by clancy jack
This n8n workflow recommends Taiwan indie music based on a user's city, mood, birthday, today's weather, and star sign. Here's a concise overview: Trigger: Starts manually with the "When clicking ‘Test workflow’" node. Input Setup: The "infomation" node sets user inputs (e.g., city: Taipei, mood: Happy, birthday: 1996/11/21). Song Recommendation: The "get song recommendation" node uses OpenAI's GPT-4o-mini to: Fetch today's weather for the specified city. Determine the user's zodiac sign from their birthday. Check the zodiac sign's daily fortune. Recommend a Taiwan indie song considering weather and fortune. Explain the song choice and highlight its features. Return results in JSON format. Data Extraction: The "Information Extractor" node parses the JSON output, extracting fields like date, city, weather, zodiac sign, fortune, song, artist, and additional info. Spotify Search: The "Spotify" node searches for the recommended song using the artist and song name, retrieving a Spotify URL. Final Output: The "Final Output" node compiles all data, including the Spotify link, into a structured format. Additional Note: A "Sticky Note" provides context about the workflow's purpose and credits the creator, n8nguide. This workflow integrates AI, weather data, astrology, and Spotify to deliver personalized Taiwan indie music recommendations.
by Agus Narestha
🔒 SSL Certificate Monitoring & Expiry Alert with Spreadsheet [FREE APIs] ✅ What This Workflow Does This n8n template automatically monitors SSL certificates of websites listed in a Google Sheet and sends email alerts if any are expiring within 14 days. It helps ensure you avoid downtime, security issues, and trust warnings due to expired certificates. 🧩 Key Features 📅 Weekly Automation: Runs every Monday at 7:00 AM (configurable). 📄 Google Sheets Integration: Fetches and updates data in a spreadsheet. 🔍 SSL Check via API: Uses ssl-checker.io to get certificate details. ⚠️ SSL Expiry Filter: Identifies certificates expiring within 14 days. 📧 Email Alerts: Sends notifications for certificates close to expiration. 📂 Input Spreadsheet Format Your Google Sheet should have the following columns: | No | Name | Link | SSL Issued On | SSL Expired On | SSL Status | |----|-----------------|-----------------------|-------------------|-------------------|------------| | 1 | Example Site | https://example.com | 2024-07-01 | 2025-07-01 | Valid | | 2 | My Blog | https://myblog.org | 2024-07-05 | 2024-07-20 | Expiring | Each row should include a valid website URL in the Link column. 🛠️ How It Works Scheduled Trigger Executes weekly (Monday 7:00 AM). Fetch Website List Reads all website entries from the Google Sheet. Check SSL Certificates Uses ssl-checker.io API to retrieve certificate details for each website. Update Spreadsheet Writes "Issued On" and "Expired On" fields back to the spreadsheet. Evaluate SSL Expiry Filters for certificates expiring within 14 days. Check Condition Determines whether to send alerts based on filtered results. Send Email Alert Notifies via email if any certificates are expiring soon. 📬 Example Email Output Subject: ⚠️ ALERT!! SSL EXPIRED SSL certificates expiring soon: example.com (expires in 5 days) anotherdomain.net (expires in 3 days) 🧰 Setup Requirements A Google Sheet with the correct columns and website links. SMTP credentials to send alert emails.
by Omar Hdez
Automated Email Assistant for Busy Professionals This assistant is designed for people who don't have time to write and send emails to suppliers. With just one request, it drafts and sends clear, professional messages automatically. How It Works The user makes a request (e.g., “Send an email to my fruit supplier asking for a quote on 1 crate of mangoes.”). Workflow: The AI agent searches for the supplier in a Google Sheets database. It automatically drafts the email using OpenAI (with the tone and style you define). It sends the email using your Gmail account connected through n8n. This assistant uses: Google Sheets to manage your suppliers (name and email). OpenAI to generate clear, natural messages. MCP (client-server logic) to handle request processing. Gmail as the sending channel for automated emails. Setup Instructions Create a Google Sheets document with the supplier name and email, like this: |Supplier name|Email| |-|-| |Proveedor de frutas Alvarez|fruteriaalvarez@alvarez.com| Connect your Google Sheets and Gmail accounts within n8n. Add your OpenAI API key. Test the automation by chatting with the integrated assistant. It will generate and send the email automatically to the indicated supplier. Requirements OpenAI API key to generate email content. Gmail account connected via OAuth2. Google Sheets document with your supplier database. n8n instance (cloud or self-hosted). Customization Adjust the OpenAI prompt to make the email tone more formal, casual, or technical. Add custom fields to your supplier sheet (location, notes, special conditions). Replace Google Sheets with a real database like Supabase or PostgreSQL for greater scalability.
by Gleb D
This n8n workflow automatically retrieves recent Reuters news articles related to a user-specified keyword, summarizes the main findings using Google Gemini, formats the output into styled HTML, and sends a clean email report to a specified address. 🚀 What It Does Collects news data from Bright Data's Reuters dataset. Sorts and filters top 10 most recent news articles by publication_date. Sends structured news data to Gemini Flash for summarization. Converts Gemini's response (in Markdown) into styled HTML. Delivers a concise news briefing via email, including clickable source links and topic highlights. 🛠️ Step-by-Step Setup User Form: Accepts a keyword from the user via an n8n form trigger. Bright Data API: Posts a discover_new request to Bright Data's Reuters dataset using the keyword. Snapshot Polling: Waits and checks for dataset readiness using the snapshot ID. Data Retrieval: Downloads the news data once the snapshot is complete. Parsing: Filters and sorts the latest 10 articles using a Python Code node. AI Analysis: Google Gemini summarizes the filtered content into one briefing. Markdown → HTML: Converts AI response into styled HTML using Markdown + Code node. Email Delivery: Sends the briefing as an email to a predefined recipient. 🧠 How It Works Polling Control: Uses Wait and If nodes to handle Bright Data snapshot readiness. Date Sorting: Publication dates (ISO 8601 format) are parsed and used for sorting. AI Summarization: Gemini condenses multiple articles into one cohesive summary. Formatting: Clean HTML with readable styles is generated dynamically before sending. 📨 Final Output The email includes: A brief summary of the most important developments Date range of the collected news Topics covered 🔐 Credentials Used Bright Data API (replace YOUR_API_KEY in the HTTP nodes) Google Gemini (Flash) API Email SMTP (configured in Email Send node) ⚠️ Notes You must replace all YOUR_API_KEY placeholders in Bright Data request headers with your actual Bright Data API key. You can customize the keyword prompt and output style freely. I would recommend to keep the sort = relevance option for best chronological results - sorting by date is handled later.
by Amit Mehta
How it Works This workflow automates the complete newsletter management process from content creation to client delivery, using Google Sheets, AI content generation, Google Drive, and Gmail. Whether you're a content creator, marketing agency, or small business owner, this workflow helps you automate newsletter creation and manage client communications with built-in approval workflows — all triggered from a simple spreadsheet. 🎯 Use Case Ideal for: Marketing Teams** streamlining newsletter distribution Agencies** managing multiple client newsletters Content Creators** automating regular communications Small Businesses** maintaining customer engagement Setup Instructions 1. Upload the Spreadsheet File name: Newsletter_Management Sheet structure: | ID | Topic | Client Name | Client Email | Status | Created Date | Send Date | Add newsletter topics and set their Status as Pending 2. Configure Google Sheets Nodes Connect your Google account to: Get topic from newsletter sheet Pick records to send email to client Get Client email address Update Status as Generated Update status as Sent 3. Add API Credentials OpenAI API Key** → for AI content generation Google Drive Access** → for document storage Gmail Account** → for sending newsletters and notifications 4. Activate the Workflow Once live, the workflow will: Manual Path: Generate newsletter content from pending topics Scheduled Path: Send approved newsletters to clients automatically Track status updates throughout the entire process Store generated content in Google Drive Send admin notifications and client emails 🔁 Workflow Logic Main Workflow (Content Generation) Trigger: Manual activation for newsletter creation Retrieve: Pending topics from Google Sheets Validate: Status confirmation (Pending only) Generate: AI-powered HTML newsletter content Store: Upload to Google Drive Notify: Send completion email to admin Update: Mark status as "Generated" Scheduled Workflow (Client Distribution) Trigger: Schedule-based activation Retrieve: Approved newsletters from Google Sheets Validate: Status confirmation (Approved only) Lookup: Client email addresses Loop: Process multiple recipients Send: Personalized newsletters via Gmail Update: Mark status as "Sent" 🧩 Node Descriptions | Node Name | Description | |-----------|-------------| | When clicking 'Test workflow' | Manual trigger to start newsletter generation | | Get topic from newsletter sheet | Retrieves pending newsletter topics from Google Sheets | | Validate Status as Pending | Checks whether status is 'Pending' for processing | | Create HTML for Newsletter | AI-powered content generation using OpenAI | | Prepare Data to create word doc | Formats generated content for document creation | | Upload doc to google drive | Stores completed newsletters in Google Drive | | Send an email to admin | Notifies administrators of completion | | Update Status as Generated | Marks processed items as 'Generated' | | Schedule Trigger | Automated trigger for client email distribution | | Pick records to send email to client | Retrieves approved newsletters for sending | | Validate Status as Approved | Ensures only approved content is processed | | Get Client email address | Fetches client contact information | | Loop Over Items | Processes multiple newsletter recipients | | Send email to client | Delivers personalized newsletters via Gmail | | Update status as Sent | Marks newsletters as successfully delivered | 🛠️ Customization Tips Modify AI prompts for different content styles and tones Add Slack notifications instead of or alongside Gmail Export to different formats (PDF, Word, etc.) Schedule multiple sending times for different client segments Add approval workflows with webhook triggers Integrate with CRM systems for client management 📒 Suggested Sticky Notes for Workflow | Node/Section | Sticky Note Content | |--------------|---------------------| | Manual Trigger | "Click to start newsletter generation process" | | AI Content Generation | "Customize prompts here for different newsletter styles" | | Google Drive Upload | "Organized storage - change folder structure as needed" | | Gmail Admin Notification | "Update admin email addresses and notification templates" | | Schedule Trigger | "Set optimal sending times for your audience" | | Client Email Loop | "Handles bulk sending - monitors for delivery errors" | | Status Updates | "Maintains audit trail - prevents duplicate processing" | 📎 Required Files | File Name | Purpose | |-----------|---------| | Newsletter_Management.xlsx | Google Sheet to manage topics, clients, and status tracking | | Client_Database.xlsx | Client contact information and preferences | | Newsletter_Workflow.json | Main n8n workflow export for this automation | 🧪 Testing Tips Add one test topic with status = Pending and run manual trigger Verify AI content generation produces quality HTML Check Google Drive upload and folder organization Test admin email delivery and formatting Add test client with valid email for scheduled workflow Monitor workflow logs for API responses and errors Confirm status updates occur at each step 🏷 Suggested Tags & Categories #Newsletter #EmailMarketing #ContentGeneration #ClientCommunication #Automation #GoogleWorkspace #AIContent #MarketingAutomation #WorkflowManagement #BusinessProcess 🔧 Prerequisites Google Workspace account (Sheets, Drive, Gmail) OpenAI API account with GPT-4 access n8n instance (Cloud or self-hosted) Basic understanding of Google Sheets and email marketing 📊 Expected Performance Setup Time**: 30-45 minutes Monthly Executions**: 100-500 (varies by newsletter frequency) Processing Time**: 2-5 minutes per newsletter Scalability**: Handles 100+ clients efficiently 🚨 Important Notes Ensure proper Google API permissions are configured Monitor OpenAI API usage and rate limits Set up error handling for failed email deliveries Regularly backup your Google Sheets data Test thoroughly before production deployment 💡 Advanced Features Approval Workflows**: Add manual approval steps between generation and sending A/B Testing**: Create multiple versions and track performance Analytics Integration**: Connect with Google Analytics for tracking Multi-language Support**: Generate content in different languages Dynamic Personalization**: Use client data for personalized content
by Jakkrapat Ampring
Description Quickly organize your inbox with AI! This simple workflow automatically classifies incoming emails into different categories — like High Priority, Work Related, or Promotions — and applies Gmail labels accordingly. Setup takes less than 2 minutes, and it runs 24/7, helping you stay focused on what matters most without manual sorting. Tools/Services Needed Gmail: To trigger the workflow and label emails. Google Gemini (or any LLM Model): To intelligently classify email content. How It Works Gmail Trigger: Detects every new incoming email. Text Classifier Node: Classifies the email content into predefined categories. Google Gemini Chat Model: Provides the AI-powered understanding behind the classification. Conditional Labeling: If the email is High Priority, label it accordingly. If it’s Work Related (e.g., internal emails), apply the work label. If it’s a Promotion, sort it into the promotions label. Gmail Labeling: Automatically adds the correct label to the email. Setup Instructions Connect your Gmail account to n8n. Connect your Google Gemini (or other LLM) credentials. Customize the categories and labels if needed. Activate the workflow — and that's it! Notes You can easily add more categories (like "Finance," "Newsletters," etc.) by adjusting the classification prompt. Works best with a clean and minimal set of categories to avoid overlap. Can be adapted to work with any other large language model (OpenAI, Claude, etc.) if preferred.
by Ranjan Dailata
Notice Community nodes can only be installed on self-hosted instances of n8n. Who this is for? This workflow template enables intelligent data extraction from ProductHunt using Bright Data’s Model Context Protocol (MCP) and processes search results with Google Gemini. This workflow is designed for individuals and teams who need automated, intelligent discovery and analysis of new tech products. It's especially valuable for: Startup Analysts & VC Researchers Growth Hackers & Marketers Recruiters & Tech Scouts Product Managers & Innovation Teams AI & Automation Enthusiasts What problem is this workflow solving? Traditional product discovery on ProductHunt is constrained by limited descriptions and requires repeated manual validation through web searches. Manually extracting and enriching this data is slow, repetitive, and error-prone. This workflow solves the problem by: Extracting real-time ProductHunt data using Bright Data’s MCP infrastructure to mimic real-user behavior and avoid blocks. Performing contextual searches on Google for a specific product on ProductHunt to gather use cases, reviews, and related information. Structuring results using Google Gemini LLM to provide human-readable insights and reduce noise. Delivering results seamlessly by saving output to disk, updating Google Sheets, and sending Webhook alerts. What this workflow does Input Field Node Define the ProductHunt category with the search term(s) you want to target. This is used to drive extraction and search operations. Agent Operation Node The agent performs two major tasks: Extract from ProductHunt Retrieves trending products from ProductHunt using Bright Data MCP Contextual Google Search for the product the agent searches Google for deeper context, including: Reviews Competitor mentions Real-world usage examples LLM Node (Google Gemini) Analyzes and summarizes extracted web content Removes noise (ads, menus, etc.) Structures content into bullet points, insights, or JSON objects Pre-conditions Knowledge of Model Context Protocol (MCP) is highly essential. Please read this blog post - model-context-protocol You need to have the Bright Data account and do the necessary setup as mentioned in the Setup section below. You need to have the Google Gemini API Key. Visit Google AI Studio You need to install the Bright Data MCP Server @brightdata/mcp You need to install the n8n-nodes-mcp Setup Please make sure to setup n8n locally with MCP Servers by navigating to n8n-nodes-mcp Please make sure to install the Bright Data MCP Server @brightdata/mcp on your local machine. Sign up at Bright Data. Create a Web Unlocker proxy zone called mcp_unlocker on Bright Data control panel. Navigate to Proxies & Scraping and create a new Web Unlocker zone by selecting Web Unlocker API under Scraping Solutions. In n8n, configure the Google Gemini(PaLM) Api account with the Google Gemini API key (or access through Vertex AI or proxy). In n8n, configure the credentials to connect with MCP Client (STDIO) account with the Bright Data MCP Server as shown below. Make sure to copy the Bright Data API_TOKEN within the Environments textbox above as API_TOKEN=<your-token> How to customize this workflow to your needs This workflow is flexible and modular, allowing you to adapt it for various research, product discovery, or trend analysis use cases. Below are the key customization points and how to modify them. Define Your Target Products or Topics: Change the input parameter to a specific ProductHunt category, tag, or keyword (e.g., "AI tools", "SaaS", "DevOps") Change Output Destinations : Save to Disk**: Change the file format (.json, .csv, .md) or directory path Google Sheet**: Modify sheet name, structure (columns like Product, Summary, Link) Webhook Notification**: Point to a Slack/Discord/CRM/Webhook URL with payload mapping
by David Olusola
PromptCraft AI – Telegram Image Generator 🚀 How It Works PromptCraft AI is an n8n automation that transforms simple image ideas sent through Telegram into stunning AI-generated images using OpenAI's DALL·E (or other image models). 🔁 Workflow Overview: Telegram Trigger: Listens for messages from a user on Telegram. Prompt Expansion: The message is transformed into a rich image description using GPT (OpenAI Chat Model). Image Generation: The prompt is passed to OpenAI's image API to generate a high-quality image. Send Image: The final image is sent back to the user on Telegram. (Optional) Log image titles and links to Google Drive and Google Sheets. ⚙️ Setup Instructions 📋 Prerequisites [ ] n8n installed (Self-hosted or via n8n.cloud) [ ] Telegram bot token (via @BotFather) [ ] OpenAI API key (platform.openai.com) [ ] Google Sheets & Drive OAuth2 credentials (optional) 🧠 Step-by-Step Configuration 1. 📥 Import the Workflow Go to n8n → click Import → upload PromptCraft_AI_Template.json 2. 🔐 Set Up Credentials In Credentials, add the following: Telegram API → Paste your bot token OpenAI API → Paste your OpenAI API key (Optional) Google Sheets OAuth2, Google Drive OAuth2 3. 🔄 Replace Placeholders Open each node that requires credentials: Replace REPLACE_OPENAI_API_KEY with your actual OpenAI API key Replace REPLACE_TELEGRAM_API_ID and credential names as needed (Optional) Update Google Drive Folder ID & Sheet ID in respective nodes 4. ✅ Activate the Workflow Turn on the Telegram Trigger node. Deploy and activate the full workflow. 5. ✉️ Test It Out Send your Telegram bot a message like: > a knight riding a robotic horse in the future Receive the generated image back in Telegram! 💡 Pro Tips Use detailed or imaginative inputs for better outputs. Fine-tune the GPT prompt for specific visual styles. Extend with Google Vision, image upscaling, or watermarking. 🛟 Support For setup assistance or custom feature requests, feel free to contact me @dimejicole21@gmail.com Happy Prompting! 🖼✨
by Jez
This n8n workflow template uses community nodes and is only compatible with the self-hosted version of n8n. This workflow demonstrates how to build and expose a sophisticated n8n AI Agent as a single, callable tool using the Multi-Agent Collaboration Protocol (MCP). It allows external clients or other AI systems to easily query software library documentation via Context7, without needing to manage the underlying tool orchestration or complex conversational logic. Core Idea: Instead of building complex agentic loops on the client-side (e.g., in Python, a VS Code extension, or another AI development environment), this workflow offloads the entire agent's reasoning and tool-use process to n8n. The client simply sends a natural language query (like "How do I use Flexbox in Tailwind CSS?") to an SSE endpoint, and the n8n agent handles the rest. Key Features & How It Works: Public MCP Endpoint: The main workflow uses the Context7 MCP Server Trigger node to create an SSE endpoint. This makes the agent accessible to any MCP-compatible client. The path for the endpoint is kept long and random for basic 'security by obscurity'. Tool Workflow as an Interface: A Tool Workflow node (named call_context7_ai_agent in this example) is connected to the MCP Server Trigger. This node defines the single "tool" that external clients will see and call. Dedicated AI Agent Sub-Workflow: The call_context7_ai_agent tool invokes a separate sub-workflow which contains the actual AI logic. This sub-workflow starts with a Context7 Workflow Start node to receive the user's query. A Context7 AI Agent node (using Google Gemini in this example) is the brain, equipped with: A system prompt to guide its behavior. Simple Memory to retain context for each execution (using {{ $execution.id }} as the session key). Two specialized Context7 MCP client tools: context7-resolve-library-id: To convert library names (e.g., 'Next.js') into Context7-specific IDs. context7-get-library-docs: To fetch documentation using the resolved ID, with options for specific topics and token limits. Seamless Tool Use: The AI Agent autonomously decides when and how to use the resolve-library-id and get-library-docs tools based on the user's query, handling the multi-step process internally. Benefits of This Approach: Simplified Client Integration:** Clients interact with a single, powerful tool, sending a simple query. Reduced Client-Side Token Consumption:** The detailed prompts, tool descriptions, and conversational turns are managed server-side by n8n, saving tokens on the client (especially useful if the client is another LLM). Centralized Agent Management:** Update your agent's capabilities, tools, or LLM model within n8n without any changes needed on the client side. Modularity for Agentic Systems:** Perfect for building complex, multi-agent systems where this n8n workflow can act as a specialized "expert" agent callable by others (e.g., from environments like Smithery). Cost-Effective:** By using a potentially less expensive model (like Gemini Flash) for the agent's orchestration and leveraging the free tier or efficient pricing of services like Context7, you can build powerful solutions economically. Use Cases: Providing an intelligent documentation lookup service for coding assistants or IDE extensions. Creating specialized AI "micro-agents" that can be consumed by larger AI applications. Building internal knowledge base query systems accessible via a simple API-like interface. Setup: Ensure you have the necessary n8n credentials for Google Gemini (or your chosen LLM) and the Context7 MCP client tools. The Path in the Context7 MCP Server Trigger node should be unique and secure. Clients connect to the "Production URL" (SSE endpoint) provided by the trigger node. This workflow is a great example of how n8n can serve as a powerful backend for building and deploying modular AI agents. I've made a video to try and explain this a bit too https://www.youtube.com/watch?v=dudvmyp7Pyg
by Automate With Marc
🧠 Google Drive Upload Trigger → Pinecone Vector Upsert for Document Indexing Category: AI & LLM / Document Indexing Level: Intermediate Tags: Google Drive, Pinecone, OpenAI, Embeddings, Vector Store, LangChain, RAG 📄 What This Workflow Does This workflow watches a specific Google Drive folder and automatically uploads any newly added document to a Pinecone vector database — complete with OpenAI-generated embeddings. Perfect for setting up retrieval-augmented generation (RAG) pipelines, semantic search, or document Q&A systems. Once configured, your knowledge base stays up-to-date with zero manual effort. Watch Full Step By Stey Tutorial Video Here: https://www.youtube.com/@Automatewithmarc 🔧 How It Works 📁 Google Drive Trigger Watches a specific folder and triggers when new documents are uploaded. 🔍 Google Drive File Search & Download Finds and fetches all files in the folder. 🔄 Loop Over Each File Handles batch processing for multiple files. 📃 Document Loader Parses each file as binary and applies custom metadata like document type. ✂️ Text Splitter Breaks content into manageable chunks for embedding (e.g., 600 characters, 60 overlap). 🧠 OpenAI Embeddings Generates vector embeddings using OpenAI. 📦 Pinecone Vector Store Inserts/upserts documents into a specific Pinecone namespace for search-ready indexing. 🧠 Why This is Useful This is a production-grade setup for: Building vector search tools over internal docs Feeding up-to-date data into RAG agents or chatbots Auto-tagging and chunking files for scalable AI workflows Whether you’re indexing course outlines, SOPs, or technical docs — this automation keeps your vector store fresh and organized. 🪜 Setup Instructions Connect your Google Drive, OpenAI, and Pinecone accounts. Specify the Google Drive folder to monitor. Customize metadata, chunk size, or vector namespace as needed. Activate the workflow and drop a file into the folder — magic happens behind the scenes. 📌 Notes Works best with PDFs or text-based documents. You can swap out OpenAI with other embedding models if needed. Consider adding notifications or logging (e.g., via Slack or email) for better observability.
by ARRE
Good to know: This workflow automatically processes product images from Google Drive, generates AI-powered background prompts using multiple AI models (ChatGPT, Claude, or Groq), creates professional background scenes using Pixelcut.ai, and saves enhanced images back to your Google Drive. Perfect for e-commerce businesses and product photography workflows. Who is this for? ➖E-commerce store owners who need professional product backgrounds ➖Product photographers looking to automate background generation ➖Marketing teams creating consistent product imagery ➖Small businesses wanting to enhance their product photos without expensive studio setups ➖Anyone who needs to quickly transform transparent product images into commercial-ready photos What problem is this workflow solving? This workflow solves the challenge of creating professional product photography backgrounds at scale. Instead of manually editing each product image or setting up expensive photo shoots, it automatically generates contextually appropriate backgrounds for your products using AI technology. It eliminates the time-consuming process of background creation while maintaining professional quality and consistency across your product catalog. What this workflow does: ✅Automatically fetches product images from your Google Drive folder ✅Downloads transparent/background-free product images ✅Uses advanced AI models (ChatGPT, Claude, or Groq) to generate intelligent background prompts based on product analysis ✅Creates professional backgrounds using Pixelcut.ai API with AI-generated or custom prompts ✅Saves enhanced product images back to Google Drive with organized naming ✅Processes multiple images in batch automatically How it works: 1️⃣Google Drive node searches for PNG product images in your specified folder 2️⃣Binary download node retrieves the actual image files for processing 3️⃣Optional AI agent analyzes products using your chosen AI model (OpenAI GPT-4, Claude, or Groq) and generates appropriate background prompts 4️⃣Pixelcut.ai API processes images and adds professional backgrounds using AI-generated or manual prompts 5️⃣Enhanced images are automatically saved back to Google Drive with "enhanced-" prefix How to use: Set up Google Drive OAuth2 credentials in n8n Create a Pixelcut.ai account and get your API key Configure your source folder ID in the Google Drive nodes Set up your output folder ID for enhanced images Choose and configure your preferred AI model credentials (OpenAI for ChatGPT, Anthropic for Claude, or Groq) Replace placeholder API keys with your actual credentials Execute the workflow to process your product images Requirements: ✅n8n instance (cloud or self-hosted) ✅Google Drive account with OAuth2 access ✅Pixelcut.ai API account and key ✅Product images in PNG format (transparent backgrounds recommended) ✅AI API credentials for automatic prompt generation (choose from): OpenAI API (for ChatGPT/GPT-4) Anthropic API (for Claude) Groq API (for fast inference) ✅Basic understanding of n8n workflows Customizing this workflow: 🟢Modify the image format filter to support JPG, WEBP, or other formats 🟢Switch between different AI models (ChatGPT, Claude, Groq) for prompt generation 🟢Customize background prompts for different product categories 🟢Add background removal step for products with existing backgrounds 🟢Switch to different AI background services (Deep-Image.ai, Remove.bg, etc.) 🟢Configure different AI model parameters for varied prompt creativity 🟢Add image resizing or quality optimization steps 🟢Create multiple output folders for different product categories 🟢Add error handling and retry mechanisms for failed processes 🟢Implement A/B testing with different AI models for prompt quality comparison
by Daniel Shashko
How it Works Disclaimer: This template is for self-hosted n8n instances only. This workflow is designed for developers, data analysts, and automation enthusiasts seeking to automate personalized news collection and delivery. It seamlessly combines n8n, OpenAI (e.g., GPT-4.1), and Bright Data’s Model Context Protocol (MCP) to collect, extract, and email the latest global news headlines. On a schedule or via a manual trigger, the workflow prompts an AI agent to gather fresh news. The agent leverages context-aware memory and integrated MCP tools to conduct both search engine queries and direct web page scraping in real time, delivering more than just meta search results—it extracts actual on-page headlines and trusted links. Results are formatted and delivered automatically by email via your SMTP provider, requiring zero manual effort once configured. Who is this for? Developers, data engineers, or automation pros wanting an AI-powered, fully automated newsfeed Teams needing up-to-date news digests from trusted global sources Anyone self-hosting n8n who wishes to combine advanced LLMs with real-time web data Setup Steps Setup time: Approx. 15–30 minutes (n8n install, API configuration, node setup) Requirements: Self-hosted n8n instance OpenAI API key Bright Data MCP account credentials SMTP/email provider details Install the community MCP node (n8n-nodes-mcp) for n8n and set up Bright Data MCP access. Configure these nodes: Schedule Trigger: For automated delivery at your chosen interval. Edit Fields: To inject your AI news collection prompt. AI Agent: Connects to OpenAI and MCP, enabled with memory for context. OpenAI Chat Model: Connects via your OpenAI credentials. MCP Clients: Configure at least two—one for search (e.g. search_engine) and one for scraping (e.g. scrape_as_markdown). Send Email: Set up with recipient and SMTP information. Credentials must be entered into their respective nodes for successful execution. Customization Guidance Prompt Tweaks:** Refine your AI news prompt to target specific genres, regions, or sources, or broaden/narrow the coverage as needed. Tool Configuration:** Carefully define tool descriptions and parameters in MCP client nodes so the agent can pick the best tool for each step (e.g., only scrape real news sites). Delivery Settings:** Adjust email recipient(s) and SMTP details as needed. Workflow Enhancements:** Use sticky notes in n8n for extended documentation, alternate prompts, or troubleshooting tips. Run Frequency:** Set schedule as needed—from hourly to daily updates. Once configured, this workflow will automatically gather, extract, and email curated news headlines and links—no manual curation required!