Workflow Templates

This template is for self-hosted n8n instances only. This n8n demonstrates how to build a simple FileSystem MCP server. Connecting to this server allows MCP clients and agents to list, read and create directories and files on the local machine or remote server. This MCP example is based off an official MCP reference implementation which can be found here -https://github.com/modelcontextprotocol/servers/tree/main/src/filesystem How it works A MCP server trigger is used and connected to 5 tools: 3 Execute Command tools and 2 custom workflow tools. The 3 Execute Command tools allow for listing, searching and creating directories. The 2 custom workflow tools are for reading and writing files to disk. Special care has been to not allow the MCP agent to execute arbitrary linux commands on the target server. This is achieved by only allowing the agent to provide parameters such as filenames and paths rather than raw commands. How to use This Filesystem MCP server will write to the server which hosts the n8n instance - this can be your local machine or a remove server. If your target filesystem is on neither, then modify the commands to connect to the desired server. Connect your MCP client by following the n8n guidelines here - https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-langchain.mcptrigger/#integrating-with-claude-desktop Try the following queries in your MCP client: "Please help me list all folders under the project directory." "Help me create a bash script to send a notification to Slack." "Search for the log file on the 22nd April and read its contents. What was the cause of the outage?" Requirements Linux file system for this example template. Feel free to modify if working on Windows. MCP Client or Agent for usage such as Claude Desktop - https://claude.ai/download Customising this workflow Implement the moving and renaming of files by adding more custom workflow tools to the MCP server. Remember to set the MCP server to require credentials before going to production and sharing this MCP server with others!

Scrape Latest 20 TechCrunch Articles Who is this for? This workflow is designed for developers, researchers, and data analysts who need to track the latest trending repositories on GitHub. It is useful for anyone who wants to stay updated on popular open-source projects without manually browsing GitHub’s trending page. What problem is this workflow solving? Manually checking GitHub’s trending repositories daily can be time-consuming and inefficient. This workflow automates the extraction of trending repositories, providing structured data including repository name, author, description, programming language, and direct repository links. What this workflow does This workflow scrapes the trending repositories from GitHub’s trending page and extracts essential metadata such as repository names, languages, descriptions, and URLs. It processes the extracted data and structures it into an easy-to-use format. Setup Ensure you have n8n installed and configured. Import this workflow into your n8n instance. Run the workflow manually or schedule it to execute at regular intervals. (Optional) Customize the extracted data or integrate it with other systems. How to customize this workflow to your needs Modify the HTTP request node to target different GitHub trending categories (e.g., specific programming languages). Add further processing steps such as filtering repositories by stars, forks, or specific keywords. Integrate this workflow with Slack, email, or a database to store or notify about trending repositories. Workflow Steps Trigger execution manually using the "When clicking ‘Test workflow’" node. Send an HTTP request to fetch GitHub’s trending page using "Request to Github Trend". Extract the trending repositories box from the HTML response using "Extract Box". Extract all repository data including names, authors, descriptions, and languages using "Extract all repositories". Convert extracted data into a structured list for easier processing using "Turn to a list". Extract detailed repository information using "Extract repository data". Format and set variables to ensure clean and structured data output using "Set Result Variables". Note: Since GitHub’s trending page updates dynamically, ensure you run this workflow periodically to capture the latest trends.

🧠 Problem This Solves Managing credit card expenses can be tricky, especially when you want to stay transparent and keep your spouse in the loop. Most banks don't offer real-time notification sharing with family members, and manually updating expenses takes time and effort. This n8n workflow automates the entire process: tracking your HDFC credit card usage, logging it in Google Sheets, and sending an instant Telegram notification to your spouse. 👥 Who This Template Is For Couples who want shared visibility of credit card spending Individuals looking for automated personal finance tracking Anyone using HDFC Credit Card with email alerts enabled n8n users who want to integrate Gmail, Google Sheets, and Telegram ⚙️ Workflow Breakdown Here’s how the automation works: Gmail Trigger – Monitors your Gmail inbox for credit card transaction alerts from HDFC Bank. Email Parser – Extracts transaction details like amount, merchant name, date, and card type. Google Sheets Node – Logs the parsed transaction data into a structured Google Sheet for record-keeping. Telegram Node – Sends a message to your wife’s Telegram account with transaction details for instant notification. 🛾 Step-by-Step Setup Instructions Prerequisites An HDFC Credit Card with email alerts enabled A Gmail account connected to n8n A Google Sheet created with columns like Date, Amount, Merchant, Card, etc. A Telegram Bot and your wife’s Telegram Chat ID Set up Gmail Trigger Use the Gmail Trigger Node to monitor incoming emails from alerts@hdfcbank.net or similar. Filter emails with subject line containing keywords like Credit Card Transaction Alert. Extract Email Content Use the HTML Extract or Regex node to parse out transaction amount, merchant name, date, and card number from the email body. Log to Google Sheets Connect your Google Sheets account in n8n Use the Append Row node to add each transaction as a new row in your finance sheet. Send Telegram Message Set up a Telegram Bot and get the Chat ID of your wife’s Telegram account Format a message like: "💳 HDFC Transaction Alert: ₹5,000 at Amazon on 17 May via XXXX1234" Send it via the Telegram node 🛠️ Customization Tips 💡 Add Spending Limits: Add a condition node to alert only if the transaction exceeds a certain amount. 🧾 Category Mapping: Use additional logic to classify expenses (e.g., Shopping, Dining) based on keywords. 📊 Weekly Summary: Create another workflow that sends a weekly Telegram summary using data from Google Sheets. 🔐 Security Tip: Mask part of the card number before sending the Telegram message for added security.

This workflow automatically sends you a list of your daily meetings every morning via a Telegram bot. Use Cases: This workflow is useful for anyone who wants to be automatically informed of their daily meetings, especially for busy professionals, students, and anyone with a hectic schedule. Setup: Google Calendar connected to n8n A Telegram bot created and connected to n8n Your Telegram user ID specified Notes: You need to replace the placeholder in the Telegram node with your actual Telegram user ID. You can customize the formatting of the Telegram message in the JavaScript Code node.

🎤 Audio-to-Insights: Auto Meeting Summarizer Transform your meeting recordings into actionable insights automatically. This powerful n8n workflow monitors your Google Drive for new audio files, transcribes them using OpenAI's Whisper, generates intelligent summaries with ChatGPT, and logs everything in Google Sheets - all without lifting a finger. 🔄 How It Works This workflow operates as a seamless 6-step automation pipeline: Step 1: Smart Detection The workflow continuously monitors a designated Google Drive folder (polls every minute) for newly uploaded audio files. Step 2: Secure Download When a new audio file is detected, the system automatically downloads it from Google Drive for processing. Step 3: AI Transcription OpenAI's Whisper technology converts your audio recording into accurate text transcription, supporting multiple audio formats. Step 4: Intelligent Summarization ChatGPT processes the transcript using a specialized prompt that extracts: Key discussion points and decisions Action items with assigned persons and deadlines Priority levels and follow-up tasks Clean, professional formatting Step 5: Timestamp Generation The system automatically adds the current date and formats it consistently for tracking purposes. Step 6: Automated Logging The final summary is appended to your Google Sheets document with the date, creating a searchable archive of all meeting insights. ⚙️ Setup Steps Prerequisites Before setting up the workflow, ensure you have: Active Google Drive account OpenAI API key with credits Google Sheets access n8n instance (cloud or self-hosted) Configuration Steps 1. Credential Setup Google Drive OAuth2**: Required for folder monitoring and file downloads OpenAI API Key**: Needed for both transcription (Whisper) and summarization (ChatGPT) Google Sheets OAuth2**: Essential for writing summaries to your spreadsheet 2. Google Drive Configuration Create a dedicated folder in Google Drive for meeting recordings Copy the folder ID from the URL (the long string after /folders/) Update the folderToWatch parameter in the workflow 3. Google Sheets Preparation Create a new Google Sheet or use an existing one Ensure it has columns: Date and Meeting Summary Copy the spreadsheet ID from the URL Update the documentId parameter in the workflow 4. Audio Requirements Supported Formats**: MP3, WAV, M4A, MP4 Recommended Size**: Under 100MB for optimal processing Language**: Optimized for English (customizable for other languages) Quality**: Clear audio produces better transcriptions 5. Workflow Activation Import the workflow JSON into your n8n instance Configure all credential connections Test with a sample audio file Activate the workflow trigger 🚀 Use Cases Project Management Team Standup Summaries**: Convert daily standups into actionable task lists Sprint Retrospectives**: Extract improvement points and action items Stakeholder Updates**: Generate concise reports for leadership Sales & Customer Success Discovery Call Notes**: Capture prospect pain points and requirements Demo Follow-ups**: Track questions, objections, and next steps Customer Check-ins**: Monitor satisfaction and expansion opportunities Consulting & Professional Services Client Strategy Sessions**: Document recommendations and implementation plans Requirements Gathering**: Organize complex project specifications Progress Reviews**: Track deliverables and milestone achievements HR & Training Interview Debriefs**: Standardize candidate evaluation notes Training Sessions**: Create searchable knowledge bases Performance Reviews**: Document development plans and goals Research & Development Brainstorming Sessions**: Capture innovative ideas and concepts Technical Reviews**: Log decisions and architectural choices User Research**: Organize feedback and insights systematically 💡 Advanced Customization Options Enhanced Summarization Modify the ChatGPT prompt to focus on specific elements: Add speaker identification for multi-person meetings Include sentiment analysis for customer calls Generate department-specific summaries (technical, sales, legal) Extract financial figures and metrics automatically Integration Expansions Slack Integration**: Auto-post summaries to relevant channels Email Notifications**: Send summaries to meeting participants CRM Updates**: Push action items directly to Salesforce/HubSpot Calendar Integration**: Schedule follow-up meetings based on action items Quality Improvements Audio Preprocessing**: Add noise reduction before transcription Multi-language Support**: Configure for international teams Custom Templates**: Create industry-specific summary formats Approval Workflows**: Add human review before final storage 🛠️ Troubleshooting & Best Practices Common Issues Large File Processing**: Split recordings over 100MB into smaller segments Poor Audio Quality**: Use noise reduction tools before uploading API Rate Limits**: Implement delay nodes for high-volume usage Formatting Issues**: Adjust ChatGPT prompts for consistent output Optimization Tips Upload files in supported formats only Ensure stable internet connection for cloud processing Monitor OpenAI API usage and costs Regularly backup your Google Sheets data Test workflow changes with sample files first 📊 Expected Outputs Sample Summary Format: Meeting Summary - March 15, 2024 Key Discussion Points: Q1 budget review and allocation decisions New product launch timeline and milestones Team restructuring and role assignments Action Items: John: Finalize budget proposal by March 20th (High Priority) Sarah: Schedule product demo sessions for March 25th Team: Submit org chart feedback by March 18th Decisions Made: Approved additional marketing budget of $50K Delayed product launch to April 15th for quality assurance Promoted Lisa to Senior Developer role 📞 Questions & Support For any questions, customizations, or technical support regarding this workflow: 📧 Email Support Primary Contact**: Yaron@nofluff.online Response Time**: Within 24 hours on business days Best For**: Setup questions, customization requests, troubleshooting 🎥 Learning Resources YouTube Channel**: https://www.youtube.com/@YaronBeen/videos Step-by-step setup tutorials Advanced customization guides Workflow optimization tips 🔗 Professional Network LinkedIn**: https://www.linkedin.com/in/yaronbeen/ Connect for ongoing support Share your workflow success stories Get updates on new automation ideas 💡 What to Include in Your Support Request Describe your specific use case Share any error messages or logs Mention your n8n version and setup type Include sample audio file characteristics (if relevant) Ready to transform your meeting chaos into organized insights? Download the workflow and start automating your meeting summaries today!

Inquiry Form to Personalised WhatsApp Message Overview This workflow creates a smart, automated system for capturing leads from an inquiry form, initiating personalized WhatsApp message via Unipile API, and updating your Google Sheet CRM. It uses AI to craft initial outreach messages and logs the success or failure of each message sent, ensuring you track every lead effectively. This automation helps you engage leads quickly and efficiently, without manual effort. Use Case This workflow is ideal for: Sales Teams**: Automate the first touchpoint with new leads, qualifying them and initiating conversations. Small Businesses**: Provide immediate, personalized responses to inquiries, enhancing customer experience. Customer Support**: Quickly gather more context from users after they fill out a help form. Lead Generation**: Streamline the process from form submission to active lead engagement and CRM tracking. How It Works Form Submission Trigger: The workflow is activated when someone submits an "Inquiry Form." This form collects essential lead details such as: Full Name Email WhatsApp number Company Name "How can we help you?" (a notes field) AI Crafts Personalized Message: An OpenAI node, acting as "Alex" (a friendly, approachable human assistant), generates a short, personalized, and engaging opening message for the lead. This message directly addresses the lead by their first name and includes an open-ended question to encourage them to share more details about their needs. WhatsApp Outreach: The AI then uses the WhatsApp API (via Unipile) to send this personalized message directly to the lead's WhatsApp number. Unipile is key here, as it allows sending messages without prior chat history and can connect to your personal WhatsApp. Log Success or Failure: The AI checks the response from the WhatsApp API. If the WhatsApp message is sent successfully: The lead's details, along with the personalized message, WhatsApp chat ID, and message ID, are logged into a "Successful" sheet in your Google Sheet CRM. If the WhatsApp message fails to send: The lead's information, the attempted message, and the reason for failure are logged into a "Failed" sheet in your Google Sheet CRM. This helps you identify and follow up on problematic leads. How to Set It Up To set up your Lead Capture Agent, follow these steps: Google Sheet Setup: Copy the Template: Make a copy of the provided Google Sheet Template ("Sales Agent" with "Successful" and "Failed" sheets) into your own Google Drive. Connect Google Sheets: Ensure your Google Sheets OAuth2 API credentials are set up in n8n and linked to the "Google Sheets" and "Google Sheets3" nodes. Update Sheet IDs: In both "Google Sheets" and "Google Sheets3" nodes, update the documentId with the ID of your copied "Sales Agent" Google Sheet. Unipile (WhatsApp API) Credentials: Sign up for Unipile: Get your DSN and API key from Unipile (they offer a 7-day free trial). Replace Placeholders: In the "Whatsapp API" node, replace <YOUR_DSN>, <YOUR_API_KEY>, and <YOUR_ACCOUNT_ID> with your actual Unipile credentials. OpenAI API Key: Connect your OpenAI API key as an API credential in n8n and link it to the "OpenAI" node. Inquiry Form Setup: The "Enquiry Form" node generates a public webhook URL. You can embed this form on your website or share the URL directly. Alternatively, if you use your own form solution, configure it to send data via a webhook to the URL provided by the "Enquiry Form" node. Import the Workflow: Import the provided workflow JSON into your n8n instance. Activate and Test: Once all settings are complete, activate the workflow. Test it by submitting a new entry through the "Inquiry Form." Check your Google Sheet to see the lead captured and the message status. This workflow is designed to ensure no lead falls through the cracks, giving your sales or support team a powerful edge!

This n8n demonstrates how to build a simple PostgreSQL MCP server to manage your PostgreSQL database such as HR, Payroll, Sale, Inventory and More! This MCP example is based off an official MCP reference implementation which can be found here -https://github.com/modelcontextprotocol/servers/tree/main/src/postgres How it works A MCP server trigger is used and connected to 5 tools: 2 postgreSQL and 3 custom workflow. The 2 postgreSQL tools are simple read-only queries and as such, the postgreSQL tool can be simply used. The 3 custom workflow tools are used for select, insert and update queries as these are operations which require a bit more discretion. Whilst it may be easier to allow the agent to use raw SQL queries, we may find it a little safer to just allow for the parameters instead. The custom workflow tool allows us to define this restricted schema for tool input which we'll use to construct the SQL statement ourselves. All 3 custom workflow tools trigger the same "Execute workflow" trigger in this very template which has a switch to route the operation to the correct handler. Finally, we use our standard PostgreSQL node to handle select, insert and update operations. The responses are then sent back to the the MCP client. How to use This PostgreSQL MCP server allows any compatible MCP client to manage a PostgreSQL database by supporting select, create and update operations. You will need to have a database available before you can use this server. Connect your MCP client by following the n8n guidelines here - https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-langchain.mcptrigger/#integrating-with-claude-desktop Try the following queries in your MCP client: "Please help me check if Alex has an entry in the users table. If not, please help me create a record for her." "What was the top selling product in the last week?" "How many high priority support tickets are still open this morning?" Requirements PostgreSQL for database. This can be an external database such as Supabase or one you can host internally. MCP Client or Agent for usage such as Claude Desktop - https://claude.ai/download Customising this workflow If the scope of schemas or tables is too open, try restrict it so the MCP serves a specific purpose for business operations. eg. Confine the querying and editing to HR only tables before providing access to people in that department. Remember to set the MCP server to require credentials before going to production and sharing this MCP server with others!

Extracting LinkedIn Profile Information Use Case Manually copying data from LinkedIn profiles is time-consuming and error-prone. This automation helps you extract structured, detailed information from any public LinkedIn profile—enabling fast enrichment, hiring research, or lead scoring. What This Automation Does This automation extracts profile details from a LinkedIn URL using the following input parameters: airtop_profile**: The name of your Airtop Profile connected to LinkedIn. linkedin_url**: The URL of the LinkedIn profile you want to extract data from. How It Works Starts with a form trigger or via another workflow. Assigns the LinkedIn URL and Airtop profile variables. Opens the LinkedIn profile in a real browser session using Airtop. Uses an AI prompt to extract structured information, including: Name, headline, location Current company and position About section, experience, and education history Skills, certifications, languages, connections, and recommendations Returns structured JSON ready for further use or storage. Setup Requirements Airtop API Key — free to generate. An Airtop Profile connected to LinkedIn (requires one-time login). Next Steps Sync with CRM**: Push extracted data into HubSpot, Salesforce, or Airtable for lead enrichment. Combine with Search Automation**: Use with a LinkedIn search scraper to process profiles in bulk. Adapt to Other Platforms**: Customize the prompt to extract structured data from GitHub, Twitter, or company sites. Read more about the Extract Linkedin Profile Information automation.

Problem Monitoring SEO performance from Google Search Console (GSC) manually is repetitive and prone to human error. For marketers or analysts managing multiple domains, checking reports manually and copying data into spreadsheets or databases is time-consuming. There is a strong need for an automated solution that collects, stores, and updates SEO metrics regularly for easier analysis and dashboarding. Solution This workflow automatically pulls performance metrics from Google Search Console — including queries, pages, CTR, impressions, positions, and devices — and stores them in a structured format inside a NocoDB table. It’s ideal for SEO specialists, marketing teams, or data analysts who need to automate SEO reporting and centralize data for analytics or dashboards (like Superset or Metabase). Setup Instructions Authorize your Google Search Console account Connect via OAuth2 (requires GSC API access). Create a NocoDB table Define fields to match GSC response: query (text) page (URL) device (text) clicks (number) impressions (number) ctr (percentage) position (number) Add credentials in n8n Use credential nodes for both: Google OAuth2 NocoDB API Token Customize schedule trigger Set the frequency (e.g., weekly) and adjust the domain/date range as needed. Generalize domains Replace specific domains like martechmafia.net with your-domain.com before submission. NocoDB Table Structure The NocoDB table must match the fields coming from GSC's Search Analytics API. Here's a sample schema: { "query": "string", "page": "string", "device": "string", "clicks": "number", "impressions": "number", "ctr": "number", "position": "number" }

Overview This automated workflow fetches Upwork job postings using Apify, removes duplicate job listings via MongoDB, and sends new job opportunities to Slack. Key Features: Automated job retrieval** from Upwork via Apify API Duplicate filtering** using MongoDB to store only unique jobs Slack notifications** for new job postings Runs every 20 minutes** during working hours (9 AM - 5 PM) This workflow requires an active Apify subscription to function, as it uses the Apify Upwork API to fetch job listings. Who is This For? This workflow is ideal for: Freelancers looking to track Upwork jobs in real time Recruiters automating job collection for analytics Developers who want to integrate Upwork job data into their applications What Problem Does This Solve? Manually checking Upwork for jobs is time-consuming and inefficient. This workflow: Automates job discovery based on your keywords Filters out duplicate listings, ensuring only new jobs are stored Notifies you on Slack when new jobs appear How the Workflow Works 1. Schedule Trigger (Every 20 Minutes) Triggers the workflow at 20-minute intervals Ensures job searches are only executed during working hours (9 AM - 5 PM) 2. Query Upwork for Jobs Uses Apify API to scrape Upwork job posts for specific keywords (e.g., "n8n", "Python") 3. Find Existing Jobs in MongoDB Searches MongoDB to check if a job (based on title and budget) already exists 4. Filter Out Duplicate Jobs The Merge Node compares Upwork jobs with MongoDB data The IF Node filters out jobs that are already stored in the database 5. Save Only New Jobs in MongoDB The Insert Node adds only new job listings to the MongoDB collection 6. Send a Slack Notification If a new job is found, a Slack message is sent with job details Setup Guide Required API Keys Upwork Scraper (Apify Token) – Get your token from Apify MongoDB Credentials – Set up MongoDB in n8n using your connection string Slack API Token – Connect Slack to n8n and set the channel ID (default: #general) Configuration Steps Modify search keywords in the 'Assign Parameters' node (startUrls) Adjust the Working Hours in the 'If Working Hours' node Set your Slack channel in the Slack node Ensure MongoDB is connected properly Adjust the 'If Working Hours' node to match your timezone and hours, or remove it altogether to receive notifications and updates constantly. How to Customize the Workflow Change keywords: update the startUrls in the 'Assign Parameters' node to track different job categories Change 'If Working Hours': Modify conditions in the IF Node to filter times based on your needs Modify Slack Notifications: Adjust the Slack message format to include additional job details Why Use This Workflow? Automated job tracking without manual searches Prevents duplicate entries in MongoDB Instant Slack notifications for new job opportunities Customizable – adapt the workflow to different job categories Next Steps Run the workflow and test with a small set of keywords Expand job categories for better coverage Enhance notifications by integrating Telegram, Email, or a dashboard This workflow ensures real-time job tracking, prevents duplicates, and keeps you updated effortlessly.

This n8n template allows you to send emails with a custom alias from your Gmail account Since the native Gmail node has some limitations regarding use of email aliases, this template allows you to set up your own internal endpoint/sub-workflow to send emails as an email alias . How it works This workflow uses a Code node and the Gmail API via an HTTP node to format the email content and send using an alias on your Gmail account. Setup instructions You must have added the email address as an alias you wish to send as in your Gmail account, guide on how to do so here. You must have created a Gmail credential in N8N, guide on how to do so here. Use your Gmail OAuth Credential in the HTTP node. Use this template as an API endpoint or a sub-workflow, and send this payload to it via POST: { "senderName": "SENDER NAME HERE", "fromEmail": "FROM EMAIL HERE", "replyTo": "REPLY TO EMAIL HERE", "toEmail": "jacob@vwork.digital", "subject": "SUBJECT LINE HERE", "htmlBody": "HTML BODY HERE - MUST BE JSON STRINGIFIED", "file_urls": [ "FILE URLS FOR ATTACHMENTS HERE" ] } Notes Only the following are required fields: fromEmail toEmail subject htmlBody Customizing this workflow You can easily convert this to a sub-workflow by swapping out the Webhook trigger for a "When executed by another workflow" trigger

Automated monitoring system that sends instant alerts when target companies make technology changes, delivered directly to your inbox or Slack. 🚀 What It Does Monitors technology stack changes Sends real-time email alerts Posts updates to Slack Tracks historical changes Filters by technology type 🎯 Perfect For Sales teams IT departments Competitive intelligence Technology vendors Market researchers ⚙️ Key Benefits ✅ Instant technology change alerts ✅ Multiple notification channels ✅ Historical tracking ✅ Customizable filters ✅ Team collaboration 🔧 What You Need BuiltWith API access Email service (SMTP/SendGrid) Slack workspace (optional) n8n instance 📊 Alerts Include Company name Technology changes Timestamp Impact assessment Direct links 🛠️ Setup & Support Quick Setup Get alerts in 15 minutes with our step-by-step guide 📺 Watch Tutorial 💼 Get Expert Support 📧 Direct Help Stay informed about technology changes that matter to your business with automated monitoring alerts and notifications.