by Amjid Ali
Smart Email Auto-Responder with AI Classification Automatically Categorize and Reply to Emails using LangChain + Google Gemini + Gmail + SMTP + Brevo This n8n workflow is designed to intelligently manage incoming emails and automatically send personalized responses based on the content. It classifies emails using LangChain's Text Classifier, sends HTML responses depending on the category, and updates Gmail and Brevo CRM accordingly. Key Features Triggers and Classifies Emails Listens for new Gmail messages every hour Uses AI-based classification to identify the type of inquiry For Example: Guest Post YouTube Review Udemy Course Inquiry Responds Automatically Sends professional HTML replies customized for each type Uses SMTP to deliver emails from your domain Enhances Workflow with Automation Marks processed emails as read Applies Gmail labels Adds sender to Brevo contact list Optional AI Chat Integration Uses Google Gemini (PaLM 2) to enhance classification or summarization Tools & Integrations Required Gmail account (OAuth2) LangChain (Text Classifier node) Google Gemini API account SMTP credentials (e.g., Gmail SMTP, Brevo, etc.) Brevo/Sendinblue account and API key Step-by-Step Node Guide 1. Gmail Trigger Polls Gmail every hour for new emails. Filters out internal addresses (e.g., @syncbricks.com). Avoids replying to already-responded emails (Re: subject filter). 2. LangChain Text Classifier Uses AI to categorize the content of the email based on pre-defined categories: Guest Post** Youtube** Udemy Courses** 3. Google Gemini (PaLM) Chat Model (Optional) Provides additional AI support to enhance classification accuracy. Can be used to summarize or enrich the context if needed. 4. Email Send Nodes Each response category has a separate SMTP node with a custom HTML email: Guest Post Inquiry** YouTube Video Inquiry** Udemy Course Inquiry** 5. Gmail: Mark as Read Marks the email so it isn’t processed again. 6. Gmail: Apply Label Adds a label (e.g., Handled by Bot) for organization. 7. Brevo: Create/Update Contact Saves the sender to your CRM for future communication or marketing. Email Templates Included Guest Post Template Includes pricing, website list, submission guidelines, and payment instructions. YouTube Review Template Includes package pricing, review samples, video thumbnails, and inquiry instructions. Step by Step Tutorial GET n8n Now N8N COURSE n8n Book More courses: http://lms.syncbricks.com YouTube Channel: https://youtube.com/@syncbricks How to Use Import the template into your n8n instance. Configure your Gmail OAuth2 and SMTP credentials. Set up your LangChain Text Classifier and Google Gemini API credentials. Update label ID in the Gmail node and ensure all custom fields like from.value[0].name match your use case. Run the workflow and watch it respond intelligently to new inquiries. Best Practices Always test with mock emails first. Keep the Google Gemini node optional if you want to reduce cost/API calls. Use Gmail filters to auto-label certain types of emails. Monitor your Brevo contacts to track new leads. Attribution & Support Developed by Amjid Ali This template took extensive time and effort to build. If you find it useful, please consider supporting my work. Buy My Book: Mastering n8n on Amazon Full Courses & Tutorials: http://lms.syncbricks.com Follow Me Online: LinkedIn: https://linkedin.com/in/amjidali Website: https://amjidali.com YouTube: https://youtube.com/@syncbricks
by WeblineIndia
This workflow automatically forwards incoming Gmail emails to a Telegram chat only if the email subject contains specific keywords (like "Urgent" or "Server Down"). The workflow extracts key details such as the sender, subject, and message body, and sends them as a formatted message to a specified Telegram chat. This is useful for real-time notifications, security alerts, or monitoring important emails directly from Telegram — filtering out unnecessary emails. Prerequisites: Before setting up the workflow, ensure the following: The Gmail API should be enabled. Create a bot using @BotFather and obtain the API key. Retrieve the telegram Chat ID (for personal messages or group messages). Set up OAuth2 for Gmail and use the Bot Token for Telegram. Customisation Options : Modify the subject keywords in the IF Node to change the filtering criteria. Customize how the email details appear in Telegram (bold subject, italic body, etc.). Extend the workflow to include email attachments in Telegram. Steps : Step 1: Gmail Trigger Node (On Message Received) Select "Gmail Trigger" and add it to the workflow. Authenticate with your Google Account. Set Trigger Event to "Message Received". (Optional) Add filters for specific senders, labels, or subjects. Click "Execute Node" to test the connection. Click "Save". Step 2: IF Node (Conditional Filtering) Add an "IF" Node after the Gmail Trigger. Configure the condition to check if the email subject contains specific keywords (e.g., "Urgent", "Server Down", "Alert"). If the condition is true, proceed to the next step. If false, you can stop or route it elsewhere (optional). Step 3: Telegram Node (Send Message Action) Click "Add Node" and search for Telegram. Select "Send Message" as the action. Authenticate using your Telegram Bot Token. Set the Chat ID (personal or group chat). Format the message using email details received from the email trigger node and set the message in text. Steps 4. Connect & Test the Workflow Link Gmail Trigger → if node → Telegram Send Message. Save and execute the workflow manually. Send a test email to your Gmail account. Verify if the email details appear in your Telegram chat. About the Creator, WeblineIndia This workflow is created by the Agentic business process automation developers at WeblineIndia. We build automation and AI-driven tools that make life easier for your team. If you’re looking to hire dedicated developers who can customize workflows around your business, we’re just a click away.
by Samir Saci
Tags: Productivity, Pomodoro, Organization Context Hey! I’m Samir, a Supply Chain Engineer and Data Scientist from Paris, founder of LogiGreen Consulting 🌱 A significant improvement in my productivity came from following the Pomodoro Technique. What is the Pomodoro Technique? The Pomodoro Technique is a time management method that breaks your workday into 25-minute focus intervals followed by short breaks. After 4 cycles, you take a longer break to recharge. It helps maintain concentration while preventing burnout. I’ve used this technique with web apps to receive break/work notifications. But I always wished I had a way to track my sessions for self-assessment. > Let’s use n8n to boost our productivity and log our deep work sessions automatically! 📬 For business inquiries, you can add me on Here Who Is This Template For? I built this workflow for creators, freelancers, students, and professionals who love the Pomodoro technique but want more than just timers — they want data. This template helps you: Track every deep work session automatically Store logs in Google Sheets for later analysis Stay in control via Telegram commands There is no need to pay for premium apps. It’s all free and powered by n8n. How Does It Work? This Telegram bot tracks your Pomodoro sessions and sends you alerts during the process. Here’s what happens: A user sends /start to the bot. It launches a 25-minute deep work timer. After 25 minutes, the bot sends a break reminder. After four cycles, a long break is triggered and the session is logged. The session is automatically recorded to Google Sheets with (Date & Time, User ID, Pomodoro count, Session ID, Duration of focus and breaks) What Gets Tracked? | Field | Description | |-------------------|--------------------------------------| | Date & Time | When the session was logged | | User ID | Your Telegram ID | | Block Type | Deep Work or Short Break | Pomodoro Count | Number of cycles completed | | Working Session ID | Unique ID for each session | | Focus Duration | Length of each deep work session | | Break Duration | Short or long break info | You can use this workflow as a base to bring additional features like: Connecting with tasks from Google Task Send automated productivity reports to monitor your activity Link a Pomodoro with a task using Google Calendar What Do I Need to Start? This workflow is beginner-friendly — no coding required. Google Drive API* and *Google Sheet API** credentials A Google Sheet set up to log sessions (with the columns of the table above) API Credentials: Google Sheets API (OAuth2) Telegram Bot Token Telegram app to chat with the bot > The template is plug-and-play. Just follow the sticky notes in the n8n editor to configure it. Next Steps Follow the sticky notes in the n8n workflow editor to: Set your credentials Connect your Google Sheet Initialize the static data Launch your first /start command on Telegram 🎥 Watch My Tutorial 🚀 Curious how n8n can supercharge productivity and learning skills?? 📬 Let’s connect on LinkedIn This workflow has been created with N8N 1.82.1 Submitted: March 24th, 2025
by Friedemann Schuetz
Update 19-04-2025 Change from OpenAI to Claude 3.7 Sonnet module Adding the Think Tool The update enables significantly better results to be achieved. This is particularly noticeable during longer meetings! What this workflow does This workflow retrieves the Zoom meeting data from the last 24 hours. The transcript of the last meeting is then retrieved, processed, a summary is created using AI and sent to all participants by email. AI is then used to create tasks and follow-up appointments based on the content of the meeting. Important: You need a Zoom Workspace Pro account and must have activated Cloud Recording/Transcripts! This workflow has the following sequence: manual trigger (Can be replaced by a scheduled trigger or a webhook) retrieval of of Zoom meeting data filter the events of the last 24 hours retrieval of transcripts and extract of the text creating a meeting summary, format to html and send per mail create tasks and follow-up call (if discussed in the meeting) in ClickUp/Outlook (can be replaced by Gmail, Airtable, and so forth) via sub workflow Requirements: Zoom Workspace (via API and HTTP Request): Documentation Microsoft Outlook: Documentation ClickUp: Documentation AI API access (e.g. via OpenAI, Anthropic, Google or Ollama) SMTP access data (for sending the mail) You must set up the individual sub-workflows as separate workflows. Then set the “Execute workflow trigger” here. Then select the corresponding sub-workflow in the AI Agent Tools. You can select the number of domains yourself. If the data queries are not required, simply delete the corresponding tool (e.g. “Analytics_Domain_5). Feel free to contact me via LinkedIn, if you have any questions!
by Md. Nazmul Islam
AI-Powered MCQ Quiz Generator from YouTube Videos Transform any YouTube video into an interactive MCQ quiz automatically! This workflow uses Google Gemini AI to analyze video content and generate comprehensive multiple-choice questions with automatic grading - perfect for educators, trainers, and content creators. Who is this For This workflow is perfect for: Educators** creating quizzes from educational YouTube content Corporate Trainers** developing assessments from training videos Content Creators** engaging their audience with interactive quizzes Students** testing their knowledge on video lectures Online Course Creators** building assessments from video content Features AI Video Analysis**: Google Gemini 2.5 Flash analyzes entire YouTube videos (up to 50 minutes) Dynamic Question Generation**: Creates up to 90 MCQ questions with 3 options each Automatic Form Creation**: Generates Google Forms with quiz functionality Smart Grading**: Built-in correct answer identification and scoring Error Handling**: Robust error management with user feedback How It Works User Input via n8n Web Form: Form Name (Quiz Title) Email Address YouTube Video URL Number of Questions (1-90) AI Processing Pipeline: Google Gemini analyzes the YouTube video content AI extracts key concepts and generates relevant questions Structured output parser formats questions into JSON Google Forms Integration: Automatically creates a new Google Form Adds all generated questions with multiple choice options Configures quiz settings with correct answers and scoring Completion & Access: User receives direct link to the generated quiz Form ready for immediate use or sharing Video Demo: See this youtube Video to explore "how it works". Set Up Steps Import the Workflow Create a new workflow in n8n Import the JSON file by clicking "three dots" (upper right corner) > "Import from file..." Configure Google Gemini API Get your Google AI Studio API key from Google AI Studio On “HTTP Request to Gemini” node replace the “API_KEY” from url with your API key. Create a "Google Gemini (PaLM) API" credential in n8n Add your API key to the credential Connect the credential to the "Google Gemini Chat Model" node Set Up Google Forms Integration Enable Google Forms API in Google Cloud Console Create a "Google OAuth2 API" credential in n8n Authorize the credential with Forms permissions Connect the credential to both HTTP Request nodes (“Create a Google Form” node and “Create MCQ Quizzes” node) Configure Form Trigger The workflow includes a built-in form trigger No additional setup needed - the form URL will be generated automatically Customize form fields if needed in the “Input YouTube URL" node Test the Workflow Activate the workflow Submit the form to generate a test quiz Verify the Google Form is created successfully Pre-requisites Necessary Accounts:** Google Account (for Forms API access) Google AI Studio Account (for Gemini API access) n8n Instance (cloud or self-hosted) API Access:** Google Forms API enabled Google drive API enabled Google Generative AI API access Valid API keys and OAuth credentials N8N Requirements:** n8n version 1.95.2 or higher LangChain nodes package installed Internet access for API calls Customization Guidance Question Generation Prompts: Modify the prompt in "Set Prompt and model" node for different question styles Adjust difficulty levels or focus areas Change question format (True/False, Fill-in-blanks, etc.) Form Customization: Update form title and description templates Add additional input fields (difficulty level, subject area) Customize success/error messages Advanced Features You Can Add: Email Notifications: Send quiz links via email Analytics Integration: Track quiz performance and completion rates Multi-language Support: Generate quizzes in different languages Question Bank Storage: Save generated questions to a database Batch Processing: Generate multiple quizzes from a YouTube playlist Error Handling Enhancements: Add retry logic for API failures Implement fallback question generation Create detailed error logging Technical Specifications Video Length**: Up to 50 minutes supported Question Limit**: 1-90 questions per quiz Processing Time**: 2-10 minutes depending on video length Supported Formats**: YouTube videos (public and unlisted) Output Format**: Google Forms with automatic grading Limitations & Considerations YouTube video must be publicly accessible or unlisted Processing time increases with video length and question count API rate limits may apply for high-volume usage Some complex visual content may not be fully analyzed Ready to Transform Videos into Quizzes? This workflow streamlines the entire process from video analysis to quiz deployment. Perfect for educators and trainers looking to create engaging assessments from video content quickly and efficiently.
by Harshil Agrawal
This workflow demonstrates the use of $runIndex expression. It demonstrates how the expression can be used to avoid an infinite loop. The workflow will create 5 Tweets with the content 'Hello from n8n!'. You can use this workflow by replacing the Twitter node with any other node(s) and updating the condition in the IF node.
by Alfonso Corretti
Gmail to Vector Embeddings with PGVector and Ollama Who is this for? Everyone! Did you dream of asking an AI "what hotel did I stay in for holidays last summer?" or "what were my marks last semester like?". Dream no more, as vector similarity searches and this workflow are the foundations to make it possible (as long as the information appears in your e-mails 😅). 100% local This workflow is designed to use locally-hosted open source. Ollama as LLM provider, nomic-embed-text as the embeddings model, and pgvector as the vector database engine, on top of Postgres. But.. how?! Firstly, specify the date you created your Gmail account on, then manually run the workflow in order to bulk read all your e-mail in monthly batches. Your database is now populated! Now it's the task for other workflows to query the vector database. Activate the workflow so that new e-mail is continuously added by the Gmail Trigger upon receiving it. Structured AND Vectorized This workflow stores your e-mail activity in two ways: In a structured table In a vector embeddings table And the information in both of them can be correlated by Gmail's messages id, which is stored in the vectors table as metadata property emails_metadata.id. That way consumers can benefit from both worlds! ✨ Vector similarity searches enable semantic searches, while structured queries can retrieve more factual data like the message id, its date or who it came from. Other useful templates My template Chat with Your Email History using Telegram, Mistral and Pgvector for RAG is a ready-made solution to consume this workflow. You may also pair this workflow with my other template to Email Assistant: Convert Natural Language to SQL Queries with Phi4-mini and PostgreSQL and you'll enable RAG workflows that use both structured and vectorized databases. Customizations I suppose the e-mail provider could be changed, but then you'd have to identify an alternative id field. Message-ID would be a more standard option. There are a few opinionated choices as to what metadata to store, but those shouldn't need adjustments.
by Lucas Perret
This node is designed to cleanse URLs and extract their domain names efficiently. It effectively handles a wide range of URL formats, including those with unconventional or complex top-level domains (TLDs), such as 'co.uk'. You can also use it to extract the domain from an email. The node will also check if the domain is from a free email provider (gmail.com / outlook.com...etc) or not. How It Works The node analyzes the provided URL, removing any unnecessary elements. It then identifies and extracts the domain name, ensuring compatibility with a diverse array of TLDs. The node utilizes an extensive list of TLDs to guarantee accurate domain extraction for virtually any URL. To view the complete list of supported top-level domains, please visit: TLD List on GitHub How to use it Call this workflow using the "execute workflow" node You can pass either an email variable or a url variable. For email, the node also detect free mail provider such as Yahoo / Google...etc
by Aitor | 1Node
Talk to Your Apps: Building a Personal Assistant MCP Server with Google Gemini Wouldn't it be cool to just tell your computer or phone to "schedule a meeting with Sarah next Tuesday at 3 PM" or "find John Doe's email address" and have it actually do it? That's the dream of a personal assistant! With n8n and the power of MCP and AI models like Google Gemini, you can actually build something pretty close to that. We've put together a workflow that shows you how you can use a natural language chat interface to interact with your other apps, like your CRM, email, and calendar. What You Need to Get Started Before you dive in, you'll need a few things: n8n:** An n8n instance (either cloud or self-hosted) to build and run your workflow. Google Gemini Access:** Access to the Google Gemini model via an API key. Credentials for Your Apps:** API keys or login details for the specific CRM, Email, and Calendar services you want to connect (like Google Sheets for CRM, Gmail, Google Calendar, etc., depending on your chosen nodes). A Chat Interface:** A way to send messages to n8n to trigger the workflow (e.g., via a chat app node or webhook). How it Works (In Simple Terms) Imagine this workflow is like a helpful assistant who sits between you and your computer. Step 1: You Talk, the AI Agent Listens It all starts when you send a message through your connected chat interface. Think of this as you speaking directly to your assistant. Step 2: The Assistant's Brain (Google Gemini) Your message goes straight to the assistant's "brain." In this case, the brain is powered by a smart AI model like Google Gemini. In our template we are using the latest Gemini 2.5 Pro. But this is totally up to you. Experiment and track which model fits the kind of tasks you will pass to the agent. Its job is to understand exactly what you're asking for. Are you asking to create something? Are you asking to find information? Are you asking to update something? The brain also uses a "memory" so it can remember what you've talked about recently, making the conversation feel more natural. We are using the default context window, which is the past 5 interactions. Step 3: The Assistant Decides What Tool to Use Once the brain understands your request, the assistant figures out the best way to help you. It looks at the request and thinks, "Okay, to do this, I need to use one of my tools." Step 4: The Assistant's Toolbox (MCP & Your Apps) Here's where the "MCP" part comes in. Think of "MCP" (Model Context Protocol) as the assistant's special toolbox. Inside this toolbox are connections to all the different apps and services you use – your CRM for contacts, your email service, and your calendar. The MCP system acts like a manager for these tools, making them available to the assistant whenever they're needed. Step 5: Using the Right Tool for the Job Based on what you asked for, the assistant picks the correct tool from the toolbox. If you asked to find a contact, it grabs the "Get Contact" node from the CRM section. If you wanted to schedule a meeting, it picks the "Create Event" node from the Calendar section. If you asked to draft an email, it uses the "Draft Email" node. Step 6: The Tool Takes Action Now, the node or set of nodes get to work! It performs the action you requested within the specific app. The CRM tool finds or adds the contact. The Email tool drafts the message. The Calendar tool creates the event. Step 7: Task Completed! And just like that, your request is handled automatically, all because you simply told your assistant what you wanted in plain language. Why This is Awesome This kind of workflow shows the power of combining AI with automation platforms like n8n. You can move beyond clicking buttons and filling out forms, and instead, interact with your digital life using natural conversation. n8n makes it possible to visually build these complex connections between your chat, the AI brain, and all your different apps. Taking it Further (Possible Enhancements) This is just the start! You could enhance this personal assistant by: Connecting more apps and services (task managers, project tools, etc.). Adding capabilities to search the web or internal documents. Implementing more sophisticated memory or context handling. Getting a notification when the AI agent is done completing each task such as in Slack or Microsoft Teams. Allowing the assistant to ask clarifying questions if needed. Building a robust prompt for the AI agent. Ready to Automate Your Workflow? Imagine the dozens of hours your team could save weekly by automating repetitive tasks through a simple, natural language interface. Need help? Feel free to contact us at 1 Node. Get instant access to a library of free resources we created.
by Davide
This workflow allows users to convert a 2D image into a 3D model by integrating multiple AI and web services. The process begins with a user uploading or providing an image URL, which is then sent to a generative AI model capable of interpreting the content and generating a 3D representation in .glb format. The model is then stored and a download link is returned to the user. Main Steps Trigger Node: Initiates the workflow either via HTTP request, webhook, or manual execution. Image Upload or Input: The image is acquired via direct upload or URL input. API Integration: The image is sent to a 3D generation API (e.g., a service like Kaedim, Luma Labs, or a custom AI model). Model Generation: The external API processes the image and creates a 3D model. File Storage: The resulting 3D model is stored in cloud storage (e.g., S3, Google Drive, or a local server). Response to User: A download link for the 3D model is returned to the user via the same communication channel (HTTP response, email, or chat). Advantages Automation**: Eliminates the need for manual 3D modeling, saving time for artists, developers, and designers. AI-Powered**: Leverages AI to generate realistic and usable 3D models from simple 2D inputs. Scalability**: Can be triggered automatically and scaled up to handle many requests via n8n's automation. Integration-Friendly**: Easily extendable with other services like Discord, Telegram, or marketplaces for 3D assets. No-Code Configuration**: Built with n8n’s visual interface, making it editable without programming knowledge. How It Works Trigger: The workflow can be started manually ("When clicking ‘Test workflow’") or automatically at scheduled intervals ("Schedule Trigger"). Data Retrieval: The "Get new image" node fetches data from a Google Sheet, including the model image, product image, and product ID. 3D Image Creation: The "Create 3D Image" node sends the image data to the Fal.run API (Trellis) to generate a 3D model. Status Check: The workflow periodically checks the request status ("Get status" and "Wait 60 sec.") until the job is marked as "COMPLETED." Result Processing: Once completed, the 3D model URL is retrieved ("Get Url 3D image"), the file is downloaded ("Get File 3D image"), and uploaded to Google Drive ("Upload 3D Image"). Sheet Update: The final 3D model URL is written back to the Google Sheet ("Update result"). Set Up Steps Prepare Google Sheet: Create a Google Sheet with columns: IMAGE MODEL and 3D RESULT (empty). Example sheet: Google Sheet Template. Obtain Fal.run API Key: Sign up at Fal.ai and get an API key. Configure the Authorization header in the "Create 3D Image" node with Key YOURAPIKEY. Configure Workflow Execution: Run manually via the Test workflow button. For automation, set up the Schedule Trigger node (e.g., every 5 minutes). Verify Credentials: Ensure Google Sheets, Google Drive, and Fal.run API credentials are correctly set in n8n. Once configured, the workflow processes new entries in the Google Sheet, generates 3D models, and updates the results automatically. Need help customizing? Contact me for consulting and support or add me on Linkedin.
by Sirhexalot
This n8n workflow enables you to export data from Zammad, including Users, Roles, Groups, and Organizations, into individual Excel files. It simplifies data handling and reporting by creating structured outputs for further processing or sharing. Features Export Users with associated details such as email, firstname, lastname, role_ids, and group_ids. Export Roles and Organizations with their respective identifiers and names. Convert all data into separate Excel files for easy access and use. Usage Import this workflow into your n8n instance. Configure the required Zammad API credentials (zammad_base_url and zammad_api_key) in the Basic Variables node. Run the workflow to generate Excel files containing Zammad data. Issues and Suggestions If you encounter any issues or have suggestions for improvement, please report them on the GitHub repository. We appreciate your feedback to help enhance this workflow!
by Zacharia Kimotho
What problem is this workflow solving? This workflow is aimed for email marketing enthusiasts looking for an easy way to either extract the domain from an email ad also check if the syntax is correct without having to use the code node. How this works For this to work, replace the debugger node with your actual data source. Map your data at match the above layout Run your workflow and check for all the emails that are either valid or not Once done, you will have a list of all your emails, domains, and whether they are valid or not.