Workflow Templates

📄 What this workflow does This workflow captures a full-page screenshot of any website added to a Google Sheet and automatically uploads the screenshot to a designated Google Drive folder. It uses Dumpling AI’s screenshot API to generate the image and manages file storage through Google Drive. 👤 Who is this for This is ideal for: Marketers and outreach teams capturing snapshots of client or lead websites Lead generation specialists tracking landing page visuals Researchers or analysts who need to archive website visuals from URLs Anyone looking to automate website screenshot collection at scale ✅ Requirements A Google Sheet with a column labeled Website where URLs will be added Dumpling AI** API access for screenshot capture A connected Google Drive account with an accessible folder to store screenshots ⚙️ How to set up Replace the Google Sheet and folder IDs in the workflow with your own. Connect your Dumpling AI and Google credentials in n8n. Make sure your sheet contains a Website column with valid URLs. Activate the workflow to begin watching for new entries. 🔁 How it works (Workflow Steps) Watch New Row in Google Sheets: Triggers when a new row is added to the sheet. Request Screenshot from Dumpling AI: Sends the website URL to Dumpling AI and gets a screenshot URL. Download Screenshot: Fetches the image file from the returned URL. Upload Screenshot to Google Drive: Uploads the file to a selected folder in Google Drive. 🛠️ Customization Ideas Add timestamped filenames using the current date or domain name Append the Google Drive URL back to the same row in the sheet for easy access Extend the workflow to send Slack or email notifications when screenshots are saved Add filters to validate URLs before sending them to Dumpling AI

Proactively retain customers predicted to churn with this automated n8n workflow. Running daily, it identifies high-risk customers from your Google Sheet, uses Google Gemini to generate personalized win-back offers based on their churn score and preferences, sends these offers via Gmail, and logs all actions for tracking. What does this workflow do? This workflow automates the critical process of customer retention by: Running automatically every day** on a schedule you define. Fetching customer data** from a designated Google Sheet containing metrics like predicted churn scores and preferred categories. Filtering* to identify customers with a high churn risk (score > 0.7) who haven't recently received a specific campaign (based on the created_campaign_date field - *you might need to adjust this logic). Using Google Gemini AI to dynamically generate one of three types of win-back offers, personalized based on the customer's specific churn score and preferred product categories: Informational: (Score 0.7-0.8) Highlights new items in preferred categories. Bonus Points: (Score 0.8-0.9) Offers points for purchases in a target category (e.g., Books). Discount Percentage: (Score 0.9-1.0) Offers a percentage discount in a target category (e.g., Books). Sending the personalized offer* directly to the customer via *Gmail**. Logging** each sent offer or the absence of eligible customers for the day in a separate 'SYSTEM_LOG' Google Sheet for monitoring and analysis. Who is this for? CRM Managers & Retention Specialists:** Automate personalized outreach to at-risk customers. Marketing Teams:** Implement data-driven retention campaigns with minimal manual effort. E-commerce Businesses & Subscription Services:** Proactively reduce churn and increase customer lifetime value. Anyone** using customer data (especially churn prediction scores) who wants to automate personalized retention efforts via email. Benefits Automated Retention:** Set it up once, and it runs daily to engage at-risk customers automatically. AI-Powered Personalization:** Go beyond generic offers; tailor messages based on churn risk and customer preferences using Gemini. Proactive Churn Reduction:* Intervene *before customers leave by addressing high churn scores with relevant offers. Scalability:** Handle personalized outreach for many customers without manual intervention. Improved Customer Loyalty:** Show customers you value them with relevant, timely offers. Action Logging:** Keep track of which customers received offers and when the workflow ran. How it Works Daily Trigger: The workflow starts automatically based on the schedule set (e.g., daily at 9 AM). Fetch Data: Reads all customer data from your 'Customer Data' Google Sheet. Filter Customers: Selects customers where predicted_churn_score > 0.7 AND created_campaign_date is empty (verify this condition fits your needs). Check for Eligibility: Determines if any customers passed the filter. IF Eligible Customers Found: Loop: Processes each eligible customer one by one. Generate Offer (Gemini): Sends the customer's predicted_churn_score and preferred_categories to Gemini. Gemini analyzes these and the defined rules to create the appropriate offer type, value, title, and detailed message, returning it as structured JSON. Log Sent Offer: Records action_taken = SENT_WINBACK_OFFER, the timestamp, and customer_id in the 'SYSTEM_LOG' sheet. Send Email: Uses the Gmail node to send an email to the customer's user_mail with the generated offer_title as the subject and offer_details as the body. IF No Eligible Customers Found: Set Status: Creates a record indicating system_log = NOT_FOUND. Log Status: Records this 'NOT_FOUND' status and the current timestamp in the 'SYSTEM_LOG' sheet. n8n Nodes Used Schedule Trigger Google Sheets (x3 - Read Customers, Log Sent Offer, Log Not Found) Filter If SplitInBatches (Used for Looping) Langchain Chain - LLM (Gemini Offer Generation) Langchain Chat Model - Google Gemini Langchain Output Parser - Structured Set (Prepare 'Not Found' Log) Gmail (Send Offer Email) Prerequisites Active n8n instance (Cloud or Self-Hosted). Google Account** with access to Google Sheets and Gmail. Google Sheets API Credentials (OAuth2):** Configured in n8n. Two Google Sheets:** 'Customer Data' Sheet: Must contain columns like customer_id, predicted_churn_score (numeric), preferred_categories (string, e.g., ["Books", "Electronics"]), user_mail (string), and potentially created_campaign_date (date/string). 'SYSTEM_LOG' Sheet: Should have columns like system_log (string), date (string/timestamp), and customer_id (string, optional for 'NOT_FOUND' logs). Google Cloud Project** with the Vertex AI API enabled. Google Gemini API Credentials:** Configured in n8n (usually via Google Vertex AI credentials). Gmail API Credentials (OAuth2):** Configured in n8n with permission to send emails. Setup Import the workflow JSON into your n8n instance. Configure Schedule Trigger: Set the desired daily run time (e.g., Hours set to 9). Configure Google Sheets Nodes: Select your Google Sheets OAuth2 credentials for all three Google Sheets nodes. 1. Fetch Customer Data...: Enter your 'Customer Data' Spreadsheet ID and Sheet Name. 5b. Log Sent Offer...: Enter your 'SYSTEM_LOG' Spreadsheet ID and Sheet Name. Verify column mapping. 3b. Log 'Not Found'...: Enter your 'SYSTEM_LOG' Spreadsheet ID and Sheet Name. Verify column mapping. Configure Filter Node (2. Filter High Churn Risk...): Crucially, review the second condition: {{ $json.created_campaign_date.isEmpty() }}. Ensure this field and logic correctly identify customers who should receive the offer based on your campaign strategy. Modify or remove if necessary. Configure Google Gemini Nodes: Select your configured Google Vertex AI / Gemini credentials in the Google Gemini Chat Model node. Review the prompt in the 5a. Generate Win-Back Offer... node to ensure the offer logic matches your business rules (especially category names like "Books"). Configure Gmail Node (5c. Send Win-Back Offer...): Select your Gmail OAuth2 credentials. Activate the workflow. Ensure your 'Customer Data' and 'SYSTEM_LOG' Google Sheets are correctly set up and populated. The workflow will run automatically at the next scheduled time. This workflow provides a powerful, automated way to engage customers showing signs of churn, using personalized AI-driven offers to encourage them to stay. Adapt the filtering and offer logic to perfectly match your business needs!

📒 Telegram Expense Tracker to Google Sheets with GPT-4.1 👤 Who’s it for This workflow is for anyone who wants to log their daily expenses by simply chatting with a Telegram bot. Ideal for: Individuals who want a quick way to track spending Freelancers who log receipts and purchases on the go Teams or small business owners who want lightweight expense capture ⚙️ How it works / What it does User sends a text message on Telegram describing an expense (e.g., “Bought coffee for 50k at Highlands”) Message format is validated If the message is text, it proceeds to GPT-4.1 Mini for processing. If it's not text (e.g. image or file), the bot sends a fallback message. OpenAI GPT-4.1 Mini parses the message and returns: relevant: true/false expense_record: structured fields (date, amount, currency, category, description, source) message: a friendly confirmation or fallback If valid: The bot replies with a fun acknowledgment The data is saved to a connected Google Sheet If invalid: A fallback message is sent to encourage proper input 🛠️ How to set up 1. Telegram Bot Setup Create a bot using BotFather on Telegram Copy the bot token and paste it into the Telegram Trigger node 2. Google Sheet Setup Create a Google Sheet with these columns: Date | Amount | Currency | Category | Description | SourceMessage Share the sheet with your n8n service account email 3. OpenAI Configuration Connect the OpenAI Chat Model node using your OpenAI API key Use GPT-4.1 Mini as the model Apply a system prompt that extracts structured JSON with: relevant, expense_record, and message 4. Add Parser Use the Structured Output Parser node to safely parse the JSON response 5. Conditional Logic Nodes Is text message? Checks if the message is in text format Supported scenario? Checks if relevant = true in the LLM response 6. Final Actions If relevant**: Send confirmation via Telegram Append row to Google Sheet If not relevant**: Send fallback message via Telegram ✅ Requirements Telegram bot token OpenAI GPT-4.1 Mini API access n8n instance (self-hosted or cloud) Google Sheet with access granted to n8n Basic understanding of n8n node configuration 🧩 How to customize the workflow | Feature | How to Customize | |----------------------------------|-------------------------------------------------------------------| | Add multi-currency support | Update system prompt to detect and extract different currencies | | Add more categories | Modify the list of categories in the system prompt | | Track multiple users | Add username or chat ID column to the Google Sheet | | Trigger alerts | Add Slack, Email, or Telegram alerts for specific expense types | | Weekly summaries | Use a cron node + Google Sheet query + Telegram message | | Visual dashboards | Connect the sheet to Looker Studio or Google Data Studio | Built with 💬 Telegram + 🧠 GPT-4.1 Mini + 📊 Google Sheets + ⚡ n8n

How it works This workflow automates the process of creating, approving, and optionally posting LinkedIn content from a Google Sheet. Here's a high-level overview: Scheduled Trigger: Runs automatically based on your defined time interval (daily, weekly, etc.). Fetch Data from Google Sheets: Pulls the first row from your sheet where Status is marked as Pending. Generate LinkedIn Post Content: Uses OpenAI to create a professional LinkedIn post using the Post Description and Instructions from the sheet. Format & Prepare Data: Formats the generated content along with the original instruction and post description for email. Send for Approval: Sends an email to a predefined user (e.g., marketing team) with a custom form for approval, including a dropdown to accept/reject and an optional field for edits. (Optional) Image Fetch: Downloads an image from a URL (if provided in the sheet) for future use in post visuals. Set up steps You’ll need the following before you start: A Google Sheet with the following columns: Post Description, Instructions, Image (URL), Status Access to an OpenAI API key A connected Gmail account for sending approval emails Your own Google Sheets and Gmail credentials added in n8n Steps: Google Sheet Preparation: Create a new Google Sheet with the mentioned columns (Post Description, Instructions, Image, Status, Output, Post Link). Add a row with test data and set Status to Pending. Credentials: In n8n, create OAuth2 credentials for: a. Google Sheets b. Gmail c. OpenAI (API Key) Assign these credentials to the respective nodes in the JSON. OpenAI Model: Choose a model like gpt-4o-mini (used here) or any other available in your plan. Adjust the prompt in the "Generate Post Content" node if needed. Email Configuration: In the Gmail node, set the recipient email to your own or your team’s address. Customize the email message template if necessary. Schedule the Workflow: Set the trigger interval (e.g., every morning at 9 AM). Testing: Run the workflow manually first to confirm everything works. Check Gmail for the approval form, respond, and verify the results.

This workflow automates the generation of AI-enhanced, contextualized images using FLUX Kontext, based on prompts stored in a Google Sheet. The generated images are then saved to Google Drive, and their URLs are written back to the spreadsheet for easy access. Example Image: Prompt: The girl is lying on the bed and sleeping Result: Perfect for E-commerce and Social Media This workflow is especially useful for e-commerce businesses: Generate product images with dynamic backgrounds based on the use-case or season. Create contextual marketing visuals for ads, newsletters, or product pages. Scale visual content creation without the need for manual design work. How It Works Trigger**: The workflow can be started manually (via "Test workflow") or scheduled at regular intervals (e.g., every 5 minutes) using the "Schedule Trigger" node. Data Fetch**: The "Get new image" node retrieves a row from a Google Sheet where the "RESULT" column is empty. It extracts the prompt, image URL, output format, and aspect ratio for processing. Image Generation**: The "Create Image" node sends a request to the FLUX Kontext API (fal.run) with the provided parameters to generate a new AI-contextualized image. Status Check**: The workflow waits 60 seconds ("Wait 60 sec." node) before checking the status of the image generation request via the "Get status" node. If the status is "COMPLETED," it proceeds; otherwise, it loops back to wait. Result Handling**: Once completed, the "Get Image Url" node fetches the generated image URL, which is then downloaded ("Get Image File"), uploaded to Google Drive ("Upload Image"), and the Google Sheet is updated with the result ("Update result"). Set Up Steps To configure this workflow, follow these steps: Google Sheet Setup: Create a Google Sheet with columns for PROMPT, IMAGE URL, ASPECT RATIO, OUTPUT FORMAT, and RESULT (leave this empty). Link the sheet in the "Get new image" and "Update result" nodes. API Key Configuration: Sign up at fal.ai to obtain an API key. In the "Create Image" node, set the Header Auth with: Name: Authorization Value: Key YOURAPIKEY Google Drive Setup: Specify the target folder ID in the "Upload Image" node where generated images will be saved. Schedule Trigger (Optional): Adjust the "Schedule Trigger" node to run the workflow at desired intervals (e.g., every 5 minutes). Test Execution: Run the workflow manually via the "Test workflow" node to verify all steps function correctly. Once configured, the workflow will automatically process pending prompts, generate images, and update the Google Sheet with results. Need help customizing? Contact me for consulting and support or add me on Linkedin.

This n8n workflow scrapes recent Instagram posts by hashtag and generates new, relevant caption ideas using OpenAI. It avoids making up suggestions by analyzing real-world content and surfacing common patterns. ✅ Use Case Marketing teams, content creators, or social media managers can: Discover what’s trending for a specific topic Automatically generate Instagram captions based on real posts Understand common caption styles for a niche Save time brainstorming ideas while staying on-brand 🧠 How It Works 1️⃣ Manual Trigger 🧩 Node: When clicking ‘Execute workflow’ Manually starts the workflow for testing or single-run execution. 2️⃣ Define the Hashtag 🧩 Node: Create Search Term Sets the value of the hashtag you'd like to scan. Default is n8n, but you can modify it to anything. { "Search_Term": "yourCustomHashtag" } 3️⃣ Scrape Instagram Posts 🧩 Node: Find Recent Posts API**: Apify Instagram Hashtag Scraper Setup**: Visit Apify Console Create an API token In n8n, go to Credentials and add HTTP Query Auth Use ?token=yourTokenHere as the query string JSON Body: { "hashtags": ["{{ $json.Search_Term }}"], "resultsLimit": 20, "resultsType": "posts" } 4️⃣ Extract Captions 🧩 Node: Set bio and follower count Extracts just the caption from each post and stores it in a clean variable for the AI agent to use. 5️⃣ Aggregate Captions 🧩 Node: Aggregate Gathers all captions into one list before processing. Useful for passing a large text block into the AI. 6️⃣ Convert to Single Text Block 🧩 Node: Convert table names and columns into single text for agent Uses a Code node to combine all captions into a single string for OpenAI to read: return [ { json: { text: items .map(item => - ${JSON.stringify(item.json)}) .join('\n\n'), }, }, ]; 7️⃣ Generate Caption Ideas with AI 🧩 Node: AI Agent Takes the combined post text and sends it to GPT-4o-mini. Includes this system message: I'm looking for ideas for posts about {{ $('Create Search Term').item.json.Search_Term }}. Here’s the last 5 posts on Instagram about the topic. Use those to help me generate a list of relevant captions. Do not make up ideas that are not like the others in the list. Output like this: { "Post Idea": ["Idea1", "Idea2"], "Most Common Post": ["common post 1", "common post 2"] } 8️⃣ Choose Language Model 🧩 Node: OpenAI Chat Model Model**: gpt-4o-mini Credential**: Use your OpenAI API key. Get it from: OpenAI API Keys Add it in n8n under OpenAI credentials. 9️⃣ Parse the AI Output 🧩 Node: Structured Output Parser Parses the GPT response into structured JSON: { "Post Idea": ["Idea1", "Idea2"], "Most Common Post": ["common post 1", "common post 2"] } 🔟 Split the Outputs 🧩 Nodes: Split Out, Split Out1 Separates the Post Idea list and Most Common Post list into individual items. 🔁 Merge for Final Output 🧩 Node: Merge Combines the two split lists into one output stream. 👤 Need More Help? Robert Breen Automation Consultant | AI Workflow Designer | n8n Expert 📧 robert@ynteractive.com 🔗 LinkedIn

This workflow automates the process of generating and scheduling social media posts using content from a WordPress blog. It leverages advanced AI (OpenAI & Anthropic Claude), Google Sheets, and the Postiz platform to create and publish platform-specific posts across LinkedIn, Facebook, Instagram, and Twitter (X). This system streamlines cross-platform social media publishing, ensuring consistent branding and AI-optimized content. Key Features Content Source: WordPress Automatically fetches the content of a WordPress post by its Post ID. Content Transformation via AI Uses Anthropic Claude and OpenAI to generate unique, optimized captions for each platform: LinkedIn: professional and insight-driven Instagram: creative with emojis and storytelling Facebook: community-oriented and friendly Twitter (X): concise, hashtag-optimized Visual Generation (Optional) Uses OpenAI's DALL·E (via OpenRouter) to generate custom images based on the AI-generated Instagram and Facebook/LinkedIn captions. Post Management with Google Sheets Uses a Google Sheet as the control panel: Simply input the WordPress Post ID Marks each post as “done” by updating corresponding columns (TWITTER, FACEBOOK, INSTAGRAM, LINKEDIN) Publishing via Postiz Uses the Postiz API to schedule or immediately publish posts to your connected social accounts. Handles image uploads and scheduling time for each platform. Benefits 💡 Intelligent automation: Saves time by removing manual copywriting and platform formatting. 🎯 Platform optimization: Ensures posts are tailored to each platform’s audience and algorithm. 🛠️ No-code friendly: Simple setup via Google Sheets + Postiz + WordPress. 🔁 Repeatable & Scalable: Ideal for agencies or content creators managing multiple posts per week. 🧪 +20 Social Media Platforms: Easy to start with social integrations. How It Works Input & Data Fetching: The workflow starts with a manual trigger (e.g., "Test workflow") or scheduled execution. It retrieves a WordPress post ID from a Google Sheets document, then fetches the full post content (title and body) via the WordPress API. AI-Powered Content Generation: The "Social Media Manager" node (powered by Claude Opus 4.1) analyzes the post and generates platform-optimized captions for: Twitter/X: Concise, hashtag-rich text (≤150 chars). Facebook/LinkedIn: Professional yet engaging copy with CTAs. Instagram: Visual-focused captions with emojis and hashtags. AI-generated images are created for Instagram (square) and Facebook/LinkedIn (landscape) using OpenAI’s image model. Publishing Automation: Captions and images are uploaded to Postiz, a social media scheduler. Postiz publishes the content to connected platforms (Twitter, Facebook, LinkedIn, Instagram) at the specified time. Google Sheets is updated with status markers (e.g., "x" in columns like TWITTER, FACEBOOK) to track published posts. Set Up Steps Prerequisites: Postiz Account: Sign up for Postiz (free trial available). API Keys: Configure Postiz API credentials in the "Postiz" and "Upload Image" nodes. Social Channels: Link your social accounts in Postiz’s dashboard and note their integrationId values (replace "XXX" in Postiz nodes). Google Sheets Setup: Clone the template Sheet and add WordPress post IDs to the "POST ID" column. Configure Nodes: WordPress: Add credentials for your WordPress site in the "Get Post" node. AI Models: Ensure API keys for Claude (Anthropic) and OpenAI (for images) are valid. Postiz Nodes: Replace placeholder integrationId values with your actual Postiz channel IDs. Test & Deploy: Trigger the workflow manually to verify captions, images, and Postiz scheduling. Activate the workflow for automation (e.g., run daily to publish new WordPress posts). Note: This workflow requires self-hosted n8n due to community nodes (Postiz, LangChain). Need help customizing? Contact me for consulting and support or add me on Linkedin.

Here's the corrected English text: Dropbox Folder Monitoring Workflow As we don't have (yet?) a Dropbox node "Watching new files" or "Watching folder", I created this central workflow to do it. How it works Triggered by Dropbox webhook I respond immediately to Dropbox to avoid webhook disabling Then I add/duplicate one branch per monitored folder, according to my needs In my case, I need to monitor several folders, like "vocal notes to process", "transcriptions to LinkedIn posts" or "quotes to add". This workflow shows 2 types of folder monitoring: Way #1: Each file in the monitored folder calls a sub-workflow Way #2: We get all files from the monitored folder and compare them to a database. If the file is not listed in DB, i supposed it's new one. Way #1 - We get all files from the monitored folder I set a variable folder_to_watch to indicate which folder to monitor. This step is here just to be homogeneous and allow setting the folder path only once in this branch. I list the folder files We keep only files (exclude folders) Then I call the specialized sub-workflow Way #2 - We want only new files from the monitored folder I set a variable folder_to_watch to indicate which folder to monitor I list the folder files and keep only files Meanwhile, I query my DB to get known files about this folder (I send the query to NocoDB (folder_to_watch,eq,{{ $json.folder_to_watch }})) Now I can exclude old files and keep only new ones by merging (I compare from Dropbox file id - as the file could be renamed by the user) I add the new file in DB to be sure to recognize it next time - I save the JSON Dropbox data: { "id":"{{ $json.id }}", "name":"{{ $json.name }}", "lastModifiedClient": "{{ $json.lastModifiedClient }}", "lastModifiedServer": "{{ $json.lastModifiedServer }}", "rev": "{{ $json.rev }}", "contentSize": {{ $json.contentSize }}, "type": "{{ $json.type }}", "contentHash": "{{ $json.contentHash }}", "pathLower": "{{ $json.pathLower }}", "pathDisplay": "{{ $json.pathDisplay }}", "isDownloadable": {{ $json.isDownloadable }} } And now I can call my sub-workflow :) My DB Columns details: folder_to_watch data (json/text) timestamp file_id (Dropbox file ID, to ease future searches) My vision: I have only one workflow in my n8n that monitors Dropbox folders/files This workflow calls the required sub-workflow specialized for the tasks required I will have as many branches as I have folders to monitor (if I have 5 different folders to watch, I will get 5 branches and 5 sub-workflows)

This n8n template helps you build a full AI-powered LinkedIn content generator with just a few clicks. Paired with the free WeWeb UI template, it becomes a ready-to-use web app where users can: Add their own OpenAI API key Customize the prompt and define 6 content topics Edit the AI-generated topics Choose when to generate LinkedIn posts, complete with hashtags and an optional image Who This Is For Perfect for marketers, indie hackers, and solopreneurs who want to build their personal brand on LinkedIn while staying in control of what gets posted. 🧠 What Makes This Different Unlike most AI agents, you stay fully in control: You define the tone and focus via the prompt. You choose which topics to keep or modify. You decide when to generate a post. You can build on top of this and create your own SaaS product. It’s also modular and extendable—hook it up to your backend, add user login, or feed AI improvements based on user input. ⚙️ How It Works Triggering Events: The app includes 3 pre-configured triggers, ready to be hooked into your WeWeb frontend. Just update the webhook URLs after duplicating the n8n workflow. Topic Generation: A call is made to OpenAI (GPT-4) to generate topic ideas based on your prompt. Post Creation: Once topics are approved or edited, GPT-4 writes full posts with suggested hashtags. Image Generation (Optional): If enabled, a DALL·E call generates a relevant image. Everything Stays Local: All data and images are handled locally, no cloud storage setup needed. 🧪 Requirements & Setup No fancy infrastructure required. Here’s what helps you get started: Free WeWeb account** (recommended) to use the frontend UI template OpenAI account** with API access (for GPT-4 and DALL·E) n8n account** (self-hosted or cloud) to run the backend workflow The template is completely free to use. Since each user adds their own OpenAI API key, you don't need to worry about usage costs or rate limits on your end. 🔧 Want to Go Further? This setup is beginner-friendly, but developers can: Add user accounts Save post history Feed user feedback back into the prompt logic Launch their own branded version as a SaaS

Email Inbox Manager System Categories Email Automation AI-Powered Operations Internal Productivity Tools This workflow builds a fully automated AI-powered email categorization and response assistant. It intelligently processes, categorizes, labels, and drafts replies to incoming Gmail messages in real time using AI with zero manual involvement. Perfect for support, sales, finance, and internal operations. Benefits Automated Email Triage** – Every unread email is instantly read, analyzed, and classified AI-Powered Categorization** – Uses GPT-4 to understand content and apply correct labels Smart Response Generation** – Automatically drafts accurate replies based on category Slack Notifications** – Instantly notifies your team about internal or sales-related messages Seamless Gmail Integration** – Labels, drafts, and marks emails directly in your inbox Custom Classification Rules** – Tailored to internal, support, sales, finance, and promotional needs How It Works Gmail Trigger: Monitors Gmail inbox in real-time for new unread messages Triggers the workflow every minute with no need for manual refresh Smart Classification: Feeds email body to AI-powered Text Classifier Categories include: Internal, Customer Support, Promotions, Admin/Finance, and Sales Opportunity Classification based on sender domain, keywords, and context AI-Based Labeling: Applies appropriate Gmail label based on classification result Helps keep inbox clean, organized, and easily searchable AI Reply Generation: Specialized GPT-4 agents generate replies tailored to each category: Internal:** Polished team replies Customer Support:** Clear and professional customer responses Promotions:** Summarizes and evaluates promotional value Admin/Finance:** Extracts invoice/payment information Sales Opportunity:** Drafts personalized replies and sales notifications Auto-Drafting + Slack Alerts: Replies are saved as Gmail drafts, ready for review or direct send Sends Slack notifications for Internal or Sales Opportunities Includes subject lines and quick message previews Smart Decision-Making: Promotional emails are evaluated with AI for usefulness Only valuable offers are flagged or responded to Automatically marks emails as read after processing Business Use Cases Customer Support Teams** – Automatically categorize and prep replies to client messages Sales Reps** – Instantly receive drafted responses to new inquiries Operations Managers** – Keep internal comms clear and responsive Finance Departments** – Auto-extract and review payment/invoice messages Founders** – Never miss an important email while your AI sorts and replies for you Difficulty Level: Intermediate Estimated Build Time: 2–4 hours Monthly Operating Cost: $20–80 (depending on OpenAI usage and Slack volume) Required Setup Gmail Integration Set up Gmail OAuth2 connection Create labels: Internal, Customer Support, Promotions, Admin/Finance, Sales Opportunity OpenAI Integration Connect GPT-4 or GPT-4o account Configure role-based prompts for each email category Output structured response data (subject, body, notification) Slack Integration Set up Slack OAuth2 connection Configure target Slack channel Notify team when important categories are triggered System Architecture The workflow follows a powerful 6-stage automation: Trigger – Poll Gmail for new unread emails Classify – AI categorizes the email into the right bucket Label – Applies Gmail label for search and visibility Generate Reply – GPT-4 crafts draft email reply Draft Email – Saves response in Gmail Notify – Optional Slack message alerts for priority emails Why This System Works Inbox Clarity – Keeps your inbox categorized and organized Human Quality Replies – AI-generated messages sound professional and personalized Time-Saving Automation – Handles support, sales, internal ops, and finance without touching your inbox Multi-Agent Architecture – Each email type is handled by a specialized GPT-4 prompt Real Time Reactions – From email receipt to Slack notification in under a minute

✨ Summary Efficiently monitor Kubernetes environments by sending only unique error logs from Grafana Loki to Slack. Reduces alert fatigue while keeping your team informed about critical log events. 🧑‍💻 Who’s it for DevOps or SRE engineers running EKS/GKE/AKS Anyone using Grafana Loki and Promtail for centralized logging Teams that want Slack alerts but hate alert spam 🔍 What it does This n8n workflow queries your Loki logs every 5 minutes, filters only the critical ones (error, timeout, exception, etc.), removes duplicate alerts within the batch, and sends clean alerts to a Slack channel with full metadata (pod, namespace, node, container, log, timestamp). 🧠 How it works 🕒 Schedule Trigger Every 5 minutes (customizable) 🌐 Loki HTTP Query Pulls logs from the last 10 minutes Keyword match: error, failed, oom, etc. 🧹 Log Parsing Extracts log fields (pod, container, etc.) Skips empty/malformed results 🧠 Deduplication Removes repeated error messages (within query window) 📤 Slack Notification Sends nicely formatted message to Slack ⚙️ Requirements Tool Notes Loki- Exposed internally or externally Slack App- With chat:write OAuth n8n- Cloud or self-hosted 🔧 How to Set It Up Import the JSON file into n8n Update: Loki API URL (e.g., http://loki-gateway.monitoring.svc.cluster.local) Slack Bearer Token (via credentials) Target Slack channel (e.g., #k8s-alerts) (Optional) Change keywords in the query regex Activate the workflow Ensure n8n pod/container is having access to your kubernetes cluster/pods/namespaces 🛠 How to Customize Want more or fewer keywords? Adjust the regex in the Query Loki for Error Logs node. Need to increase deduplication logic? Enhance the Remove Duplicate Alerts node. Want 5-log summaries every 5 min? Fork this and add a Batch + Slack group sender. Grafana Loki logs to Slack Output

🛠️ Demio Tool MCP Server Complete MCP server exposing all Demio Tool operations to AI agents. Zero configuration needed - all 4 operations pre-built. ⚡ Quick Setup Need help? Want access to more workflows and even live Q&A sessions with a top verified n8n creator.. All 100% free? Join the community Import this workflow into your n8n instance Activate the workflow to start your MCP server Copy the webhook URL from the MCP trigger node Connect AI agents using the MCP URL 🔧 How it Works • MCP Trigger: Serves as your server endpoint for AI agent requests • Tool Nodes: Pre-configured for every Demio Tool operation • AI Expressions: Automatically populate parameters via $fromAI() placeholders • Native Integration: Uses official n8n Demio Tool tool with full error handling 📋 Available Operations (4 total) Every possible Demio Tool operation is included: 📅 Event (3 operations) • Get an event • Get many events • Register an event 🔧 Report (1 operations) • Get a report 🤖 AI Integration Parameter Handling: AI agents automatically provide values for: • Resource IDs and identifiers • Search queries and filters • Content and data payloads • Configuration options Response Format: Native Demio Tool API responses with full data structure Error Handling: Built-in n8n error management and retry logic 💡 Usage Examples Connect this MCP server to any AI agent or workflow: • Claude Desktop: Add MCP server URL to configuration • Custom AI Apps: Use MCP URL as tool endpoint • Other n8n Workflows: Call MCP tools from any workflow • API Integration: Direct HTTP calls to MCP endpoints ✨ Benefits • Complete Coverage: Every Demio Tool operation available • Zero Setup: No parameter mapping or configuration needed • AI-Ready: Built-in $fromAI() expressions for all parameters • Production Ready: Native n8n error handling and logging • Extensible: Easily modify or add custom logic > 🆓 Free for community use! Ready to deploy in under 2 minutes.