Workflow Templates

Intro This template is for project managers, team leads, or anyone who wants to automatically remind teammates of tasks due today—no manual copy‑and‑paste required. How it works Schedule Trigger runs every morning at 8 AM. Google Sheets node reads your “Tasks” sheet. If node filters rows where Due Date = today. Summarize (ChatGPT HTTP Request) generates a friendly reminder per person. Message a model sends the prompt to your ChatGPT Assistant and returns the AI response. Send a message (Gmail) emails each assignee their personalized reminder. Required Google Sheet Structure | Column Name | Type | Example | Notes | |-------------|--------|---------------------------|-------------------------| | Name | string | Alice Johnson | Person to remind | | Email | string | user@example.com | Recipient email address | | Task | string | Submit quarterly report | Task description | | Due Date | date | 2025‑07‑29 | Format: YYYY‑MM‑DD | Detailed Setup Steps Google Sheets Create your sheet with the columns above. In n8n → Credentials, add Google Sheets API (do not include real sheet IDs in the name). ChatGPT Assistant In the OpenAI Dashboard → Assistants, click Create Assistant. Choose a model (e.g., gpt-4), copy the Assistant ID. In n8n → Credentials → OpenAI, add your API Key and Assistant ID. Gmail In n8n → Credentials → Gmail (OAuth2 or SMTP), connect your account without embedding your real address in the credential name. Import & Configure Export this workflow’s JSON (three‑dot menu → Export). Paste it under Template Code in the Creator form. In each node, select your Google Sheets, OpenAI, and Gmail credentials. Sticky Notes A note on the Schedule node: “Set your desired run time.” A note on the ChatGPT node: “Customizes reminder text.” A note on the Gmail node: “Sends reminder email.” Customization Guidance Change schedule: edit the Cron expression in **Schedule Trigger. Adjust tone**: modify the system prompt in your ChatGPT Assistant. Email format: update **Subject and Body in the Gmail node. Batch processing: insert a **SplitInBatches node before Summarize for large sheets. Troubleshooting Ensure your Google Sheet is shared with the connected service account. Verify Due Date format (YYYY‑MM‑DD). If ChatGPT fails, check your API key and quota. Security & Best Practices Do not** hard‑code API keys, sheet IDs, or real emails. Use n8n Credentials or environment variables only. Remove any private information before submitting.

This n8n template demonstrates how to create a comprehensive voice-powered restaurant assistant that handles table reservations, food orders, and restaurant information requests through natural language processing. The system uses VAPI for voice interaction and PostgreSQL for data management, making it perfect for restaurants looking to automate customer service with voice AI technology. Good to know Voice processing requires active VAPI subscription with per-minute billing Database operations are handled in real-time with immediate confirmations The system can handle multiple simultaneous voice requests All customer data is stored securely in PostgreSQL with proper indexing How it works Table Booking & Order Handling Workflow Voice requests are captured through VAPI triggers when customers make booking or ordering requests The system processes natural language commands and extracts relevant details (party size, time, food items) Customer data is immediately saved to the bookings and orders tables in PostgreSQL Voice confirmations are sent back through VAPI with booking details and estimated wait times All transactions are logged with timestamps for restaurant management tracking Restaurant Info Provider Workflow Info requests trigger when customers ask about hours, menu, location, or services Restaurant details are retrieved from the restaurant_info table containing current information Wait nodes ensure proper data loading before voice response generation Structured restaurant information is delivered via VAPI in natural, conversational format Database Schema Bookings Table booking_id (PRIMARY KEY) - Unique identifier for each reservation customer_name - Customer's full name phone_number - Contact number for confirmation party_size - Number of guests booking_date - Requested reservation date booking_time - Requested time slot special_requests - Dietary restrictions or special occasions status - Booking status (confirmed, pending, cancelled) created_at - Timestamp of booking creation Orders Table order_id (PRIMARY KEY) - Unique order identifier customer_name - Customer's name phone_number - Contact for order updates order_items - JSON array of food items and quantities total_amount - Calculated order total order_type - Delivery, pickup, or dine-in special_instructions - Cooking preferences or allergies status - Order status (received, preparing, ready, delivered) created_at - Order timestamp Restaurant_Info Table info_id (PRIMARY KEY) - Information entry identifier category - Type of info (hours, menu, location, contact) title - Information title description - Detailed information content is_active - Whether info is currently valid updated_at - Last modification timestamp How to use The manual trigger can be replaced with webhook triggers for integration with existing restaurant systems Import the workflow into your n8n instance and configure VAPI credentials Set up PostgreSQL database with the required tables using the schema provided above Configure restaurant information in the restaurant_info table Test voice commands such as "Book a table for 4 people at 7 PM" or "What are your opening hours?" Customize voice responses in VAPI nodes to match your restaurant's tone and branding The system can handle multiple concurrent voice requests and scales with your restaurant's needs Requirements VAPI account for voice processing and natural language understanding PostgreSQL database for storing booking, order, and restaurant information n8n instance with database and VAPI integrations enabled Customising this workflow Voice AI automation can be adapted for various restaurant types - from quick service to fine dining establishments Try popular use-cases such as multi-location booking management, dietary restriction handling, or integration with existing POS systems The workflow can be extended to include payment processing, SMS notifications, and third-party delivery platform integration

Who is this tempate for? This workflow powers a simple yet effective customer and sales support chatbot for your webshop. It's perfect for solopreneurs who want to automate customer interactions without relying on expensive or complex support tools. How it works? The chatbot listens to user requests—such as checking product availability—and automatically handles the following Fetches product information from a Google Sheet Answers customer queries Places an order Updates the stock after a successful purchase Everything runs through a single Google Sheet used for both stock tracking and order management. Setup Instructions Before you begin, connect your Google Sheets credentials by following this guide: This will be used to connect all the tools to Google Sheets 👉 Setup Google sheets credentials Get Stock Open "Get Stock" tool node and select the Google sheet credentials you created. Choose the correct google sheet document and sheet name and you are done. Place order Go to your "Place Order" tool node and select the Google sheet credentials you have created. Choose the correct google sheet document and sheet name. Update Stock - Open your "Update Stock" tool node and select the Google sheet credentials you have created. Choose the correct google sheet document and sheet name. In "Mapping Column Mode" section select map each column manually. In "Column to match on" select the column with a unique identifier (e.g., Product ID) to match stock items. In values to update section, add only the column(s) that need to be updated—usually the stock count. AI Agent node Adjust the prompt according to your use case and customize what you need. Google Sheet Template Stock sheet |Case ID|Phone Model|Case Name|Case Type|Image URL|Quantity Avaialble|Initital Inventory|Sold| |-|-|-|-|-|-|-|-| |1023|Iphone 14 pro|Black Leather|Magsafe|https://example.com/url|90|100|10 Order sheet |Case ID|Phone Model|Case Name|Name|Phone Number|Address| |-|-|-|-|-|-| |1023|Black Leather |Iphone 14 pro|Fernando Torres|9998898888|Paris, France

This workflow compares two lists of objects (List A and List B) using a user-specified key (e.g. email, id, domain) and returns: Items common to both lists (based on the key) Items only in List A Items only in List B How it works: Accepts a JSON input containing: listA: the first list of items listB: the second list of items key: the field name to use for comparison Performs a field-based comparison using the specified key Returns a structured output: common: items with matching keys (only one version retained) onlyInA: items found only in List A onlyInB: items found only in List B Example Input: { "key": "email", "listA": [ { "email": "alice@example.com", "name": "Alice" }, { "email": "bob@example.com", "name": "Bob" } ], "listB": [ { "email": "bob@example.com", "name": "Bobby" }, { "email": "carol@example.com", "name": "Carol" } ] } Output: common: [ { "email": "bob@example.com", "name": "Bob" } ] onlyInA: [ { "email": "alice@example.com", "name": "Alice" } ] onlyInB: [ { "email": "carol@example.com", "name": "Carol" } ] Use Cases: Deduplicate data between two sources Find overlapping records Identify new or missing entries across systems This workflow is useful for internal data auditing, list reconciliation, transaction reconciliation, or pre-processing sync jobs.

This workflow is designed for freelancers, solopreneurs, and business owners who receive a high volume of irrelevant messages in their Gmail inbox — from cold offers to spammy promotions — and want to automatically filter and delete them using AI. Its main purpose is to scan new emails with the help of OpenAI, classify their content, and automatically delete those considered marketing (OFFER) or junk (SPAM). The result is a cleaner inbox without the need to manually sift through low-value messages. The classification logic uses a detailed system prompt with practical examples, so even complex or borderline messages are categorized accurately. Important emails — such as payment confirmations, shipping updates, or genuine business inquiries — remain untouched. This helps maintain a professional inbox with only valuable and relevant communication. The entire process runs automatically in the background and can be customized further — for example, to archive instead of delete, or log deleted emails for review. How it works When triggered (every hour), the workflow fetches new Gmail messages using the Gmail Trigger node. Each message is passed to an AI classifier powered by OpenAI, which reads the message body (email snippet) and returns one of three labels: SPAM: Obvious junk messages, scams, or low-effort bulk messages OFFER: Cold outreach, discount promotions, cart reminders, or generic advertising IMPORTANT: Valuable information for the user, even if commercial (e.g., invoices, order updates, personal inquiries) The workflow then routes the result through an IF node. If the message is marked as SPAM or OFFER, it is immediately deleted from Gmail via the Gmail Delete node. Emails marked as IMPORTANT are ignored and remain in the inbox. The classification is entirely AI-driven based on message content — sender address, headers, or metadata are not used. How to set up To get started, simply connect two credentials: A Gmail account using OAuth2 (via the Gmail Trigger and Gmail Delete nodes) An OpenAI API key (used by the AI classifier node) No advanced setup is needed beyond these two connections. Optionally, you can review or modify the system prompt used for classification — it’s available inside the workflow’s LangChain AI Agent node. The prompt is in English, so it’s recommended to use this workflow with English-language emails for best results. By default, the workflow deletes matching emails immediately. If you prefer safer testing, you can modify the Gmail node to archive, label, or log emails instead of deleting them. The full workflow takes around 5–10 minutes to configure and includes a sticky note with additional instructions and warnings.

Use Case This workflow is a slight variation of a workflow we're using at n8n. In most companies, employees have a lot of great ideas. That was the same for us at n8n. We wanted to make it as easy as possible to allow everyone to add their ideas to some formatted database - it should be somewhere where everyone is all the time and could add a new idea without much extra effort. Since we're using Slack, this seemed to be the perfect place to easily add ideas. In this example, we're adding the ideas to Google Sheets instead of Notion, like we do. What this workflow does This workflow waits for a webhook call within Slack, that gets fired when users use the /idea command on a bot that you will create as part of this template. It then checks the command, adds the idea to Google Sheets and notifies the user about the newly added idea as you can see below: Creating your Slack bot Visit https://api.slack.com/apps, click on New App and choose a name and workspace. Click on OAuth & Permissions and scroll down to Scopes -> Bot token Scopes Add the chat:write scope Head over to Slash Commands and click on Create New Command Use /idea as the command Copy the test URL from the Webhook node into Request URL Add whatever feels best to the description and usage hint Go to Install app and click install Setup Create a Google Sheets document with the columns Name and Creator Add your Google credentials Fill the Set me up node. Create your Slack app (see other sticky) Click Test workflow and use the /idea comment in Slack Activate the workflow and exchange the Request URL with the production URL from the webhook How to adjust it to your needs You can adjust the table in Google Sheets and for example, add different types of ideas or areas that they impact Rename the Slack command as it works best for you How to enhance this workflow At n8n we use this workflow in combination with some others. E.g. we have the following things on top: We additionally have a /bug Slack command that adds a new bug to Linear. Here we're using AI to classify the bugs and move it to the right team. (Bug command workflow and Ai Classifier workflow) We also added other types, like /pain to be less solution-driven To make it easier for everyone to give input, we added a Votes column that allows everyone to vote on ideas/pain points in the list We're also running a workflow once a week that highlights the most popular new ideas and the most active voters

Overview This n8n workflow is specifically designed to monitor USDT TRC20 transactions within a specified wallet. It utilizes the public blockchain database of TronScan, requiring no API authentication, to periodically check and process transaction data. This workflow is ideal for users who need an automated solution to track their TRC20 wallet transactions. Features Automated Tracking**: Executes every 15 minutes to capture new transactions. Customizable Filters**: Tailors the tracking based on specific parameters like transaction time and wallet addresses. Data Aggregation**: Compiles transaction data into a single, structured list. Formatted Outputs**: Presents transaction data in an organized and comprehensible format. Requirements N8N (self-hosted or cloud version) setup and operational. Basic understanding of N8N workflows and nodes. Setup and Configuration Import Workflow: Load the provided JSON workflow into your N8N instance. Configure Edit Fields Node: Enter your TRC20 wallet address in the 'Your Wallet Address' field. Adjust 'Number of transactions to retrieve per request' if necessary. (Default one set to 20 which is recommanded) TronScan Data Access: The workflow accesses TronScan's public blockchain data, so no additional configuration is required for API access. Schedule Trigger Node: Defaulted to trigger every 15 minutes. Modify as per your requirements. Test the Workflow: Execute the workflow manually to ensure everything is operating correctly. How it Works Schedule Trigger: Initiates the workflow at predetermined intervals. Edit Fields: Sets up the wallet address and transaction retrieval count. TronScan Data Retrieval: Gathers transaction data from the TRC20 wallet using TronScan's public database. Split Out & Filter: Processes and filters the transaction data. Final Results: Organizes and formats the required transaction data for review. Aggregate: Consolidates all records (items) into a one comprehensive list (item). Customization Modify the filter conditions and fields to suit your tracking needs. (for example you can higher or lower the number of time to filter or IN / OUT transactions - Default is 15m/IN) Adjust the schedule trigger frequency according to your preference (default is 15m). Best Practices Regularly test the workflow to ensure consistent performance. Stay updated with any changes to the structure of TronScan's public data that might affect the workflow. Contributing Your feedback and contributions are greatly appreciated. Feel free to adapt, modify, and share enhancements with the n8n community.

Extract Title tag and meta description from url for SEO analysis. How it works The workflows takes records from Airtable, get the url in the records and extract from the related webpage the title tag (<title>) and meta description (<meta name="description" content="Some content">). If title tag and/or meta description tag isn't available on the webpage, the result will be empty. Setup Set a Base in Airtable with a table with the following structure: url (field type url), title tag (field type text string), meta desc (field type text field) Minimum suggested table structure is: url (https://example.com), title (Title example), meta desc* (This is the meta description of the example page) Connect Airtable to both Airtable nodes in the template and, with the following formula, get all the records that miss title tag and meta desc. Formula: AND(url != "", {title tag} = "", {meta desc} = "") Insert the url to be analyzed in the table in the field url and let the workflow do the rest. Extra You can also calculate the length for title tag and meta desc using formula field inside Airtable. This is the formula: LEN({title tag}) or LEN({meta desc}) You can automate the process calling a Webhook from Airtable. For this, you need an Airtable paid plan.

What it is: In version 1.78, n8n introduced a dedicated node to use the OpenRouter service, which lets you to use a lot of different LLM models and providers and change models on the fly in an agentic workflow. For prior n8n versions, there's a workaround to make OpenRouter accessible, by using the OpenAI node with a OpenRouter-specific BaseURL. This trivial workflow demonstrates this for version before 1.78, so that you can use different LLM model dynamically with the available n8n nodes for OpenAI LLM and OpenAI credentials. What you can do: Use any of the OpenRouter models Have the model even dynamically configured or changing (by some external config, some rule, or some specific chat message) Setup steps: Import the workflow Ensure you have registered and account, purchased some credits and created and API key for OpenRouter.ai Configure the "OpenRouter" credentials with your own credentials, using an OpenAI type credential, but making sure in the credential's config form its "Base URL" is set to https://openrouter.ai/api/v1 so OpenRouter is used instead of OpenAI. Open the "Settings" node and change the model value to any valid model id from the OpenRouter models list or even have the model property set dynamically

I am submitting this workflow for the Obsidian community to showcase the potential of integrating Obsidian with n8n. While straightforward, it serves as a compelling demonstration of the potential unlocked by integrating Obsidian with n8n. How it works This workflow lets you retrieve specific Airtable data you need in seconds, directly within your Obsidian note, using n8n. By highlighting a question in Obsidian and sending it to a webhook via the Post Webhook Plugin, you can fetch specific data from your Airtable base and instantly insert the response back into your note. The workflow leverages OpenAI’s GPT model to interpret your query, extract relevant data from Airtable, and format the result for seamless integration into your note. Set up steps Install the Post Webhook Plugin: Add this plugin to your Obsidian vault from the plugin store or GitHub. Set up the n8n Webhook: Copy the webhook URL generated in this workflow and insert it into the Post Webhook Plugin's settings in Obsidian. Configure Airtable Access: Link your Airtable account and specify the desired base and table to pull data from. Test the Workflow: Highlight a question in your Obsidian note, use the “Send Selection to Webhook” command, and verify that data is returned as expected.

🌐 Web Server Monitor & Alert System This automation pings web servers at regular intervals, logs their status, and sends email alerts if a server goes down. It’s perfect for maintaining visibility over server uptime — without complex monitoring tools. 🧠 How It Works This workflow performs minute-by-minute checks on all listed servers in a Google Sheet and: ✅ Logs all reachable servers in an “Alive” log. 🔻 Sends an email alert if a server is unreachable. 📄 Logs failed servers in a “Down” sheet with timestamps. 🧩 Key Components ⏰ 1. Schedule Trigger Runs the workflow every minute for real-time monitoring. 📄 2. Web Servers List (Google Sheets) Pulls server IPs or hostnames from a Google Sheet named Server_List. Each row = one server to monitor. This makes adding/removing servers effortless — just update the sheet. 🌐 3. Servers Alive Check (HTTP Request) Performs an HTTP GET request to each server (e.g., http://your-server.com). If the request fails, it automatically triggers the error path (handled via continueOnFail). ✅ 4. Web Server Alive Log (Google Sheets) Records successful pings in Server_Status_Alive with: Timestamp Server IP Status = Alive This log can be used for uptime reports or audits. 📧 5. Server Down Notification (Gmail) If a server fails, this node sends an email to the admin. It includes: Server address Timestamp Suggested action 📄 6. Web Server Down Log (Google Sheets) Logs failed pings in a separate sheet for historical tracking and debugging. ✅ Main Advantages Live Server Monitoring Stay informed about server health in near real-time. No-Code Configuration Add/remove servers from the Google Sheet — no need to touch the workflow. Email Alerts on Failure Proactively notifies you before users report the issue. Audit-Ready Logging Maintains logs for both healthy and failed checks for documentation or reporting. Flexible & Scalable Monitor 1 or 100 servers with the same template — just scale the list. ⚙️ Setup Steps 🔑 Prerequisites Google Sheet with server list (column name = “Server”) Gmail OAuth2 Connection for alerts n8n Instance running regularly 🛠 Configuration Google Sheets Sheet 1 (Server_List): Your list of servers. Sheet 2 (Server_Status_Alive): Log for reachable servers. Sheet 3 (Server_Status_Down): Log for unreachable servers. Gmail Integration Connect your Gmail account in the Server Down Notification node. Edit recipient email and message content as needed. HTTP Check Adjust the HTTP request URL template if using port numbers or paths (e.g., http://{{Server}}:8080/status). Schedule Default is every 1 minute. Change via Schedule Trigger if needed. 🧪 Testing Input a reachable server (e.g., example.com) and an unreachable IP. Run the workflow manually or wait for the next scheduled run. Check: Alive log updates correctly. Down log records failures. Email alert is received. 🚀 Deployment Activate the workflow, and it will quietly run in the background, notifying you of any server downtime instantly while keeping logs for future review.

Who is this workflow for? If you're using Meta Ads to generate new leads to your sales pipeline, this workflow is for you! 🙌🏻 What this workflow does Triggers every time you have a new calendar event on a chosen Google Acount Filter only events with the same name of your "Schedule a demo" event Formats and send event to Meta Conversion API What events can I send? Any event you'd like! It's preconfigured with the "Schedule" event, but you can change to "Purchase", "InitiateCheckout", "Lead" and custom events. Setup Guide Connect Google OAuth2 to n8n Get your PIXEL ID and Access Token from Meta Set your configuration node with Pixel ID, Access Token, source_url and event_name Requirements Meta Access Token + Pixel ID (via Meta Conversion API): Documentation Google Access (via OAuth2): Documentation This free template was created by pdforge. Feel free to contact us via the founder Linkedin, if you have any questions! 👋🏻