uploads the image to WordPress as a media item. Creates a new draft post on the WordPress site using the article's content and sets the uploaded image as the featured image. ✅ Features: Polls RSS feed every minute. Automatically extracts and sets featured images. Posts are created as drafts for editorial review. 📝 Requirements: WordPress REST API access with media upload permission. Active WordPress credentials in n8n. Perfect for teams who want to streamline PR content publishing without manual effort.

This workflow creates a Slack thread when a new ticket is created in Zendesk. Subsequent comments on the ticket in Zendesk are added as replies to the thread in Slack. Prerequisites Zendesk account and Zendesk credentials. Slack account and Slack credentials. Slack channel to create threads in. How it works The workflow listens for new tickets in Zendesk. When a new ticket is created, the workflow creates a new thread/message in Slack. The Slack thread ID is then saved in one of the ticket's fields called "Slack thread ID". The next time a comment is added to the ticket, the workflow retrieves the Slack thread ID from the ticket's field and adds the comment to the thread/message in Slack as a reply. Setup This workflow requires that you set up a webhook in Zendesk. To do so, follow the steps below: In the workflow, open the On new Zendesk ticket node and copy the webhook URL. In Zendesk, navigate to Admin Center > Apps and integrations > Webhooks > Actions > Create Webhook. Add all the required details which can be retrieved from the On new Zendesk ticket node. The webhook URL gets added to the “Endpoint URL” field, and the “Request method” should match what is shown in n8n. Save the webhook. In Zendesk, navigate to Admin Center > Objects and rules > Business rules > Triggers > Add trigger. Give trigger a name such as “New tickets”. Under “Conditions” in “Meet ALL of the following conditions”, add “Status is New”. Under “Actions”, select “Notify active webhook” and select the webhook you created previously. In the JSON body, add the following: { "id": "{{ticket.id}}", "comment": "{{ticket.latest_comment_html}}" } Save the Zendesk trigger. You will also need to set up a field in Zendesk to store the Slack thread ID. To do so, follow the steps below: In Zendesk, navigate to Admin Center > Objects and rules > Tickets > Fields > Add field. Use the text field option and give the field a name such as “Slack thread ID”. Save the field. In n8n, open the Update ticket node and select the field you created in Zendesk.

Who is this template for? This template is designed for developers, DevOps engineers, and automation enthusiasts who want to streamline their GitLab merge request process using n8n, a low-code workflow automation tool. It eliminates manual intervention by automating the merging of GitLab branches through API calls. How it works ? Trigger the workflow: The workflow can be triggered by a webhook, a scheduled event, or a GitLab event (e.g., a new merge request is created or approved). Fetch Merge Request Details: n8n makes an API call to GitLab to retrieve merge request details. Check Merge Conditions: The workflow validates whether the merge request meets predefined conditions (e.g., approvals met, CI/CD pipelines passed). Perform the Merge: If all conditions are met, n8n sends a request to the GitLab API to merge the branch automatically. Setup Steps 1. Prerequisites An n8n instance (Self-hosted or Cloud) A GitLab personal access token with API access A GitLab repository with merge requests enabled 2. Create the n8n Workflow Set up a trigger: Choose a trigger node (Webhook, Cron, or GitLab Trigger). Fetch merge request details: Add an HTTP Request node to call GET /merge_requests/:id from GitLab API. Validate conditions: Check if the merge request has necessary approvals. Ensure CI/CD pipelines have passed. Merge the request: Use an HTTP Request node to call PUT /merge_requests/:id/merge API. 3. Test the Workflow Create a test merge request. Check if the workflow triggers and merges automatically. Debug using n8n logs if needed. 4. Deploy and Monitor Deploy the workflow in production. Use n8n’s monitoring features to track execution. This template enables seamless GitLab merge automation, improving efficiency and reducing manual work! Note: Never hard code API token or secret in your https request.

Who is this for? This workflow is perfect for: Companies that manage invoices through Google Drive Business owners who want to minimize manual data entry and maximize accuracy Accounting teams and finance departments seeking to automate invoice processing What problem is this workflow solving? Processing invoices manually is time-consuming, error-prone, and inconsistent. This workflow solves those issues by: Automating invoice processing** from detection to data extraction to storage Improving accuracy** by using AI to extract key invoice data fields reliably Reducing human workload** while maintaining compliance and consistency What this workflow does This workflow creates a fully automated invoice processing system by: Monitoring a Google Drive folder for new PDF invoices in real time Downloading the PDF files and extracting their content using OCR technology Using AI (OpenAI) to parse and extract key invoice fields such as invoice number, date, total amount, vendor name, itemized details, tax, and category Validating the extracted data to ensure compliance with a structured JSON schema Storing structured data in Google Sheets for easy access, review, and reporting Key Features: AI-powered extraction handles both text-based and scanned PDF invoices Provides a structured, searchable invoice database in Google Sheets Configured to run as frequently as the user needs, ensuring timely processing. Setup Copy the Google Sheet template here: 👉 PDF Invoice Parser – Google Sheet Template Connect your Google Drive account to the Drive Trigger and File Download nodes Add your OpenAI API key in the AI Parser node Link the Google Sheet in the final storage node Drop a test invoice PDF into the monitored Drive folder Required Credentials: OpenAI API Key** Google Drive Credentials** Google Sheets Credentials** How to customize this workflow to your needs Modify the polling interval** (default: every minute) for higher/lower frequency. Integrate with your accounting software** by adding nodes (e.g., QuickBooks, Xero). Use alternative LLM** such as Gemini, Claude.

This workflow creates a GitHub issue when a new ticket is created in Zendesk. Subsequent comments on the ticket in Zendesk are added as comments to the issue in GitHub. Prerequisites Zendesk account and Zendesk credentials. GitHub account and GitHub credentials. GitHub repository to create issues in. How it works The workflow listens for new tickets in Zendesk. When a new ticket is created, the workflow creates a new issue in GitHub. The GitHub issue number is then saved in one of the ticket's fields (in setup we call this "GitHub Issue Number"). The next time a comment is added to the ticket, the workflow retrieves the GitHub issue number from the ticket's field and adds the comment to the issue in GitHub. Setup This workflow requires that you set up a webhook in Zendesk. To do so, follow the steps below: In the workflow, open the On new Zendesk ticket node and copy the webhook URL. In Zendesk, navigate to Admin Center > Apps and integrations > Webhooks > Actions > Create Webhook. Add all the required details which can be retrieved from the On new Zendesk ticket node. The webhook URL gets added to the “Endpoint URL” field, and the “Request method” should match what is shown in n8n. Save the webhook. In Zendesk, navigate to Admin Center > Objects and rules > Business rules > Triggers > Add trigger. Give trigger a name such as “New tickets”. Under “Conditions” in “Meet ALL of the following conditions”, add “Status is New”. Under “Actions”, select “Notify active webhook” and select the webhook you created previously. In the JSON body, add the following: { "id": "{{ticket.id}}", "comment": "{{ticket.latest_comment_html}}" } Save the Zendesk trigger. You will also need to set up a field in Zendesk to store the GitHub issue number. To do so, follow the steps below: In Zendesk, navigate to Admin Center > Objects and rules > Tickets > Fields > Add field. Use the number field option and give the field a name such as “GitHub Issue Number”. Save the field. In n8n, open the Update ticket node and select the field you created in Zendesk.

Google Sheets Company Enrichment with Explorium MCP Template Download the following json file and import it to a new n8n workflow: google\_sheets\_enrichment.json Overview This n8n workflow template enables automatic enrichment of company information in your Google Sheets. When you add a new company or update existing company details (name or website), the workflow automatically fetches additional business intelligence data using Explorium MCP and updates your sheet with: Business ID NAICS industry code Number of employees (range) Annual revenue (range) Key Features Automatic Triggering**: Monitors your Google Sheet for new rows or updates to company name/website fields Smart Processing**: Only processes new or modified rows, not the entire sheet Data Validation**: Ensures both company name and website are present before processing Error Handling**: Processes each row individually to prevent one failure from affecting others Powered by AI**: Uses Claude Sonnet 4 with Explorium MCP for intelligent data enrichment Prerequisites Before setting up this workflow, ensure you have: n8n instance (self-hosted or cloud) Google account with access to Google Sheets Anthropic API key for Claude Explorium MCP API key Installation & Setup Step 1: Import the Workflow Create a new workflow. Download the workflow JSON from above. In your n8n instance, go to Workflows → Add Workflow → Import from File Select the JSON file and click Import Step 2: Create Google Sheet Create a new google sheet (or make a copy of this template) Your Google Sheet must have the following columns (exact names): name - Company name website - Company website URL business_id - Will be populated by the workflow naics - Will be populated by the workflow number_of_employees_range - Will be populated by the workflow yearly_revenue_range - Will be populated by the workflow Step 3: Configure Google Sheets Credentials You'll need to set up two Google credentials: Google Sheets Trigger Credentials: Click on the Google Sheets Trigger node Under Credentials, click Create New If working on n8n Cloud, Click the 'Sign in with Google' button Grant permissions to read and monitor your Google Sheets If working on n8n Instance, Follow the OAuth2 authentication process here Fill the Client ID and Client Secret fields Google Sheets Update Credentials: Click on the Update Company Row node Under Credentials, select the same credentials or create new ones (The same you did above) Ensure permissions include write access to your sheets Step 4: Configure Anthropic Credentials Click on the Anthropic Chat Model node Under Credentials, click Create New Enter your Anthropic API key Save the credentials Step 5: Configure Explorium MCP Credentials Click on the MCP Client node Under Credentials, click Create New (Header Auth) Fill the Name field with api_key Fill the Value field with your Explorium API Key Save the credentials Step 6: Link Your Google Sheet In the Google Sheets Trigger node: Select your Google Sheet from the dropdown Select the worksheet (usually "Sheet1") In the Update Company Row node: Select the same Google Sheet and worksheet Ensure the matching column is set to row_number Step 7: Activate the Workflow Click the Active toggle in the top right to activate the workflow The workflow will now monitor your sheet every minute for changes How It Works Workflow Process Flow Google Sheets Trigger: Polls your sheet every minute for new rows or changes to name/website fields Filter Valid Rows: Validates that both company name and website are present Loop Over Items: Processes each company individually AI Agent: Uses Explorium MCP to: Find the company's business ID Retrieve firmographic data (revenue, employees, NAICS code) Format Output: Structures the data for Google Sheets Update Company Row: Writes the enriched data back to the original row Trigger Behavior First Activation**: May process all existing rows to establish a baseline Ongoing Operation**: Only processes new rows or rows where name/website fields change Polling Frequency**: Checks for changes every minute Usage Adding New Companies Add a new row to your Google Sheet Fill in the name and website columns Within 1 minute, the workflow will automatically: Detect the new row Enrich the company data Update the remaining columns Updating Existing Companies Modify the name or website field of an existing row The workflow will re-process that row with the updated information All enrichment data will be refreshed Monitoring Executions In n8n, go to Executions to see workflow runs Each execution shows: Which rows were processed Success/failure status Detailed logs for troubleshooting Troubleshooting Common Issues All rows are processed instead of just new/updated ones Ensure the workflow is activated, not just run manually Manual test runs will process all rows First activation may process all rows once No data is returned for a company Verify the company name and website are correct Check if the company exists in Explorium's database Some smaller or newer companies may not have data available Workflow isn't triggering Confirm the workflow is activated (Active toggle is ON) Check that changes are made to the name or website columns Verify Google Sheets credentials have proper permissions Authentication errors Re-authenticate Google Sheets credentials Verify Anthropic API key is valid and has credits Check Explorium Bearer token is correct and active Error Handling The workflow processes each row individually, so if one company fails to enrich: Other rows will still be processed The failed row will retain its original data Check the execution logs for specific error details Best Practices Data Quality: Ensure company names and websites are accurate for best results Website Format: Include full URLs (https://example.com) rather than just domain names Batch Processing: The workflow handles multiple updates efficiently, so you can add several companies at once Regular Monitoring: Periodically check execution logs to ensure smooth operation API Limits & Considerations Google Sheets API**: Subject to Google's API quotas Anthropic API**: Each enrichment uses Claude Sonnet 4 tokens Explorium MCP**: Rate limits may apply based on your subscription Support For issues specific to: n8n platform**: Consult n8n documentation or community Google Sheets integration**: Check n8n's Google Sheets node documentation Explorium MCP**: Contact Explorium support for API-related issues Anthropic/Claude**: Refer to Anthropic's documentation for API issues Example Use Cases Sales Prospecting: Automatically enrich lead lists with company size and revenue data Market Research: Build comprehensive databases of companies in specific industries Competitive Analysis: Track and monitor competitor information Investment Research: Gather firmographic data for potential investment targets

AI Voice Calling Bot - OpenAI GPT-4o + ElevenLabs + Twilio Integration for Multilingual Appointment Booking & Service Orders Overview Transform your business with an intelligent voice calling bot that handles customer calls automatically in 25+ languages. This N8n workflow integrates OpenAI GPT-4o, ElevenLabs text-to-speech, and Twilio for seamless appointment scheduling, pizza orders, and service bookings. Key Features Multilingual Support**: Conversations in English, Spanish, French, German, Italian, Portuguese, Chinese, Japanese, Arabic, and 20+ more languages Natural AI Conversations**: GPT-4o powered responses with ElevenLabs realistic voice synthesis Multi-Service Handling**: Appointments, orders, and service requests with automatic logging Real-time Processing**: Instant speech-to-text and audio response generation Prerequisites N8n instance (self-hosted or cloud) Twilio account with phone number OpenAI API key (GPT-4o access) ElevenLabs API credentials Google Sheets access Cloud storage for audio files Setup Instructions Step 1: Configure Credentials Add API keys for OpenAI, ElevenLabs, Twilio, and Google Sheets in N8n credentials manager. Step 2: Prepare Data Storage Create Google Sheets for call logs and appointments with columns: timestamp, caller_id, speech_input, ai_response, language, call_sid. Step 3: Configure Twilio Set webhook URL to your N8n endpoint: https://your-n8n-instance.com/webhook/voice-webhook Step 4: Update Sheet IDs Replace placeholder Google Sheet IDs in workflow nodes with your actual sheet IDs. Customization Options Voice Settings**: Adjust ElevenLabs multilingual voice models and parameters AI Behavior**: Modify system prompts for specific business needs and languages Service Types**: Add custom service handling logic Business Hours**: Implement language-specific operating hours Monitoring Track call analytics, language preferences, conversion rates, and customer satisfaction across all supported languages through automated Google Sheets logging. Ready for production use with comprehensive error handling and scalability for global businesses.

An intelligent WhatsApp-based chatbot designed for restaurants to automate customer interactions related to table bookings, menu inquiries, opening hours, services, and offers. Built using the n8n automation platform and powered by an AI language model, this solution streamlines communication, boosts efficiency, and improves customer satisfaction. Objectives Automate replies to common customer queries on WhatsApp Handle table booking requests with confirmation Provide menu item details, pricing, and dietary information Share restaurant timing, location, and service availability Promote offers and handle promotional queries Operate 24/7 without manual intervention Store bookings and conversations for reporting and analytics Workflow Summary Step 1: Message Reception Node: WhatsApp Trigger (Webhook or API-based) Function: Listens for incoming customer messages. Step 2: Intent Recognition Node: AI Query Processor (e.g., OpenAI API) Function: Detects customer intent (e.g., booking, menu, timing). Step 3: Conditional Routing Node: Switch or IF Node Function: Routes flow based on detected intent: General information (menu, timing, services) Table booking Step 4A: Respond to General Info Queries Node: AI Response or Static Reply Node Function: Returns relevant information (menu, timing, address, etc.). Step 4B: Process Booking Requests Nodes: Collect Booking Details** (via chatbot interactions) Store Booking Info** (to DB or Google Sheets) Send Booking Confirmation** (to customer) Step 5: Context Management Node: Set/Update Customer Data Function: Maintains conversation state and tracks follow-up messages. Database or Google Sheet Columns for Table Booking | Column Name | Description | | ----------------- | ----------------------------------------------- | | reservation\_id | Unique reservation identifier | | guest\_name | Full name of the guest | | contact\_number | Customer’s WhatsApp or mobile number | | email | (Optional) Email address | | booking\_date | Reservation date (YYYY-MM-DD format) | | booking\_time | Reservation time (HH\:MM format) | | party\_size | Number of guests | | table\_id | (Optional) Table number or identifier | | special\_requests | Allergies, seating preferences, etc. | | status | Booking status: Confirmed / Cancelled / Pending | | created\_at | Timestamp when booking was made | | updated\_at | Timestamp when booking was last modified | Prerequisites Verified WhatsApp Business Account with API access n8n instance (Cloud or self-hosted) Access to an AI service (e.g., OpenAI, Claude) Google Sheets, Airtable, MySQL, or other DB integration Setup Instructions Connect WhatsApp API using webhook or third-party WhatsApp provider (e.g., 360Dialog, Twilio). Integrate AI using HTTP Request or OpenAI node for response generation. Create Data Store (Google Sheet, Airtable, or MySQL) with defined booking columns. Design Workflow in n8n with intent detection, conditional logic, and response nodes. Test End-to-End by sending different WhatsApp queries and checking logs and stored data. Example Conversation Customer: “Can I book a table for 2 people tomorrow at 8 PM?” Bot: “Sure. Please provide your name and contact number to confirm the reservation for 2 people at 8:00 PM tomorrow.” \[Booking details are saved, and a confirmation is sent.] Benefits Fully automated customer interaction Supports real-time table reservations Accurate and quick responses Scales without increasing staff effort Operates 24/7 Centralized booking data for analytics Analytics and Reporting Track key performance metrics such as: Number of bookings per day/week Average response time Customer satisfaction scores (via feedback node) Popular menu items or query types Booking conversion rates Security and Compliance End-to-end encrypted WhatsApp messages Role-based access to sensitive data Compliance with data protection regulations (e.g., GDPR) Secure API integrations and storage solutions Conclusion This WhatsApp chatbot serves as a reliable, AI-powered digital front desk for restaurants. Built using n8n and scalable components, it automates customer support, manages bookings, and enhances operational efficiency while offering a seamless customer experience.

This template shows how to sync data from one service to another. Specifically, in this example we're saving a new qualified lead from a Postgres database to a Google Sheets file. Setup instructions are located inside the workflow template.

Intro This workflow needs a user to authenticate by using an openid connect provider in order to call the webhook. If the user is not authenticated, it starts a login process by using an Authorization Code with PKCE https://datatracker.ietf.org/doc/html/rfc7636, a standard way to authenticate users with openid connect. Then, after the user logs in, the webhook is refreshed and gets the user's token from a cookie. With this token, all details about the user are requested through the userinfo endpoint on the identity provider. How to set up with Keycloak Keycloak Keycloak is an open source identity and access management solution. Feel free to get a demo realm at https://please-open.it or get your own Keycloak server up and running. After creating a realm, go to "Realm Settings" and click on "OpenID Endpoint Configuration" Retrieve authorization_endpoint, token_endpoint and userinfo_endpoint values. Set those variables in the "Set variables" node. In Keycloak, create a new client (name it as you want) Disable the client authentication, check only "standard flow" : At the third step, put the webhook url in "valid redirect URIs", fill "Web origins" with a "+". You're done, open the webhook and it asks you to authenticate. Usage User informations The userinfo node returns this structure about the user has logged in : [ { "sub":"73a6543f-f420-4fa6-9811-209e903c348b", "email_verified":true, "preferred_username": "mathieu.passenaud@please-open.it", "email": "mathieu.passenaud@please-open.it" } ] I can use those infos in my workflow for custom operations. APIs calls the "code" node returns me a cookie named "n8n-custom-auth" which is the access_token returned by the identity provider. This access_token can be used to call APIs connected to this identity provider (for example, we call userinfo API with this token). Example : asks a user to log in with his Google account then call an API (Gmail, drive...) with his own token. How it works We published a blog post about this flow, how it works and how you can use it : https://blog.please-open.it/n8n-openid-client/

. IOT device control with MQTT and webhook This workflow is for users wanting a practical example of how to control IOT systems using the MQTT protocol in an an n8n environment. The template provides typical n8n MQTT and Webhook node implementation and configuration settings necessary to set IOT device inputs and outputs. How it works A webpage with IOT control 'on and 'off' buttons is presented to the user. When a button is selected on the webpage the value is sent via a webhook to trigger the active workflow. The workflow set node then prepares the received value into a message payload. It then passes the message to the MQTT node for publishing the topic with the payload to a cloud based MQTT broker. A remote ESP32 micro-controller subscribes to the broker and reads the payload contained in the topic. The ESP32 will then toggle the GPIO pin depending on the topic payload value. The IOT control webpage The webpage is a simple HTML page containing the clickable 'on' and 'off' buttons. It also has the get webhook URL that sends the selected value to the n8n workflow in this case running locally. The URL webhook format is http://localhost:5678/webhook/pin-control?value=action The webpage code IOT-control.html IOT device The IOT device is an ESP32 micro-controller running on a remote network. To keep it simple GPIO2 is selected as the control output. In this case when the received value is "on" GPIO2 goes high a led will turn on in the ESP32. It will go off when the received value is "off". The program for the ESP32 IOT control is 'main.py' . You will require a micropython interpreter to be uploaded to the ESP32 for the program to run automatically. The code can be easily edited and modified to accommodate any further attached IOT devices. The ESP32 main.py code main.py How to customise this workflow to your needs ESP32 You will need a working ESP32 installed with a micro-python interpreter. The code main.py is provided. The main.py program can loaded and edited with a python IDE. I used Thonny for this example. Use a free MQTT broker to get started. I used "broker.emqx.io" in the code. IOT Control Webpage The webpage contains HTML and can be easily edit to enhance functionality. The embedded webhook is configured for n8n production mode. http://localhost:5678/webhook/pin-control?value=action If you want to run the page in test mode you will use the following URL. http://localhost:5678/webhook-test/pin-control?value=action n8n workflow. The workflow is a good demonstration of how to control IOT devices using n8n. Following these steps will give a good insight for microcontroller automation.