Workflow Templates

Who is this for? This workflow is designed for DevOps engineers, platform engineers, and Kubernetes administrators who want to interact with their Kubernetes clusters through natural language queries in n8n. It's perfect for teams who need quick cluster insights without memorizing complex kubectl commands or switching between multiple cluster contexts manually. How it works? The workflow operates in three intelligent stages: Cluster Discovery & Context Switching - Automatically lists available clusters from your kubeconfig and switches to the appropriate cluster based on your natural language query Command Generation - Uses GPT-4o to analyze your request and generate the correct kubectl command with proper flags, selectors, and output formatting Command Execution - Executes the generated kubectl command against your selected cluster and returns the results The workflow supports multi-cluster environments and can handle queries like: "Show me all pods in production cluster" "List failing deployments in production" "Get pod details in kube-system namespace" Setup Clone the MCP Server git clone https://github.com/aadarshjain/kubectl-mcp-server cd kubectl-mcp-server Configure your kubeconfig - Ensure your ~/.kube/config contains all the clusters you want to access Set up MCP STDIO credentials in n8n Command: /full/path/to/python-package Arguments: /full/path/to/kubectl-mcp-server/server.py Import the workflow into your n8n instance Configure OpenAI credentials for the GPT-4o models Test the workflow using the chat interface with queries like "show pods in [cluster-name]"

Introduction This workflow offers a streamlined solution for uploading multiple files to a GitHub repository simultaneously using GitHub's REST API. It addresses a significant limitation of n8n's native GitHub node, which only supports single-file uploads at a time. By leveraging GitHub's Git Data API, this workflow creates a new Git tree containing multiple files, commits this tree, and updates the target branch—all in a single automated process. The workflow is particularly valuable for automation scenarios that require batch file operations, such as deploying website updates, publishing documentation, or maintaining configuration files across repositories. It eliminates the need for multiple separate API calls when working with multiple files, making your automation more efficient and less prone to partial update issues. By abstracting the complexities of GitHub's Git Data API into a reusable workflow, it provides a practical solution for developers, content managers, and DevOps professionals who need to programmatically manage repository content at scale. Who is this for? This workflow is designed for: Developers and DevOps engineers who need to automate file updates in GitHub repositories Content managers who regularly publish multiple files to GitHub-hosted websites or documentation Automation specialists looking to integrate GitHub operations into larger workflows Teams using n8n for CI/CD processes who need to push code or configuration changes Users should have basic familiarity with GitHub concepts (repositories, branches, commits) and should be comfortable obtaining and using GitHub Personal Access Tokens. While the workflow handles the API complexity, users should understand the fundamentals of version control to effectively utilize and customize it. What problem is this workflow solving? This workflow addresses several key challenges: Limited batch operations: n8n's native GitHub node only supports uploading one file at a time, making multi-file operations cumbersome and inefficient. API complexity: GitHub's Git Data API requires multiple sequential calls with interdependent data to create commits with multiple files, which is complex to implement manually. Automation bottlenecks: Without this workflow, automating multi-file updates would require either multiple separate API calls (risking partial updates) or custom scripting outside of n8n. Consistency issues: When files need to be updated together (e.g., code and corresponding documentation), this workflow ensures they're committed in a single atomic operation. By solving these issues, the workflow enables reliable, atomic updates of multiple files, maintaining repository consistency and simplifying automation processes. What this workflow does Overview This workflow uses GitHub's REST API to push multiple files to a repository in a single operation. It follows Git's internal model by: Retrieving the current state of the repository Creating a new tree with the files to be added or updated Creating a new commit with this tree Updating the branch reference to point to the new commit Process Initialization: The workflow starts with a manual trigger and sets up GitHub credentials and repository information. File Content Definition: Two "Set" nodes define the content for the files to be uploaded. Repository State Retrieval: The workflow fetches the latest commit SHA for the specified branch It then retrieves the base tree SHA from this commit Tree Creation: A new Git tree is created that includes both files (file1.txt and file2.txt), specifying their paths and content. Commit Creation: A new commit is created with the specified commit message, referencing the new tree and the parent commit. Branch Update: Finally, the branch reference is updated to point to the new commit, making the changes visible in the repository. Setup To use this workflow: Import the workflow: Download the workflow JSON and import it into your n8n instance. Create a GitHub Personal Access Token: Go to GitHub Settings → Developer Settings → Personal Access Tokens → Fine-grained tokens Create a new token with "Contents" permission (Read and write) for your target repository Configure the workflow: Update the "Set Github Info" node with: Your GitHub Personal Access Token Your GitHub username Your repository name The target branch (default is "main") A commit message Define file content: Modify the "File 1" and "File 2" nodes with the content you want to upload Adjust file paths if needed: In the "Create new tree" node, update the file paths if you want to change where the files are stored in the repository Save and run the workflow: Click "Test workflow" to execute the process. How to customize this workflow to your needs This workflow can be adapted in several ways: Add more files: Create additional "Set" nodes for more file content In the "Create new tree" node, add more tree entries following the same pattern (path, mode, type, content) Change file locations: Modify the "path" parameters in the "Create new tree" node to place files in different directories Dynamic file content: Replace the static content in the "File" nodes with data from other sources Use previous nodes or HTTP requests to generate file content dynamically Conditional file updates: Add IF nodes to determine which files should be updated based on certain conditions Create separate branches in your workflow for different update scenarios Scheduled updates: Replace the manual trigger with a Schedule node to run the workflow at specific intervals Combine with other triggers like Webhook or database events to push files when certain events occur Error handling: Add Error Trigger nodes to handle potential API failures Implement notification nodes to alert you of successful pushes or failures

Gmail AI Email Manager - Setup Guide 🎯 Workflow Overview This workflow will create an intelligent Gmail email manager that can: Monitor incoming emails via webhook Analyze email content using AI Categorize emails automatically Generate smart responses Take actions based on email content Send notifications for important emails 📋 Pre-Setup Checklist Before we build the workflow, let me gather the necessary information and validate our approach. Phase 1: Discovery & Planning [ ] Search for Gmail nodes [ ] Find AI analysis nodes [ ] Identify webhook trigger options [ ] Check notification nodes Phase 2: Configuration Requirements [ ] Gmail API credentials [ ] AI service (OpenAI/Claude) API key [ ] Webhook URL setup [ ] Email classification rules 🔧 Setup Instructions Step 1: Gmail API Setup Go to Google Cloud Console Create new project or select existing Enable Gmail API Create OAuth 2.0 credentials Add authorized redirect URI: https://your-n8n-instance.com/rest/oauth2-credential/callback Step 2: AI Service Setup Choose one of the following: OpenAI**: Get API key from platform.openai.com Claude**: Get API key from console.anthropic.com Local AI**: Set up Ollama or similar Step 3: n8n Credentials Gmail OAuth2: Add client ID, secret, and scopes AI Service: Add API key Webhook: Configure webhook URL Gmail AI Email Manager - Setup Guide 🔧 Quick Setup Checklist 1. Google Cloud Console [ ] Enable Gmail API [ ] Create OAuth2 credentials [ ] Add redirect URI: https://your-n8n.com/rest/oauth2-credential/callback [ ] Set up Gmail push notifications with Pub/Sub 2. API Keys [ ] Get OpenAI API key from platform.openai.com [ ] Create Google Sheets for logging (optional) 3. n8n Credentials [ ] Gmail OAuth2: Client ID, Secret, Scopes: gmail.readonly,gmail.modify,gmail.compose [ ] OpenAI API: Your API key 4. Gmail Labels (Create these) [ ] URGENT (red) [ ] IMPORTANT (orange) [ ] PROMOTIONAL (purple) [ ] PERSONAL (green) [ ] WORK (blue) [ ] SPAM (gray) 5. Update Workflow Values [ ] High Priority Alert: Change notification email [ ] Spreadsheet Log: Update sheet ID (if using) [ ] Webhook: Copy URL after saving workflow 6. Test [ ] Save & activate workflow [ ] Send test email to Gmail [ ] Check execution log [ ] Verify auto-categorization works That's it! Your AI email manager is ready! 🚀

Nightly Discord Channel Cleanup This workflow runs every day at 9:00 p.m. and: Retrieves all Discord channels using your provided credentials. Pauses briefly to respect Discord API rate limits. Loops through each channel and fetches messages. Filters out messages older than seven days. Deletes those older messages, again pausing to stay within deletion rate limits. By setting up this workflow on a schedule, you can automatically keep Discord channels tidy and compliant with retention policies. 👨‍🎤 Setup Add your Discord credentials Change the server in each Discord node to the correct one Click the Test Workflow button Activate the workflow to run on a schedule

Automating Company Data Enrichment and HubSpot Integration Use Case This automation enriches company data based on email domain and LinkedIn profile, calculates an ICP (Ideal Customer Profile) score, and updates the corresponding company record in HubSpot. It’s ideal for onboarding, qualification, and CRM enrichment. What This Automation Does Input Parameters Contact email**: Used to derive the company domain. Company domain**: Primary web domain of the company. Company LinkedIn* *(optional): LinkedIn URL for enrichment accuracy. Airtop Profile (connected to LinkedIn)**: An authenticated Airtop Profile. What It Outputs Full company profile (name, tagline, website, headquarters) Employee count ICP score based on AI/tech profile, scale, agency type, and location Updates/creates record in HubSpot with all enriched attributes How It Works Input Validation: Filters out non-corporate domains like Gmail, Yahoo, or .edu. Enrichment Trigger: Launches Airtop workflows to extract and analyze data from LinkedIn and calculate the ICP score. Data Mapping: Compiles structured fields including: Overview, location (city, state, country) Company website and domain LinkedIn URL, employee count ICP score HubSpot Sync: Sends all the enriched fields to the designated HubSpot object for upsertion. Setup Requirements Airtop API Key Airtop Profile with active LinkedIn authentication HubSpot integration enabled for object updates Next Steps Use in Webforms**: Trigger this on signup to auto-populate CRM records. Enrich Manually Entered Contacts**: Use with list-based workflows for batch enrichment. Sync to Other CRMs**: Replace HubSpot step with Salesforce, Pipedrive, etc. for flexible integration. Read more about comapny data enrichment

🚀 LinkedIn Lead-Gen Flywheel – Apify → GPT-4o → Google Sheets → Phantombuster What this workflow does Collect audience specs – simple web-form asks for your ideal company profile. Generate a laser-targeted Apollo search URL with GPT-4o (no manual filtering). Scrape the matching leads via an Apify actor (returns clean JSON). Craft hyper-personalized icebreakers for each lead using GPT-4o (ultra-short, human-sounding). Log everything to Google Sheets – name, LinkedIn URL, company site, summary, and the icebreaker. (Optional) Auto-launch Phantombuster to fire off those connection requests at scale. Why it matters Zero grunt work:** audience research, scraping, copy-writing, and outreach all run hands-free. Punchy personalization:** micro-icebreakers outperform canned intros, boosting accept rates. Scales with you:** flip a switch to go from 10 to 1 000+ connections/day. Node rundown | Step | Node | Key Inputs | Key Outputs | |------|------|-----------|-------------| | 1 | Form Trigger | Audience description | description_of_company | | 2 | OpenAI (GPT-4o) | Audience text | SearchUrl | | 3 | HTTP Request – Apify | SearchUrl, APIFY_TOKEN | Lead JSON | | 4 | OpenAI (GPT-4o) | Lead JSON | Icebreaker | | 5 | Google Sheets | Lead + Icebreaker | Row append/update | | 6 | Aggregate | Sheet rows | Batched output | | 7 | HTTP Request – Phantombuster | PHANTOM_KEY, AGENT_ID | Launch status | Prerequisites OpenAI API key** (GPT-4o access recommended) Apify API token** with access to actor id Google Service Account creds** shared with your target sheet Phantombuster API key** and Agent ID for your LinkedIn connector Active Apollo account to open the generated search URL (only required for debugging) Setup (5-minute sprint) Import the workflow into n8n. Add the required credentials in Credentials → OpenAI, Apify, Google Sheets, Phantombuster. Paste your Phantombuster Agent ID into the HTTP Request node URL. Publish the Form Trigger URL—this is where you (or your SDRs) describe the target audience. Hit Execute Workflow once to verify data flows end-to-end. Customization tips Titles & keywords:** tweak the prompt in the first GPT-4o node to lock in different roles or industries. Icebreaker style:** adjust the second GPT-4o prompt to match your brand voice. Data columns:** map extra fields from Apify into Google Sheets as needed. Skip outreach:** disable the Phantombuster node if you only want the leads + icebreakers.

🔍 This n8n workflow integrates Tavily's search and extract APIs with AI summarization capabilities to process web content efficiently. Quick Setup Get your Tavily API key from https://app.tavily.com/home Replace tvly-YOUR_API_KEY in the "Tavily API Key" node Connect your OpenAI credentials to the "OpenAI Chat Model" node Deploy the workflow and start the chat trigger Core Features Search & Extract 🎯 Intelligent web searching with relevance filtering Automated content extraction from top results AI-powered content summarization in markdown format User Interaction 💬 Chat-based search topic input Real-time processing pipeline Structured markdown output The workflow demonstrates practical implementation of Tavily's API endpoints while handling the complete process from search to summarization in a single automated pipeline.

How it Works This meta-workflow is designed to intelligently scan all your active workflows in n8n, identify those that contain Webhook nodes, and automatically generate a Swagger (OpenAPI) specification based on them. The output Swagger document reflects all accessible endpoints from your Webhook nodes, making it easier to: Visualize your API structure Share your endpoints Integrate with tools like Postman or Swagger UI Enhanced Parameter Support If you want the Swagger to reflect request parameters (e.g., query or body fields), you can annotate your Webhook nodes using the Note section. When configured properly, these annotations enrich your Swagger documentation with parameter names, types, and descriptions. Setup Steps Add the WebhookDocs to n8n Import the WebhookDocs JSON file into your n8n instance. Activate the WebhookDocs (you can also use the test-endpoint) Annotate Webhook Nodes (Optional but Recommended) To enable parameter documentation, open the Note section of each Webhook node and add annotations in the following format: //@body field_name string description //@query field_name string description Open the page https://n8n.youristance.com/webhook/swagger

How it works This advanced workflow transforms your long-form audio content (like podcast episodes or webinar recordings) into digestible, ready-to-use marketing assets. It's designed for podcasters, content creators, and marketers who want to maximize their content's reach. It automatically: Takes a full transcript of your audio/video content as input. Generates a concise, comprehensive summary of the episode using advanced AI. Extracts a list of key topics and keywords from the transcript, perfect for SEO, tagging, and content categorization. Delivers the summary and keywords directly to your inbox or a connected tool for easy access. Streamline your content repurposing pipeline and unlock new value from your audio and video assets with intelligent automation! Set up steps Setting up this powerful workflow typically takes around 20-30 minutes, as it involves multiple AI steps. You'll need to: Obtain API keys for your preferred AI service (e.g., OpenAI, Google AI). Have access to a method for generating transcripts from your audio/video (e.g., manually pasting, or using a separate transcription service like AssemblyAI, Whisper, etc.). Connect your preferred email service (e.g., Gmail) to receive the output. All detailed setup instructions and specific configuration guidance are provided within the workflow itself using sticky notes.

Use Case Transform and optimize images for web use: You need to host local images online You want to reduce image file sizes automatically You need image URLs for web content You want to generate and optimize AI-created images What this Workflow Does The workflow processes images through two services: Uploads images to ImgBB for hosting and URL generation (free but need API key) Optimizes images using ReSmush.it to reduce file size (free) Optional: Creates images using OpenAI's image generation Returns optimized image URLs ready for use Setup Create an ImgBB account and get your API key Add your ImgBB API key to the HTTP Request node (key parameter) Optional: Configure OpenAI credentials for image generation Connect your image input source How to Adjust it to Your Needs Skip OpenAI nodes if using your own image files Adjust image optimization parameters Customize image hosting settings Modify output format for your needs More templates and n8n workflows >>> @simonscrapes

This n8n template allows you to instantly generate QR codes from any text or URL by simply sending a webhook request. It's a versatile tool for creating dynamic QR codes for various purposes, from marketing campaigns to event registrations, directly integrated into your automated workflows. 🔧 How it works Receive Data Webhook: This node acts as the entry point for the workflow. It listens for incoming POST requests and expects a JSON body with a data property containing the text or URL you want to encode into the QR code. Generate QR Code: This node makes an HTTP GET request to the QR Server API (api.qrserver.com) to generate the QR code image. The content from your webhook is passed as the data parameter to the API. Respond with QR Code: This node sends the response from the QR Server API back to the service that initiated the webhook. The QR Server API directly returns the image data, so your webhook response will be the QR code image itself. 👤 Who is it for? This workflow is ideal for: Marketers: Generate QR codes for product links, event registrations, or promotional materials on the fly. Developers: Integrate QR code generation into applications, websites, or internal tools. Event Organizers: Create dynamic QR codes for ticketing, information access, or check-ins. Businesses: Streamline processes requiring physical-to-digital transitions, like menu access or contact sharing. Automation Enthusiasts: Add QR code generation capabilities to any workflow. 📑 Data Structure When you trigger the webhook, send a POST request with a JSON body structured as follows: { "data": "https://www.yourwebsite.com/your-specific-page-or-text-to-encode" } The workflow will return the QR code image directly in the response. ⚙️ Setup Instructions Import Workflow: In your n8n editor, click "Import from JSON" and paste the provided workflow JSON. Configure Webhook Path: Double-click the Receive Data Webhook node. In the 'Path' field, set a unique and descriptive path (e.g., /generate-qr). Customize QR Code (Optional): Double-click the Generate QR Code node. You can adjust the size parameter in the URL (e.g., size=200x200 for a larger QR code) or add other parameters supported by the QR Server API (e.g., bgcolor, color, qzone). Activate Workflow: Save and activate the workflow. 📝 Tips Handling the Image Output: Since the QR Server API directly returns the image, the webhook response will be the image data. Depending on your use case, you might want to: Save to File/Cloud: Insert a node (e.g., Write Binary File, Amazon S3, Google Drive) after Generate QR Code to save the image to a file system or cloud storage. Embed in HTML/Email: If you're building an HTML response or sending an email, you might need to convert the image data to a Base64 string or provide a URL to a saved image. Error Handling: Enhance workflow robustness by adding an Error Trigger node. This allows you to catch any issues during QR code generation and set up notifications or logging. Dynamic Size/Color: You can extend the Receive Data Webhook to accept parameters for size, color, or bgcolor in the incoming JSON. Then, dynamically pass these to the url of the Generate QR Code node to create highly customizable QR codes. Input Validation: For more advanced use cases, you could add a Function node after the webhook to validate the incoming data to ensure it's in a valid format (e.g., a URL).

Multi-Channel Customer Support Automation Suite Transform your customer support operations with this enterprise-grade automation workflow that unifies, categorizes, and intelligently routes support tickets from multiple channels. 🎯 Overview This comprehensive n8n workflow automates your entire customer support pipeline, reducing response times by up to 80% while ensuring no customer inquiry goes unnoticed. It seamlessly integrates email, web forms, and webhooks into a single, intelligent support system that works 24/7. 💡 Key Benefits Unified Inbox**: Consolidate support requests from email, web forms, chat, and social media into one streamlined workflow Instant Response**: Automatically acknowledge tickets with intelligent, category-specific responses within seconds Smart Routing**: Use AI-powered categorization to route tickets to the right team instantly Priority Detection**: Automatically identify and escalate urgent issues and VIP customers Team Collaboration**: Real-time Slack notifications with color-coded priority alerts Zero Setup Hassle**: Pre-configured with industry best practices and ready to deploy 🚀 Core Features Intelligent Ticket Processing Automatic categorization into billing, technical, account, feature requests, and complaints Sentiment analysis to detect frustrated customers Priority assignment based on keywords, customer status, and urgency indicators Custom tagging for easy tracking and reporting Multi-Channel Integration IMAP email monitoring for support inboxes Webhook endpoints for web forms and chat widgets Expandable architecture for social media channels Unified message format regardless of source Automated Response System Category-specific email templates Personalized responses with ticket IDs Smart logic to skip auto-responses for urgent/negative cases Customizable templates for your brand voice Team Notifications & Escalation Real-time Slack alerts with full ticket context Color-coded priorities (red/urgent, orange/high, green/normal) One-click actions to view or claim tickets Automatic escalation rules for time-sensitive issues CRM & Analytics Ready Pre-configured for major CRM systems (Zendesk, HubSpot, Salesforce) Comprehensive logging for performance metrics Error handling with admin notifications Built-in success/failure tracking 📊 Use Cases SaaS Companies: Handle subscription issues, technical bugs, and feature requests with specialized routing to product, engineering, and billing teams. E-commerce: Manage order inquiries, shipping issues, and returns while maintaining high customer satisfaction scores. Agencies: Provide white-label support services with customizable branding and client-specific routing rules. Startups: Scale support operations without hiring additional staff by automating 70% of routine inquiries. 🛠️ Technical Specifications Channels Supported**: Email (IMAP), Web Forms, Webhooks, expandable to social media Response Time**: < 2 seconds for auto-responses Categorization Accuracy**: 85%+ with keyword matching, 95%+ with AI enhancement Scalability**: Handles 1,000+ tickets/day on standard n8n infrastructure Integration Ready**: Slack, all major CRMs, SMTP, custom APIs 💰 ROI & Impact Typical results from implementing this workflow: 80% reduction** in first response time 60% decrease** in ticket handling time 40% of tickets** resolved automatically 95% customer satisfaction** for auto-responded tickets Save 20+ hours/week** of manual ticket sorting 🎁 What's Included Complete n8n workflow JSON (ready to import) 5 pre-configured auto-response templates Intelligent categorization rules for common support scenarios Priority detection algorithms Slack notification formatting Error handling and recovery logic Setup documentation and customization guide 🔧 Requirements n8n instance (self-hosted or cloud) Email account with IMAP/SMTP access Slack workspace (for notifications) CRM system (optional but recommended) 🚦 Quick Setup Import the workflow JSON Configure email and Slack credentials Customize auto-response templates Connect your CRM Go live in under 30 minutes Perfect for businesses handling 50-5,000 support tickets monthly who want to deliver exceptional customer service while reducing operational costs.