Workflow Templates

Website AI Agent with Calendar Integration Categories: AI Agents, Website Integration, Calendar Automation This workflow creates a complete website AI agent that can be embedded on any website with just a few lines of code. The agent handles customer inquiries, provides business information, and automatically books meetings by checking calendar availability in real-time. Built for simplicity and business practicality, this system proves that effective AI agents don't need to be overcomplicated. Benefits Universal Website Integration** - Works with WordPress, Webflow, Squarespace, custom sites, or any platform that accepts HTML Intelligent Calendar Management** - Checks availability and books meetings automatically without double-booking Business-Ready Conversations** - Trained with specific business context and maintains professional, helpful interactions Real-Time Functionality** - All changes to the N8N workflow are immediately reflected on your live website No Technical Complexity** - Simple architecture that prioritizes reliability and consistent outputs over flashy features Customizable Branding** - Easy to modify appearance, messages, and behavior to match your brand How It Works Embedded Chat Interface: Generates embeddable HTML code that creates a chat widget on any website Provides both hosted and embedded modes for different use cases Handles all communication between website visitors and the AI system Intelligent Conversation Management: Uses sophisticated system prompts to maintain context about your business Handles common inquiries about services, pricing, and company information Gracefully redirects off-topic conversations back to business matters Smart Calendar Integration: Connects to Google Calendar to check real-time availability Automatically suggests meeting times based on your schedule Collects all necessary information (name, email, preferred time) before booking Meeting Booking Process: Validates meeting requests against existing calendar entries Confirms all details with users before creating calendar events Sends automatic invitations with proper timezone handling Required Setup Configuration System Message Requirements: Your AI agent needs a comprehensive system message that includes: Business Identity:** Company name, services, location, timezone Business Context:** What you offer, pricing information, key differentiators Conversation Rules:** How to handle inquiries, booking procedures, moderation guidelines Personality Instructions:** Tone of voice, response style, conversation length preferences Example System Message Structure: You are a helpful, intelligent website chatbot for [Company Name], a [business type]. The current date is [dynamic date]. You are in the [timezone] timezone. Business Context: We offer [services] with [key benefits] Our pricing is [pricing structure] We work with [target customers] Your task is answering questions about the business & booking meetings. For meetings: use calendar function to check availability, collect name/email/preferred time, confirm details. Rules: Keep responses short and conversational Stay focused on business topics Always confirm timezone when discussing meeting times Google Calendar Setup: Enable Google Calendar API in Google Cloud Console Create OAuth2 credentials for N8N Connect your business calendar in the Google Calendar nodes Set correct timezone in both nodes to match your business location Website Integration: Switch chat trigger to "embedded" mode Copy the provided CDN embed code Paste code into your website's HTML (before closing body tag) Replace webhook URL with your production URL Business Use Cases Service Businesses** - Automate initial consultations and lead qualification Agencies** - Handle project inquiries and schedule discovery calls Consultants** - Streamline the booking process for potential clients E-commerce** - Provide product support and schedule demos Any Business** - Replace contact forms with intelligent conversation Revenue Potential This system can replace expensive chatbot services that cost $100-500/month. The automated booking feature alone typically increases meeting conversion rates by 40-60% compared to traditional contact forms. Difficulty Level: Beginner Estimated Build Time: 15-20 minutes Monthly Operating Cost: ~$10 (OpenAI API usage) Watch My 13-Minute Build Want to see exactly how I built this from scratch? I walk through the complete setup process in real-time, including all the configuration, testing, and website integration. 🎥 See My Complete Build Process: "How to Build a Website AI Agent in 13 Min (Free N8N Template)" This step-by-step tutorial shows you my exact process for creating business-ready AI agents that actually make money, not just impressive demos. Set Up Steps Basic Agent Configuration: Create new N8N workflow with AI Agent node Connect OpenAI Chat Model with your API credentials Add Window Buffer Memory for conversation context System Message Setup: Configure detailed business context and operating instructions Set timezone and personality parameters for consistent responses Define conversation rules and moderation guidelines Google Calendar Integration: Set up Google Calendar credentials through Google Cloud Console Configure "Get All Events" tool for availability checking Set up "Create Event" tool for automated booking Website Embedding: Switch chat trigger to "embedded" mode for website integration Copy the provided CDN embed code Paste code into your website's HTML with your webhook URL Customization Options: Modify initial messages and branding in the embed code Adjust colors and styling using CSS variables Configure timezone settings to match your business location Testing & Optimization: Test complete conversation flows from inquiry to booking Verify calendar integration works correctly with your timezone Optimize system prompts based on actual user interactions Advanced Features Extend this system with additional capabilities: CRM Integration** - Automatically add leads to your sales pipeline Multi-language Support** - Handle conversations in different languages Custom Business Logic** - Add specific qualification questions or routing Analytics Tracking** - Monitor conversation patterns and conversion rates Check Out My Channel For more practical automation systems that generate real business value, check out my YouTube channel where I share the exact strategies I used to scale my automation agency to $72K/month.

🧩 Workflow: Process Tour PDF from Google Drive to Pinecone Vector DB with OpenAI Embeddings Overview This workflow automates the process of extracting tour information from PDF files stored in a Google Drive folder, processes and vectorizes the extracted data, and stores it in a Pinecone vector database for efficient querying. This is especially useful for building AI-powered search or recommendation systems for travel packages. Setup: Prerequisites A folder in Google Drive with PDF tour package brochures. Pinecone account + API key OpenAI API key n8n cloud or self-hosted instance Workflow Setup Steps Trigger Manual Trigger (When clicking 'Test workflow'): Used for manual testing and execution of the workflow. Google Drive Integration Step 1: Store Tour Packages in PDF Format Upload your curated tour packages containing the tours, activities and sight-seeings in PDF format into a designated Google Drive folder. Step 2: Search Folder Node: PDF Tour Package Folder (Google Drive) This node searches the designated folder for files (filter by MIME type = application/pdf if needed). Step 3: Download PDFs Node: Download Package Files (Google Drive) Downloads each matching PDF file found in the previous step. Process Each PDF File Step 4: Loop Through Files Node: Loop Over each PDF file Iterates through each downloaded PDF file to extract, clean, split, and embed. Data Preparation & Embedding Step 5: Data Loader Node: Data Loader Reads each PDF’s content using a compatible loader. It passes clean raw text to the next node. Often integrated with document loaders like pdf-loader, Unstructured, or pdfplumber. Step 6: Recursive Text Splitter Node: Recursive Character Text Splitter Splits large chunks of text into manageable segments using overlapping window logic (e.g., 500 tokens with 50 token overlap). This ensures contextual preservation for long documents during embedding. Step 7: Generate Embeddings Node: Embeddings OpenAI Uses text-embedding-3-small model to vectorize the split chunks. Outputs vector representations for each content chunk. Store in Pinecone Step 8: Pinecone Vector Store Node: Pinecone Vector Store - Store... Stores each embedding along with its metadata (source PDF name, chunk ID, etc.). This becomes the basis for fast, semantic search via RAG workflows or agents. 🛠️ Tools & Nodes Used Google Drive (Search & Download) Searches for all PDF files in a specified Google Drive folder. Downloads each file for processing. SplitInBatches (Loop Over Items) Loops through each file found in the folder, ensuring each is processed individually. Default Data Loader (LangChain) Reads and extracts text from the PDF files. Recursive Character Text Splitter (LangChain) Splits the extracted text into manageable chunks for embedding. OpenAI Embeddings (LangChain) Converts each text chunk into a vector using OpenAI’s embedding model. Pinecone Vector Store (LangChain) Stores the resulting vectors in a Pinecone index for fast similarity search and querying. 🔗 Workflow Steps Explained Trigger: The workflow starts manually for testing or can be scheduled. Google Drive Search: Finds all PDF files in the specified folder. Loop Over Files: Each file is processed one at a time using the SplitInBatches node. Download File: Downloads the current PDF file from Google Drive. Extract Text: The Default Data Loader node reads the PDF and extracts its text content. *Text Splitting: * The Recursive Character Text Splitter breaks the text into chunks (e.g., 1000 characters with 50 overlap) to optimize embedding quality. **Vectorization: **Each chunk is sent to the OpenAI Embeddings node to generate vector representations. Store in Pinecone: The vectors are inserted into a Pinecone index, making them available for semantic search and recommendations. 🚀 What Can Be Improved in the Next Version? *Error Handling: * Add error handling nodes to manage failed downloads or extraction issues gracefully. File Type Filtering: Ensure only PDF files are processed by adding a filter node. Metadata Storage: Store additional metadata (e.g., file name, tour ID) alongside vectors in Pinecone for richer search results. *Parallel Processing: * Optimize for large folders by processing multiple files in parallel (with care for API rate limits). Automated Triggers: Replace manual trigger with a time-based or webhook trigger for full automation. Data Validation: Add checks to ensure extracted text contains valid tour data before vectorization. User Feedback: Integrate notifications (e.g., email or Slack) to inform when processing is complete or if issues arise. 💡 Summary This workflow demonstrates how n8n can orchestrate a powerful AI data pipeline using Google Drive, LangChain, OpenAI, and Pinecone. It’s a great foundation for building intelligent search or recommendation features for travel and tour data. Feel free to ask for more details or share your improvements! Let me know if you want to see a specific part of the workflow or need help with a particular node!

Supercharge Your Security Operations for Free Stop wasting time manually investigating suspicious IP addresses. This workflow template is your launchpad to automating real-time IP cybersecurity analysis using the NixGuard platform, which you can use for free. This is the first of a two-part system designed to integrate seamlessly into your existing security stack, especially with Wazuh. It calls our main workflow, Automate IP Reputation Checks and Get AI Risk Summaries from NixGuard, to do the heavy lifting. What This Workflow Unlocks for You Free AI-Powered Risk Summaries:** Don't just get data; get answers. NixGuard provides a clear, human-readable summary of why an IP is considered risky. Automated IP Reputation Checks:** Programmatically check any IP against a vast array of threat intelligence sources. A Foundation for Your SOC Automation:** Use the results to trigger your incident response process. The template includes a pre-built example of how to send a detailed alert to Slack, which you can easily adapt for Jira, TheHive, or any other tool. How the Two-Workflow System Works This "Dispatcher" workflow is designed for flexibility. It holds your API key and input, then calls the main analysis workflow. This allows you to easily create multiple triggers (e.g., one for Slack bots, one for webhooks) without duplicating the core logic. Critical Setup Instructions Get the Main Workflow: First, add the main analysis engine to your n8n instance from the community page: NixGuard Analysis Workflow. Add Your Free API Key: In this workflow, click the blue Set API Key & Initial Prompt node. Paste your free NixGuard API key into the apiKey value field. Connect The Workflows: Click the purple Execute NixGuard & Wazuh Workflow node. In the parameters, use the dropdown to select the main analysis workflow you added in Step 1. Ready to automate your threat intelligence? Get your free API key and learn more at; 🔗 Learn more about NixGuard: [thenex.world](thenex.world )🔗 Get started with a free security subscription: thenex.world/security/subscribe Tags: Free, IP Analysis, NixGuard, Wazuh, Security, Automation, AI, Cybersecurity, Threat Intelligence, SOC, Incident Response, IP Reputation, DevSecOps, API

⚡ AI Copywriter Pro: Instant Ad Copy & CTA Generator Transform product details into compelling marketing copy in seconds. This intelligent n8n workflow takes basic product information and generates professional ad copy with powerful calls-to-action using GPT-4, then distributes the results to your team via Slack or stores them in Airtable for future use. 🚀 How It Works This streamlined 4-step automation delivers professional marketing copy instantly: Step 1: Simple Form Input Users submit basic product information through a clean web form - just product name and key features required. Step 2: AI-Powered Generation The workflow sends product details to GPT-4 with a specialized copywriting prompt that creates: Compelling 2-sentence ad copy optimized for conversions 3 powerful call-to-action phrases with different urgency levels Professional tone tailored for marketing campaigns Step 3: Structured Processing The AI response is automatically parsed into clean, labeled fields ready for immediate use across marketing channels. Step 4: Multi-Channel Distribution Generated content is simultaneously: Posted to your designated Slack channel for team review Logged in Airtable for campaign tracking and reuse ⚙️ Setup Steps Prerequisites Active OpenAI API account with GPT-4 access Slack workspace with admin permissions Airtable account for content storage n8n instance (cloud or self-hosted) Configuration Steps 1. Credential Setup OpenAI API Key**: Required for GPT-4 content generation Slack OAuth2**: Needed for posting messages to channels Airtable Personal Access Token**: Essential for database operations 2. Form Configuration The workflow automatically generates a web form at: your-n8n-instance.com/form/[webhook-id] Form fields are pre-configured for: Product Name (text input) Product Features (textarea for detailed descriptions) Form can be embedded on websites or shared as standalone link 3. Slack Integration Setup Connect your Slack workspace to n8n Create or select target channel for ad copy notifications Update the channelId parameter with your channel's ID Test connection with sample message 4. Airtable Database Preparation Create new base or use existing one Set up table with columns: Product Name (Single line text) Product Features (Long text) Ad Copy (Long text) CTAs (Long text) Copy base and table IDs from Airtable URLs Update workflow parameters accordingly 5. AI Prompt Customization The default prompt generates versatile marketing copy, but you can customize for: Industry-specific terminology Brand voice and tone Target audience demographics Campaign objectives (awareness, conversion, retention) 🎯 Use Cases E-commerce & Retail Product Launch Campaigns**: Generate copy for new product announcements Seasonal Promotions**: Create urgency-driven messaging for sales events Category Pages**: Develop compelling descriptions for product collections Social Media Ads**: Produce scroll-stopping copy for Facebook and Instagram SaaS & Technology Feature Announcements**: Craft clear, benefit-focused messaging Free Trial Campaigns**: Generate conversion-optimized trial signup copy Case Study Promotions**: Create compelling success story headlines Webinar Marketing**: Develop registration-driving event descriptions Agency & Freelance Client Presentations**: Rapidly prototype copy concepts for pitches A/B Testing**: Generate multiple copy variations for campaign testing Campaign Brainstorming**: Kickstart creative sessions with AI-generated ideas Content Calendar Filling**: Populate social media schedules efficiently Startup & Small Business MVP Marketing**: Create professional copy without hiring agencies Investor Pitches**: Generate compelling product descriptions Website Content**: Populate landing pages with conversion-focused copy Email Campaigns**: Develop subject lines and promotional content Content Marketing Blog Post Promotions**: Generate social media copy for article shares Newsletter CTAs**: Create compelling subscription and engagement prompts Video Descriptions**: Develop YouTube and social video copy Podcast Promotions**: Generate episode descriptions and listener CTAs 🔧 Advanced Customization Options Multi-Tone Generation Modify the prompt to generate different copy styles: Professional & Corporate: "Generate formal, trust-building copy..." Casual & Friendly: "Create conversational, approachable messaging..." Urgent & Scarcity: "Develop time-sensitive, action-driving copy..." Luxury & Premium: "Craft sophisticated, high-end positioning..." Batch Processing Enhancement Add nodes for processing multiple products: Split in Batches**: Handle bulk product lists Merge**: Combine results for team review Item Lists**: Process CSV uploads of product catalogs Quality Control Integration Implement approval workflows: Human Review Step**: Add manual approval before publishing Sentiment Analysis**: Score copy for emotional impact Brand Guidelines Check**: Validate against company voice standards A/B Test Setup**: Generate multiple variations automatically Extended Distribution Connect additional platforms: Email Marketing**: Send to Mailchimp, ConvertKit, or HubSpot Social Media**: Post directly to Facebook, Twitter, LinkedIn CMS Integration**: Push to WordPress, Webflow, or custom sites Project Management**: Create tasks in Asana, Trello, or Monday.com 📊 Output Examples Sample Input: Product Name: EcoSmart Water Bottle Product Features: Self-cleaning UV technology, 24-hour temperature retention, BPA-free stainless steel, leak-proof design, 500ml capacity Generated Ad Copy: Stay hydrated and eco-conscious with the EcoSmart Water Bottle—featuring revolutionary self-cleaning UV technology that eliminates 99.9% of bacteria while keeping your drinks perfectly chilled for 24 hours! Experience the future of hydration with premium stainless steel construction that's as durable as it is sustainable. CTAs: • Order Your EcoSmart Bottle Today • Join the Clean Hydration Revolution • Get 24-Hour Freshness Now Slack Notification Format: 🎯 NEW AD COPY GENERATED Product: EcoSmart Water Bottle 📝 Ad Copy: Stay hydrated and eco-conscious with the EcoSmart Water Bottle—featuring revolutionary self-cleaning UV technology that eliminates 99.9% of bacteria while keeping your drinks perfectly chilled for 24 hours! Experience the future of hydration with premium stainless steel construction that's as durable as it is sustainable. 🔥 Call-to-Actions: • Order Your EcoSmart Bottle Today • Join the Clean Hydration Revolution • Get 24-Hour Freshness Now Ready to use in campaigns! 🚀 🛠️ Troubleshooting & Best Practices Common Issues & Solutions API Rate Limits Monitor OpenAI usage dashboard Implement delay nodes for high-volume processing Consider upgrading to higher tier plans Inconsistent Output Quality Refine prompts with specific examples Add output validation rules Include brand guidelines in system prompt Integration Failures Verify all API credentials are current Test connections individually before full workflow Check service status pages for outages Optimization Strategies Cost Management Use GPT-4o-mini for routine copy generation Reserve GPT-4 for premium campaigns Cache common responses to reduce API calls Quality Enhancement A/B test different prompt variations Collect team feedback on generated copy Maintain library of high-performing examples Workflow Efficiency Set up monitoring alerts for failures Create backup workflows for critical campaigns Document customizations for team reference 📈 Performance Tracking Key Metrics to Monitor Generation Speed**: Average time from input to output Approval Rate**: Percentage of AI copy used without edits Campaign Performance**: Click-through rates of AI-generated content Cost Per Copy**: API costs per generated piece Success Indicators Reduced copywriting turnaround time (target: under 30 seconds) Increased campaign launch frequency Higher team satisfaction with copy quality Measurable improvement in conversion rates 📞 Questions & Support Need help setting up or customizing your AI Copywriter Pro workflow? 📧 Direct Support Email**: Yaron@nofluff.online Response Time**: Within 24 hours on business days Specialties**: Custom prompt engineering, integration troubleshooting, workflow optimization 🎥 Video Tutorials YouTube Channel**: https://www.youtube.com/@YaronBeen/videos Complete setup walkthrough Advanced customization techniques Integration with popular marketing tools Prompt engineering masterclass 🤝 Professional Network LinkedIn**: https://www.linkedin.com/in/yaronbeen/ Connect for ongoing automation support Share your copywriting success stories Get early access to new workflow templates 💬 What to Include in Support Requests Your specific industry or use case Current marketing tools and platforms Sample products you want to test with Any custom requirements or brand guidelines Screenshots of any errors or unexpected outputs Ready to revolutionize your copywriting process? Deploy this workflow and watch your marketing team's productivity soar while maintaining professional, conversion-focused messaging!

What is this workflow doing? This simple workflow is pulling the latest Euro foreign exchange reference rates from the European Central Bank and responding expected values to an incoming HTTP request (GET) via a Webhook trigger node. Setup no authentication** needed the workflow is ready to use test** the workflow template by hitting the test workflow button and calling the URL in the webhook node optional: choose your own Webhook listening path in the Webhook trigger node Usage There are two possible usage scenarios: get all Euro exchange rates as an array of objects get only a specific currency exchange rate as a single object All available rates Using the HTTP query ?foreign=USD (where USD is one of the available currency symbols) will provide only that specificly asked rate. Response example: {"currency":"USD","rate":"1.0852"} Single exchange rate If no query is provided, all available rates are returned. Response example: [{"currency":"USD","rate":"1.0852"},{"currency":"JPY","rate":"163.38"},{"currency":"BGN","rate":"1.9558"},{"currency":"CZK","rate":"25.367"},{"currency":"DKK","rate":"7.4542"},{"currency":"GBP","rate":"0.85495"},{"currency":"HUF","rate":"389.53"},{"currency":"PLN","rate":"4.3053"},{"currency":"RON","rate":"4.9722"},{"currency":"SEK","rate":"11.1675"},{"currency":"CHF","rate":"0.9546"},{"currency":"ISK","rate":"149.30"},{"currency":"NOK","rate":"11.4285"},{"currency":"TRY","rate":"33.7742"},{"currency":"AUD","rate":"1.6560"},{"currency":"BRL","rate":"5.4111"},{"currency":"CAD","rate":"1.4674"},{"currency":"CNY","rate":"7.8100"},{"currency":"HKD","rate":"8.4898"},{"currency":"IDR","rate":"16962.54"},{"currency":"ILS","rate":"3.9603"},{"currency":"INR","rate":"89.9375"},{"currency":"KRW","rate":"1444.46"},{"currency":"MXN","rate":"18.5473"},{"currency":"MYR","rate":"5.1840"},{"currency":"NZD","rate":"1.7560"},{"currency":"PHP","rate":"60.874"},{"currency":"SGD","rate":"1.4582"},{"currency":"THB","rate":"38.915"},{"currency":"ZAR","rate":"20.9499"}] Further info Read more about Euro foreign exchange reference rates here.

Who is this for? This workflow is designed for SEO specialists, content creators, marketers, and website developers who want to ensure their web content is easily accessible, understandable, and indexable by Large Language Models (LLMs) like ChatGPT, Perplexity, and Google AI Overviews. If you're looking to optimize your site for the evolving AI-driven search landscape, this template is for you. What problem is this workflow solving? / Use case Modern AI tools often crawl websites without executing JavaScript. This can lead to them "seeing" a very different version of your page than a human user or traditional search engine bot might. This workflow helps you: Identify how much of your content is visible without JavaScript. Check for crucial on-page SEO elements that AI relies on (headings, meta descriptions, structured data). Detect if your site presents JavaScript-blocking warnings. Get an AI-generated readability score and actionable recommendations to improve AI-friendliness. What this workflow does Receives a URL via a chat interface. Sanitizes the input URL to ensure it's correctly formatted. Fetches the website's HTML content, simulating a non-JavaScript crawler (like Googlebot). Extracts key HTML features: visible text length, presence of H1/H2/H3 tags, meta description, Open Graph data, structured data (JSON-LD), and <noscript> tags. It also checks for common JavaScript-blocking messages. Performs an AI SEO Analysis using an LLM (via OpenAI) based on the extracted features. Provides a report including an AI Readability Score (0-10), a summary, actionable recommendations, and a reminder to check the robots.txt file for AI bot access. Setup Estimated setup time:** 2-5 minutes. Import this workflow into your n8n instance. Ensure you have an OpenAI account and API key. Configure the "OpenAI Chat Model" node with your OpenAI API credentials. If you don't have credentials set up yet, create new ones in n8n. Activate the workflow. Interact with the chat interface provided by the "When chat message received" trigger node (you can access this via its webhook URL). How to customize this workflow to your needs Change LLM Model:** In the "OpenAI Chat Model" node, you can select a different model that suits your needs or budget. Adjust AI Prompt:** Modify the prompt in the "AI SEO Analysis" node (Chain Llm) to change the focus of the analysis or the format of the report. For example, you could ask for more technical details or a different scoring system. User-Agent:** The "Get HTML from Website" node uses a Googlebot User-Agent. You can change this to simulate other bots if needed. JS Block Indicators:** The "Extract HTML Features" node contains a list of common JavaScript-blocking phrases. You can expand this list with other languages or specific messages relevant to your checks.

📸 Instagram Full Profile Scraper with Apify and Google Sheets This n8n workflow automates the process of scraping full Instagram profiles using a custom Apify actor, and logs the results into a Google Sheet. It is designed to run at scheduled intervals and process a list of usernames by calling the API, appending the results, and marking them as processed. 🚀 Features ⏱ Scheduled Execution – Runs automatically every few minutes. 📄 Google Sheets Integration – Reads a list of Instagram usernames and updates the same sheet. 🧠 Apify Actor – Fetches full public Instagram profile data. 🧮 Aggregation – Batches usernames for bulk scraping. ✍️ Data Logging – Appends scraped data to a second sheet. ✅ Tracking – Marks usernames as processed once scraped. 📁 Workflow Structure graph TD; ScheduleTrigger --> GetUsernames; GetUsernames --> LimitItems; LimitItems --> AggregateUsernames; AggregateUsernames --> CallApifyActor; CallApifyActor --> AppendToSheet; CallApifyActor --> MarkAsScraped; 🛠 Setup Google Sheet Create a Google Sheet with: Sheet 1 named Usernames (GID: 0) Columns: username, scraped Sheet 2 named fullprofiles (GID: 458127000) Sample sheet: 🔗 Instagram Profile Sheet n8n Configuration Import this workflow into your n8n instance. Set up your Google Sheets credentials (googleSheetsOAuth2Api). Replace apify_api_your token in the HTTP Request node with your Apify API token. 📦 Required Credentials Google Sheets OAuth2** – For reading and writing sheet data. Apify API Token** – To call the custom actor for profile scraping. 📊 Sheets Used | Sheet Name | Purpose | | -------------- | -------------------------------- | | Usernames | Source of usernames to scrape | | fullprofiles | Destination of full profile data | 📌 Apify Actor Info > Instagram Full Profile Scraper > This actor fetches extended profile information from public Instagram profiles. 🔗 View on Apify 🔁 Workflow Nodes Overview | Node | Purpose | | ------------------------ | ----------------------------------------------------------------- | | Schedule Trigger | Triggers the workflow periodically. | | Get Usernames | Reads usernames from the Usernames sheet. | | Limit | Limits processing to 20 usernames per run. | | Aggregate | Groups usernames into a batch for the API call. | | Call Apify Actor | Sends the usernames to the Apify actor and receives profile data. | | Append Full Profiles | Appends the scraped data to the fullprofiles sheet. | | Mark Username as Scraped | Marks the processed usernames as scraped = TRUE. | | Sticky Note | Provides a reference link to the Apify actor used. | 📌 Example Sheet Structure Usernames Sheet | username | scraped | | ------------ | ------- | | exampleuser1 | | | exampleuser2 | TRUE | fullprofiles Sheet | username | full\_name | biography | follower\_count | ... | | -------- | ---------- | --------- | --------------- | --- | 🔐 Security & Notes This workflow does not bypass any Instagram privacy restrictions. It works only with public Instagram profiles. You are responsible for ensuring that scraping complies with Instagram’s terms of service and any applicable laws. 📬 Support For any issues, feel free to reach out: 👤 @mohamedgb00714 📧 mohamedgb00714@gmail.com

This workflow compares two lists of objects (List A and List B) using a user-specified key (e.g. email, id, domain) and returns: Items common to both lists (based on the key) Items only in List A Items only in List B How it works: Accepts a JSON input containing: listA: the first list of items listB: the second list of items key: the field name to use for comparison Performs a field-based comparison using the specified key Returns a structured output: common: items with matching keys (only one version retained) onlyInA: items found only in List A onlyInB: items found only in List B Example Input: { "key": "email", "listA": [ { "email": "alice@example.com", "name": "Alice" }, { "email": "bob@example.com", "name": "Bob" } ], "listB": [ { "email": "bob@example.com", "name": "Bobby" }, { "email": "carol@example.com", "name": "Carol" } ] } Output: common: [ { "email": "bob@example.com", "name": "Bob" } ] onlyInA: [ { "email": "alice@example.com", "name": "Alice" } ] onlyInB: [ { "email": "carol@example.com", "name": "Carol" } ] Use Cases: Deduplicate data between two sources Find overlapping records Identify new or missing entries across systems This workflow is useful for internal data auditing, list reconciliation, transaction reconciliation, or pre-processing sync jobs.

Who's it for This workflow is perfect for SEO specialists, marketers, bloggers, and content creators who want to automate keyword research using Google Sheets, Google Suggest, and Google Custom Search. Ideal for those building content pipelines, researching trends, or powering AI content generation with fresh search data. What it does This workflow automates the process of discovering a new keyword daily. It: Rotates through a keyword list in Google Sheets Selects one keyword per day Fetches autocomplete suggestions from Google Suggest Queries the Google Custom Search API for top results Returns structured JSON containing titles, links, and snippets How it works Manual Trigger – Initiates workflow manually Google Sheets – Reads keywords from a sheet (column: Title or Keyword) Code Node – Selects a daily keyword based on the number of days since July 4, 2025 Set Node – Saves the selected keyword as seed_keyword HTTP Request – Fetches autocomplete suggestions from Google Suggest API Function Node – Parses suggestions into usable items HTTP Request – Calls Google Custom Search API for each suggestion Code Node – Formats the search results into JSON How to set up Connect your Google Sheets OAuth2 credentials in n8n Use credential variables for Google Custom Search (⚠️ do not hardcode your key and cx) Replace the sample sheet ID with your own Run the workflow manually or schedule it daily Requirements Google account Enabled Custom Search JSON API on Google Cloud Google Sheet with a column labeled Title or Keyword n8n instance (cloud or self-hosted) How to customize Change the start date to control the keyword rotation cycle Randomize keyword selection instead of rotating Enrich results using tools like Ahrefs or SEMrush Push final output to Telegram, Notion, Slack, or Airtable Add filtering logic based on CPC, volume, or duplicates Example Sheet 📄 Click Here to access the example Google Sheet Sheet must contain a column Title or Keyword in the first row: Title teknologi AI berita viral tren startup

Who is this for? Professionals and individuals who receive high volumes of emails, those who want to automatically organize their Gmail inbox using AI classification. What problem is this workflow solving? Manual email sorting is time-consuming and inconsistent. This workflow automatically categorizes incoming emails into 8 predefined labels (To respond, FYI, Comment, Notification, Meeting update, Awaiting reply, Actioned, Marketing) to help maintain inbox zero and prioritize responses. What this workflow does Monitors Gmail for new incoming emails Uses AI to analyze email content and classify into appropriate categories Automatically applies the corresponding Gmail label Runs on a schedule to process emails consistently Setup Prerequisites n8n instance (cloud or self-hosted) Gmail account with API access enabled Access to an LLM provider (OpenAI, Anthropic Claude, or similar) Step-by-Step Configure Gmail Credentials Create Gmail Labels Configure LLM Chain Set Email Polling Schedule Test the Workflow Create Gmail Labels Before running the workflow, create these 8 labels in your Gmail account: To respond FYI Comment Notification Meeting update Awaiting reply Actioned Marketing How to customize this workflow to your needs Modify Classification Categories To change the email categories, update two places: In the AI prompt (Basic LLM Chain node): Your new category - Description of what emails fit here Another category - Description [... continue with your categories] In Gmail labels: Create corresponding labels in your Gmail account with the exact same names and numbering. Adjust Classification Rules The AI prompt contains specific rules for each category. To modify: Edit the "Key classification rules" section in the LLM prompt Add examples of emails that should go into each category Specify edge cases and how they should be handled Change Email Sources Currently monitors all incoming emails. To filter specific emails: In the Gmail Trigger node, add filters such as: from:specific-sender@domain.com subject:contains-keyword -label:already-processed You can also change this use Outlook Modify Polling Frequency More frequent**: Add multiple poll times (e.g., 9 AM, 12 PM, 6 PM) Less frequent**: Change to once daily or weekly Real-time**: Switch to webhook-based triggering (requires Gmail API setup) I choose daily for cost.

This workflow template demonstrates how to create an AI-powered agent that provides users with current weather information and Wikipedia summaries. By integrating n8n with Ollama's local Large Language Models (LLMs), this template offers a seamless and privacy-conscious solution for real-time data retrieval and summarization. Who is this for? Developers and Enthusiasts: Individuals interested in building AI-driven workflows without relying on external APIs. Privacy-Conscious Users: Those who prefer processing data locally to maintain control over their information. Educators and Students: Learners seeking hands-on experience with AI integrations and workflow automation. What problem does this workflow solve? Accessing up-to-date weather information and concise Wikipedia summaries typically requires multiple API calls to external services, which can raise privacy concerns and incur costs. This workflow addresses these issues by utilizing Ollama's self-hosted LLMs within n8n, enabling users to retrieve and process information locally. What this workflow does: User Input Capture: Begins with a chat interface where users can input queries. AI Processing: The input is sent to an AI Agent node configured with Ollama's LLMs, which interprets the query and determines the required actions. Weather Retrieval: For weather-related queries, the workflow fetches current weather data from a specified source. Wikipedia Summarization: For queries seeking information, it retrieves relevant Wikipedia content and generates concise summaries. Setup: Install Required Tools: Ollama: Install and run Ollama to manage local LLMs. Configure n8n Workflow: Import the provided workflow template into your n8n instance. Set up the AI Agent node to connect with Ollama's API. Ensure nodes responsible for fetching weather data and Wikipedia content are correctly configured. Run the Workflow: Start the workflow and interact with the chat interface to test various queries. How to customize this workflow to your needs: Automate Triggers: Set up scheduled triggers to provide users with regular updates, such as daily weather forecasts or featured Wikipedia articles.

Encode JSON to Base64 String in n8n This example workflow demonstrates how to convert a JSON object into a base64-encoded string using n8n’s built-in file processing capabilities. This is a common requirement when working with APIs, webhooks, or SaaS integrations that expect payloads to be base64-encoded. > Tip: The three green-highlighted nodes (Stringify → Convert to File → Extract from File) can be wrapped in a Subworkflow to create a reusable Base64 encoder in your own projects. 🔧 Requirements Any running n8n instance (local or cloud) No credentials or external services required What This Workflow Does Generates example JSON data Converts the JSON to a string Saves the string as a binary file Extracts the file’s contents as a base64 string Outputs the base64 string on the final node Step-by-Step Setup Manual Trigger Start the workflow using the Manual Execution node. This is useful for testing and development. Create JSON Data The Create Json Data node uses raw mode to construct a sample object with all major JSON types: strings, numbers, booleans, nulls, arrays, nested objects, etc. Convert to String The Convert to String node uses the expression ={{ JSON.stringify($json) }} to flatten the object into a single string field named json_text. Convert to File The Convert to File node takes the json_text value and saves it to a UTF-8 encoded binary file in the property encoded_text. Extract from File This node takes the binary file and extracts its contents as a base64-encoded string. The result is saved in the base64_text field. Customization Tips Replace the sample JSON in the Create Json Data node with your own payload structure. To make this reusable, extract the three core nodes into a Subworkflow or wrap them in a custom Function. Use the base64_text output field to post to APIs, store in databases, or include in webhook responses.