Workflow Templates

Easily generate QR codes from any URL! This workflow lets users submit a URL via a simple form and instantly receive a downloadable QR code image—perfect for quick sharing or promotions. Setup is fast and user-friendly, so you’ll be up and running in minutes! 🚀 How it works The end user submits a URL through a simple online form. The workflow automatically sends the submitted URL to a QR code generation API. The user receives a downloadable QR code image corresponding to their URL. ⚙️ Setup instruction Import Workflow: Click "Import from JSON" in your n8n environment and paste the provided workflow JSON. Click "Save" and activate the workflow. Double click the "On form submission" node to obtain the production URL. You may now use this URL to do QR code generation.

🧨 VIP Radar: Instantly Spot & Summarize High-Value Shopify Orders with AI + Slack Alerts Automatically detect when a new Shopify order exceeds $200, fetch the customer’s purchase history, generate an AI-powered summary, and alert your team in Slack—so no VIP goes unnoticed. 🛠️ Workflow Overview | Feature | Description | |------------------------|-----------------------------------------------------------------------------| | Trigger | Shopify “New Order” webhook | | Conditional Check | Filters for orders > $200 | | Data Enrichment | Pulls full order history for the customer from Shopify | | AI Summary | Uses OpenAI to summarize buying behavior | | Notification | Sends detailed alert to Slack with name, order total, and customer insights | | Fallback | Ignores low-value orders and terminates flow | 📘 What This Workflow Does This automation monitors your Shopify store and reacts to any high-value order (over $200). When triggered: It fetches all past orders of that customer, Summarizes the history using OpenAI, Sends a full alert with context to your Slack channel. No more guessing who’s worth a closer look. Your team gets instant insights, and your VIPs get the attention they deserve. 🧩 Node-by-Node Breakdown 🔔 1. Trigger: New Shopify Order Type**: Shopify Trigger Event**: orders/create Purpose**: Starts workflow on new order Pulls**: Order total, customer ID, name, etc. 🔣 2. Set: Convert Order Total to Number Ensures the total_price is treated as a number for comparison. ❓ 3. If: Is Order > $200? Condition**: $json.total_price > 200 Yes** → Continue No** → End workflow 🔗 4. HTTP: Fetch Customer Order History Uses the Shopify Admin API to retrieve all orders from this customer. Requires your Shopify access token. 🧾 5. Set: Convert Orders Array to String Formats the order data so it's prompt-friendly for OpenAI. 🧠 6. LangChain Agent: Summarize Order History Prompt**: "Summarize the customer's order history for Slack. Here is their order data: {{ $json.orders }}" Model**: GPT-4o Mini (customizable) 📨 7. Slack: Send VIP Alert Sends a rich message to a Slack channel. Includes: Customer name Order value Summary of past behavior 🧱 8. No-Op (Optional) Used to safely end workflow if the order is not high-value. 🔧 How to Customize | What | How | |--------------------------|----------------------------------------------------------------------| | Order threshold | Change 200 in the If node | | Slack channel | Update channelId in the Slack node | | AI prompt style | Edit text in LangChain Agent node | | Shopify auth token | Replace shpat_abc123xyz... with your actual private token | 🚀 Setup Instructions Open n8n editor. Go to Workflows → Import → Paste JSON. Paste this workflow JSON. Replace your Shopify token and Slack credentials. Save and activate. Place a test order in Shopify to watch it work. 💡 Real-World Use Cases 🎯 Notify sales team when a potential VIP buys 🛎️ Prep support reps with customer history 📈 Detect repeat buyers and upsell opportunities 🔗 Resources & Support 👨‍💻 Creator: Yaron Been 📺 YouTube: NoFluff with Yaron Been 🌐 Website: https://nofluff.online 📩 Contact: Yaron@nofluff.online 🏷️ Tags #shopify, #openai, #slack, #vip-customers, #automation, #n8n, #workflow, #ecommerce, #customer-insights, #ai-summaries, #gpt4o

You still can use the app in a workflow even if we don’t have a node for that or the existing operation for that. With the HTTP Request node, it is possible to call any API point and use the incoming data in your workflow Main use cases: Connect with apps and services that n8n doesn’t have integration with Web scraping How it works This workflow can be divided into three branches, each serving a distinct purpose: 1.Splitting into Items (HTTP Request - Get Mock Albums): The workflow initiates with a manual trigger (On clicking 'execute'). It performs an HTTP request to retrieve mock albums data from "https://jsonplaceholder.typicode.com/albums." The obtained data is split into items using the Item Lists node, facilitating easier management. 2.Data Scraping (HTTP Request - Get Wikipedia Page and HTML Extract): Another branch of the workflow involves fetching a random Wikipedia page using an HTTP request to "https://en.wikipedia.org/wiki/Special:Random." The HTML Extract node extracts the article title from the fetched Wikipedia page. 3.Handling Pagination (The final branch deals with handling pagination for a GitHub API request): It sends an HTTP request to "https://api.github.com/users/that-one-tom/starred," with parameters like the page number and items per page dynamically set by the Set node. The workflow uses conditions (If - Are we finished?) to check if there are more pages to retrieve and increments the page number accordingly (Set - Increment Page). This process repeats until all pages are fetched, allowing for comprehensive data retrieval.

This workflow automates voice reminders for upcoming appointments by generating a professional audio message and sending it to clients via email with the voice file attached. It integrates Google Calendar to track appointments, ElevenLabs to generate high-quality voice messages, and Gmail to deliver them efficiently. Who Needs Automated Voice Appointment Reminders? This automated voice appointment reminder system is ideal for businesses that rely on scheduled appointments. It helps reduce no-shows, improve client engagement, and streamline communication. Medical Offices & Clinics – Ensure patients receive timely appointment reminders. Real Estate Agencies – Keep potential buyers and renters informed about property visits. Service-Based Businesses – Perfect for salons, consultants, therapists, and coaches. Legal & Financial Services – Help clients remember important meetings and consultations. If your business depends on scheduled appointments, this workflow saves time and enhances client satisfaction. 🚀 Why Use This Workflow? Ensures clients receive timely reminders. Reduces appointment no-shows and scheduling issues. Automates the process with a personalized voice message. Step-by-Step: How This Workflow Automates Voice Reminders Trigger the Workflow – The system runs manually or on a schedule to check upcoming appointments in Google Calendar. Retrieve Appointment Data – It fetches event details (client name, time, and location) from Google Calendar. The workflow uses the summary, start.dateTime, location, and attendees[0].email fields from Google Calendar to personalize and send the voice reminders. Generate a Voice Reminder – Using ElevenLabs, the workflow converts the appointment details into a natural-sounding voice message. Send via Email – The generated audio file is attached to an email and sent to the client as a reminder. Customization: Tailor the Workflow to Your Business Needs Adjust Trigger Frequency – Modify the scheduling to run daily, hourly, or at specific intervals. Customize Voice Message Format – Change the script structure and voice tone to match your business needs. Change Notification Method – Instead of email, integrate SMS or WhatsApp for delivery. 🔑 Prerequisites Google Calendar Access** – Ensure you have access to the calendar with scheduled appointments. ElevenLabs API Key – Required for generating voice messages (you can start for free). Gmail API Access** – Needed for sending reminder emails. n8n Setup** – The workflow runs on an n8n instance (self-hosted or cloud). 🚀 Step-by-Step Installation & Setup Set Up Google Calendar API** Go to Google Cloud Console. Create a new project and enable Google Calendar API. Generate OAuth 2.0 credentials and save them for n8n. Get an ElevenLabs API Key** Sign up at ElevenLabs. Retrieve your API key from the dashboard. Configure Gmail API** Enable Gmail API in Google Cloud Console. Create OAuth credentials and authorize your email address for sending. Deploy n8n & Install the Workflow** Install n8n (Installation Guide). Add the required Google Calendar, ElevenLabs, and Gmail nodes. Import or build the workflow with the correct credentials. Test and fine-tune as needed. ⚠ Important: The LangChain Community node used in this workflow only works on self-hosted n8n instances. It is not compatible with n8n Cloud. Please ensure you are running a self-hosted instance before using this workflow. Summary This workflow ensures a professional and seamless experience for your clients, keeping them informed and engaged. 🚀🔊 Phil | Inforeole

All-in-One Portfolio Tracker & Telegram Finance Updates Workflow for n8n: Multi-Broker, Real-Time, Global 🚀 Overview Take control of all your investments—across multiple brokers and platforms—in one place, with live updates sent directly to your Telegram! 🌍💸 This n8n template brings together Google Sheets and Telegram so you can track your complete finance portfolio with ease, whether you’re in the US market, India, or anywhere in the world. 🔧 Built By - akash@codescale.tech How This Workflow Works Tracks your investments** across multiple brokers, platforms, or asset types. Automatically sends updates to your Telegram account**—see daily Profit & Loss (P&L), changes, and total returns in a rich, emoji-filled report. Works globally**, with a sample provided for the US market, but can be configured for any country and broker. Schedule automated updates** (e.g., market close/open) or get real-time insights on demand with Telegram commands. Highlights & Features 📊 Unified Dashboard: Integrate all your broker data in one Google Sheet for effortless monitoring (Google Sheet Link - https://docs.google.com/spreadsheets/d/1dakq9EhU8GrDgBsk82KvAen0N1P3FySAwNHFtG2lsLI/edit?usp=sharing) 🤖 Interactive Telegram Bot: Send /total or a specific broker’s name in the Telegram chat to get instant, formatted portfolio summaries. ⏰ Automatic Notifications: Receive scheduled P&L summaries at market open and close. 🗂️ Customizable for Any Region or Broker: Just update your Google Sheet with the platforms or brokers you use—including those in the US, Europe, Asia, etc. 🔐 Secure and Private: Only your pre-set Telegram user or chat receives the sensitive financial update. Example (For US Market) Let’s imagine you have portfolios with Robinhood, E*TRADE, and Charles Schwab. Every day at 10AM and 4PM Eastern Time, or whenever you send the /total command, you get this on Telegram: 📊 Daily P&L Report 🔹 Robinhood Invested: $5,000.00 P&L: $250.00 (5.00%) Change: $30.00 (0.60%) Current Value: $5,250.00 🔹 E*TRADE Invested: $8,000.00 P&L: $400.00 (5.00%) Change: $45.00 (0.56%) Current Value: $8,400.00 📈 Total Portfolio Total Invested: $13,000.00 Total P&L: $650.00 (5.00%) Today's Change: $75.00 (0.58%) 💰 Overall Value: $13,650.00 📈 Overall Return: 5.00% 💸 Overall P&L: $650.00 Easy Setup Steps Copy the Template to Your n8n Instance: Just import the provided workflow JSON. Configure Your Google Sheet: List all your brokers/platforms as rows (US, EU, or any other market). Update your credentials in n8n for Google Sheets and Telegram. Set Your Telegram Chat ID: Secure, so only you or your group receive updates. Customize Schedules: Change times for your local market hours or as you prefer. Send Commands in Telegram: /total for overall summary /Robinhood, /ETRADE, etc., for individual broker updates Who Is This For? Investors managing accounts across several brokers. Traders seeking real-time daily summaries. Portfolio managers wanting one consolidated, secure view. Users in any country, for any major market. Make It Yours! 🌏 Customize the sheet and workflow for your unique blend of accounts, currencies, and platforms—track mutual funds, stocks, ETFs, cryptos, or more. Get peace of mind with every notification, organized and delivered just for you! Start tracking smarter, not harder. Transform your finance workflow with n8n + Telegram today! 🚀

What it Does Automatically checks your Google Calendar to determine if you're officially off work for the rest of today. If so, it auto-sends a personalized out‑of‑office reply via Gmail, telling senders when you’ll be back—based on your next calendar entry within the next 2 weeks. Prerequisites To use this template, you'll need: Gmail credentials (for the trigger and reply nodes) Google Calendar credentials (for both calendar checks) A dedicated work calendar selected in the Calendar nodes Workflow Logic Gmail Trigger Monitors incoming emails every minute Can be filtered (e.g., labels or VIP senders) Calendar Check #1 Inspects if any events remain today Calendar Check #2 If no remaining events, scan the next 14 days for the next event Function Node Formats the return date as Weekday, Month D, YYYY (e.g., “Thursday, July 24, 2025”) Gmail Send Sends a customized out‑of‑office email, using the formatted date Optionally includes n8n attribution (editable) User Setup Instructions Gmail Trigger: Connect your Gmail account and add any desired filters (labels, senders). Google Calendar Nodes: Connect your calendar account and select your “work” calendar in both nodes. Function Node: No changes needed unless you prefer a different date format. Gmail Send Node: Edit the message template and toggle attribution as desired. Customization - Options Edit the final email content and tone in the Send node Adjust calendar lookahead in Calendar Check #2 (default is 14 days) Add Gmail filters to restrict auto-replies (e.g. only specific senders or labels) Why It's Useful Ideal for freelancers, consultants, or remote workers who don’t follow a strict 9–5, yet want automated responses aligned with their actual availability, not a static setting. It’s dynamic, real-time, and easy to tweak. Classification Use Case: Calendar-driven out-of-office automation Recommended audience: Business professionals, freelancers, remote employees

Elevate your Stripe workflows with an AI agent that intelligently, securely, and interactively handles essential Stripe data operations. Leveraging the Kimi K2 model via OpenRouter, this n8n template enables safe data retrieval. From fetching summarized financial insights to managing customer discounts, while strictly enforcing privacy, concise outputs, and operational boundaries. 🧾 Requirements Stripe: Active Stripe account API key with read and write access. n8n: Deployed n8n instance (cloud or self-hosted) OpenRouter: Active OpenRouter account with credit API key from OpenRouter 🔗 Useful Links Stripe n8n Stripe Credentials Setup OpenRouter 🚦 Workflow Breakdown Trigger: User Request Workflow initiates when an authenticated user sends a message in the chat trigger. AI Agent (Kimi K2 OpenRouter): Intent Analysis Determines whether the user wants to: List customers, charges, or coupons Retrieve the account’s balance Create a new coupon in Stripe Filters unsupported or unclear requests, explaining permissions or terminology as needed. Stripe Data Retrieval For data queries: Only returns summarized, masked lists (e.g., last 10 transactions/customers) Sensitive details, such as card numbers, are automatically masked or truncated Never exposes or logs confidential information Coupon Creation When a coupon creation is requested: AI agent collects coupon parameters (discount, expiration, restrictions) Clearly summarizes the action and requires explicit user confirmation before proceeding Creates the coupon upon confirmation and replies with only the public-safe coupon details 🛡️ Privacy & Security No data storage:** All responses are ephemeral; sensitive Stripe data is never retained. Strict minimization:** Outputs are tightly scoped; only partial identifiers are shown and only when necessary. Retention rules enforced:** No logs, exports, or secondary storage of Stripe data. Confirmation required:** Actions modifying Stripe (like coupon creation) always require the user to approve before execution. Compliance-ready:** Aligned with Stripe and general data protection standards. ⏱️ Setup Steps Setup time: 10–15 minutes Add Stripe API credentials in n8n Add the OpenRouter API credentials in n8n and select your desired AI model to run the agent. In our template we selected Kimi K2 from Moonshot AI. ✅ Summary This workflow template connects a privacy-prioritized AI agent (Kimi K2 via OpenRouter) with your Stripe account to enable: Fast, summarized access to customer, transaction, coupon, and balance data Secure, confirmed creation of discounts/coupons Complete adherence to authorization, privacy, and operational best practices 🙋‍♂️ Need Help? Feel free to contact us at 1 Node Get instant access to a library of free resources we created.

How it works Triggers on submitting an n8n form Uses the form details to prepare a message Sends the message to Slack Set up Steps Add in your team name Add in message tone Set up Open AI Set up Slack

Find OAuth URIs with AI Llama Overview: The AI agent identifies: Authorization URI Token URI Audience Methodology: Confidence scoring is utilized to assess the trustworthiness of extracted data: Score Range: 0 < x ≤ 1 Score Granularity: 0.01 increments Model Details: Leveraging the Wayfarer Large 70b Llama 3.3 model. How it works: This template is designed to assist users in obtaining OAuth2 settings using AI-powered insights. It is ideal for developers, IT professionals, or anyone working with APIs that require OAuth2 authentication. By leveraging the AI agent, users can simplify the process of extracting and validating key details such as the authorization_url, token_url, and audience. Set up instructions: 1. Configuration Nodes Structured Output Node**: Parses the AI model's output using a predefined JSON schema. This ensures the data is structured for downstream processing. Code Node**: If the AI model’s output does not match the required format, use the Code node to re-arrange and transform the data. Example code snippets are provided below for common scenarios. 2. AI Model Prompt The prompt for the AI model includes: A detailed structure and objectives of the query. Flexibility for the model to improvise when accurate results cannot be determined. 3. Confidence Scoring The AI model assigns a confidence score (0 < x ≤ 1) to indicate the reliability of the extracted data. Scores are provided in increments of 0.01 for granularity. Adaptability Customize this template: Update the AI model prompt with details specific to your API or OAuth2 setup. Adjust the JSON schema in the Structured Output node to match the data format. Modify the Code logic to suit the application's requirements.

An AI-powered chat assistant that analyzes Azure virtual machine activity and generates detailed timeline reports showing VM state changes, performance metrics, and operational events over time. How It Works The workflow starts with a chat trigger that accepts user queries about Azure VM analysis. A Google Gemini AI agent processes these requests and uses six specialized tools to gather comprehensive VM data from Azure APIs. The agent queries resource groups, retrieves VM configurations and instance views, pulls performance metrics (CPU, network, disk I/O), and collects activity log events. It then analyzes this data to create timeline reports showing what happened to VMs during specified periods, defaulting to the last 90 days unless the user specifies otherwise. Prerequisites To use this template, you'll need: n8n instance (cloud or self-hosted) Azure subscription with virtual machines Microsoft Azure Monitor OAuth2 API credentials Google Gemini API credentials Proper Azure permissions to read VM data and activity logs Setup Instructions Import the template into n8n. Configure credentials: Add Microsoft Azure Monitor OAuth2 API credentials with read permissions for VMs and activity logs Add Google Gemini API credentials Update workflow parameters: Open the "Set Common Variables" node Replace <your azure subscription id here> with your actual Azure subscription ID Configure triggers: The chat trigger will automatically generate a webhook URL for receiving chat messages No additional trigger configuration needed Test the setup to ensure it works. Security Considerations Use minimum required Azure permissions (Reader role on subscription or resource groups). Store API credentials securely in n8n credential store. The Azure Monitor API has rate limits, so avoid excessive concurrent requests. Chat sessions use session-based memory that persists during conversations but doesn't retain data between separate chat sessions. Extending the Template You can add more Azure monitoring tools like disk metrics, network security group logs, or Application Insights data. The AI agent can be enhanced with additional tools for Azure cost analysis, security recommendations, or automated remediation actions. You could also integrate with alerting systems or export reports to external storage or reporting platforms.

n8n Workflow: Invoice PDF Generator This n8n workflow captures invoice data and generates a PDF invoice, ready to be sent or saved. It uses a webhook to trigger the process, preprocesses the invoice data, and converts it to a PDF using HTML and custom styling. @custom-js/n8n-nodes-pdf-toolkit Features: Webhook Trigger**: Receives incoming data, including invoice details. Preprocessing**: Transforms the invoice data into HTML format. HTML to PDF Conversion**: Converts the preprocessed HTML into a styled PDF document. Response**: Sends the generated PDF back to the webhook response. Notice Community nodes can only be installed on self-hosted instances of n8n. Requirements Self-hosted** n8n instance A CustomJS API key for website screenshots. Invoice data** for PDF generation Workflow Steps: Webhook Trigger: Accepts incoming data (e.g., invoice number, recipient details, itemized list). This data is passed to the next node for processing. Set Data Node: Configures initial values for the invoice, including the recipient, sender, invoice number, and the items on the invoice. The invoice details include information like description, unit price, and quantity. Preprocess Node: Processes the raw data to format it correctly for HTML. This includes splitting addresses and converting the items into an HTML table format. HTML to PDF Conversion: Converts the generated HTML into a PDF document. The HTML includes a header, a detailed invoice table, and a footer with contact information. Respond to Webhook: Returns the generated PDF as a response to the initial webhook request. Setup Guide: 1. Configure CustomJS API Sign up at CustomJS. Retrieve your API key from the profile page. Add your API key as n8n credentials. 2. Design Workflow Create a Webhook: Set up a webhook to trigger the workflow when invoice data is received. Prepare Data: Ensure the incoming request contains fields like "Invoice No", "Bill To", "From", and "Details" (list of items with price and quantity). Customize the HTML: The HTML template for the invoice includes custom styling to give the invoice a professional look. Convert to PDF: The HTML to PDF node is configured with the data generated from the preprocessing step to convert the invoice HTML to a PDF format. Example Invoice Data: { "Invoice No": "1", "Bill To": "John Doe\n1234 Elm St, Apt 567\nCity, Country, 12345", "From": "ABC Corporation\n789 Business Ave\nCity, Country, 67890", "Details": [ { "description": "Web Hosting", "price": 150, "qty": 2 }, { "description": "Domain", "price": 15, "qty": 5 } ], "Email": "support@mycompany.com" } Result PDF File

This automated n8n workflow monitors ingredient price changes from external APIs or manual sources, analyzes historical trends, and provides smart buying recommendations. The system tracks price fluctuations in a PostgreSQL database, generates actionable insights, and sends alerts via email and Slack to help restaurants optimize their purchasing decisions. What is Price Trend Analysis? Price trend analysis uses historical price data to identify patterns and predict optimal buying opportunities. The system analyzes price movements over time and generates recommendations on when to buy ingredients based on current trends and historical patterns. Good to Know Price data accuracy depends on the reliability of external API sources Historical data improves recommendation accuracy over time (recommended minimum 30 days) PostgreSQL database provides robust data storage and complex trend analysis capabilities Real-time alerts help capture optimal buying opportunities Dashboard provides visual insights into price trends and recommendations How It Works Daily Price Check - Triggers the workflow daily to monitor price changes Fetch API Prices - Retrieves the latest prices from an external ingredient pricing API Setup Database - Ensures database tables are ready before inserting new data Store Price Data - Saves current prices to the PostgreSQL database for tracking Calculate Trends - Analyzes historical prices to detect patterns and price movements Generate Recommendations - Suggests actions based on price trends (buy/wait/stock up) Store Recommendations - Saves recommendations for future reporting Get Dashboard Data - Gathers necessary data for dashboard generation Generate Dashboard HTML - Builds an HTML dashboard to visualize insights Send Email Report - Emails the dashboard report to stakeholders Send Slack Alert - Sends key alerts or recommendations to Slack channels Database Structure The workflow uses PostgreSQL with two main tables: price_history - Historical price tracking with columns: id (Primary Key) ingredient (VARCHAR 100) - Name of the ingredient price (DECIMAL 10,2) - Current price value unit (VARCHAR 50) - Unit of measurement (kg, lbs, etc.) supplier (VARCHAR 100) - Source supplier name timestamp (TIMESTAMP) - When the price was recorded created_at (TIMESTAMP) - Record creation time buying_recommendations - AI-generated buying suggestions with columns: id (Primary Key) ingredient (VARCHAR 100) - Ingredient name current_price (DECIMAL 10,2) - Latest price price_change_percent (DECIMAL 5,2) - Percentage change from previous price trend (VARCHAR 20) - Price trend direction (INCREASING/DECREASING/STABLE) recommendation (VARCHAR 50) - Buying action (BUY_NOW/WAIT/STOCK_UP) urgency (VARCHAR 20) - Urgency level (HIGH/MEDIUM/LOW) reason (TEXT) - Explanation for the recommendation generated_at (TIMESTAMP) - When recommendation was created Price Trend Analysis The system analyzes historical price data over the last 30 days to calculate percentage changes, identify trends (INCREASING/DECREASING/STABLE), and generate actionable buying recommendations based on price patterns and movement history. How to Use Import the workflow into n8n Configure PostgreSQL database connection credentials Set up external ingredient pricing API access Configure email credentials for dashboard reports Set up Slack webhook or bot credentials for alerts Run the Setup Database node to create required tables and indexes Test with sample ingredient data to verify price tracking and recommendations Adjust trend analysis parameters based on your purchasing patterns Monitor recommendations and refine thresholds based on actual buying decisions Requirements PostgreSQL database access External ingredient pricing API credentials Email service credentials (Gmail, SMTP, etc.) Slack webhook URL or bot credentials Historical price data for initial trend analysis Customizing This Workflow Modify the Calculate Trends node to adjust the analysis period (currently 30 days) or add seasonal adjustments. Customize the recommendation logic to match your restaurant's buying patterns, budget constraints, or supplier agreements. Add additional data sources like weather forecasts or market reports for more sophisticated predictions.