Workflow Templates

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. JSON Architect - Dynamically Generate JSON Output Formats for Any AI Agent Overview Version: 1.0 The JSON Architect Workflow is designed to instruct AI agents on the required JSON structure for a given context and create the appropriate JSON output format. This workflow ensures that the generated JSON is validated and tested, providing a reliable JSON output format for use in various applications. ✨ Features Dynamic JSON Generation**: Automatically generate the JSON format based on the input requirements. Validation and Testing**: Validate the generated JSON format and test its functionality, ensuring reliability before output. Iterative Improvement**: If the generated JSON is invalid or fails testing, the workflow will attempt to regenerate it until successful or until a defined maximum number of rounds is reached. Structured Output**: The final output is the generated JSON output format, making it easy to integrate with other systems or workflows. 👤 Who is this for? This workflow is ideal for developers, data scientists, and businesses that require dynamic JSON structures for the responses of AI agents. It is particularly useful for those involved in procedural generation, data interchange formats, configuration management and machine learning model input/output. 💡 What problem does this solve? The workflow addresses the challenge of generating optimal JSON structures by automating the process of creation, validation, and testing. This approach ensures that the JSON format is appropriate for its intended use, reducing errors and enhancing the overall quality of data interchange. Use-Case examples: 🔄 Data Interchange Formats 🛠️ Procedural Generation 📊 Machine Learning Model Input/Output ⚙️ Configuration Management 🔍 What this workflow does The workflow orchestrates a process where AI agents generate, validate, and test JSON output formats based on the provided input. This approach leads to a more refined and functional JSON output parser. 🔄 Workflow Steps Input & Setup: The initial input is provided, and the workflow is configured with necessary parameters. Round Start: Initiates the round of JSON construction, ensuring the input is as expected. JSON Generation & Validation: Generates and validates the JSON output format according to the input. JSON Test: Verifies whether the generated JSON output format works as intended. Validation or Test Fails: If the JSON fails validation or testing, the process loops back to the Round Start for correction. Final Output: The final output is generated based on successful JSON construction, providing a cohesive response. 📌 Expected Input input**: The input that requires a proper JSON structure. max_rounds**: The maximum number of rounds before stopping the loop if it fails to produce and test a valid JSON structure. Suggested: 10. rounds**: The initial number of rounds. Default: 0. 📦 Expected Output input**: The original input used to create the JSON structure. json_format_name**: A snake_case identifier for the generated JSON format. Useful if you plan to reuse it for multiple AI agents or Workflows. json_format_usage**: A description of how to use the JSON output format in an input. Meant to be used by AI agents receiving the JSON output format in their output parser. json_format_valid_reason**: The reason provided by the AI agents explaining why this JSON format works for the input. json_format_structure: The JSON format itself, intended for application through the **Advanced JSON Output Parser custom node. json_format_input: The **input after the JSON output format ( json_format_structure ) has been applied in an AI agent's output parser. 📌 Example An example that includes both the input and the final output is provided in a note within the workflow. ⚙️ n8n Setup Used n8n Version**: 1.100.1 n8n-nodes-advanced-output-parser**: 1.0.1 Running n8n via**: Podman 4.3.1 Operating System**: Linux ⚡ Requirements to Use/Setup 🔐🔧 Credentials & Configuration Obtain the necessary LLM API key and permissions to utilize the workflow effectively. This workflow is dependent on a custom node for dynamically inputting JSON output formats called n8n-nodes-advanced-output-parser. You can find the repository here. Warning: As of 2025-07-09, the custom node creator has warned that this node is not production-ready. Beware when using it in production environments without being aware of its readiness. ⚠️ Notes, Assumptions & Warnings This workflow assumes that users have a basic understanding of n8n and JSON configuration. This workflow assumes that users have access to the necessary API keys and permissions to utilize the Mistral API or other LLM APIs. Ensure that the input provided to the AI agents is clear and concise to avoid confusion in the JSON generation process. Ambiguous inputs may lead to invalid or irrelevant JSON output formats. ℹ️ About Us This workflow was developed by the Hybroht team of AI enthusiasts and developers dedicated to enhancing the capabilities of AI through collaborative processes. Our goal is to create tools that harness the possibilities of AI technology and more.

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. Transform email overload into actionable insights with this automated daily digest workflow that intelligently summarizes categorized emails using AI. Who's it for This workflow is perfect for busy professionals, content creators, and newsletter subscribers who need to stay informed without spending hours reading through multiple emails. Whether you're tracking industry news, monitoring competitor updates, or managing content subscriptions, this automation helps you extract key insights efficiently. How it works The workflow runs automatically each morning at 9 AM, fetching emails from a specific Gmail label received in the last 24 hours. Each email is processed through OpenAI's language model using LangChain to create concise, readable summaries that preserve important links and formatting. All summaries are then combined into a single, well-formatted digest email and sent to your inbox, replacing dozens of individual emails with one comprehensive overview. How to set up Create a Gmail label for emails you want summarized (e.g., "Tech News", "Industry Updates") Configure credentials for both Gmail OAuth2 and OpenAI API in their respective nodes Update the Gmail label ID in the "Get mails (last 24h)" node with your specific label Set your email address in the "Send Digested mail" node Adjust the schedule in the Schedule Trigger if you prefer a different time than 9 AM Test the workflow with a few labeled emails to ensure proper formatting Requirements Gmail account with OAuth2 authentication configured OpenAI API account and valid API key At least one Gmail label set up for email categorization Basic understanding of n8n workflow execution How to customize the workflow Change summarization style: Modify the prompt in the "Summarization Mails" node to adjust tone, length, or format of summaries. You can make summaries more technical, casual, or focus on specific aspects like action items. Adjust time range: Change the receivedAfter parameter in the Gmail node to fetch emails from different time periods (last 2 days, last week, etc.). Multiple labels: Duplicate the Gmail retrieval section to process multiple labels and combine them into categories within your digest. Add filtering: Insert additional conditions to filter emails by sender, subject keywords, or other criteria before summarization. Custom formatting: Modify the "Combine Subject and Body" code node to change the HTML structure, add styling, or include additional metadata like email timestamps or priority indicators.

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. Automated Research Reports with AI and Tavily Search An intelligent research automation workflow designed for Japanese users that transforms user queries into comprehensive HTML reports via email. Using Google Gemini AI and Tavily search, this workflow generates optimized search queries, conducts multi-perspective research, and delivers structured analysis reports in Japanese. Who's it for Content creators, researchers, analysts, and businesses in Japan who need comprehensive research reports on various topics without manual information gathering. Particularly valuable for Japanese professionals conducting competitive analysis, market research, and technical comparisons who prefer reports in their native language. How it works The workflow follows a strategic four-step process: Query Optimization: Google Gemini AI analyzes user input and generates three optimized search queries for comprehensive coverage Multi-Query Research: Tavily's advanced search executes all queries with deep search parameters and AI-generated answers Report Synthesis: Another Gemini AI model consolidates findings, eliminates duplicates, and structures information into readable HTML format Email Delivery: Gmail automatically sends the final HTML report to specified recipients Requirements Google Gemini API credentials (for three separate AI nodes) Tavily API credentials for advanced search functionality Gmail authentication for email delivery Basic n8n workflow execution permissions How to set up Configure API credentials in all Google Gemini and Tavily nodes Update email settings in the "Send a message" node with your recipient address Customize your query in the "Edit Fields" node (default: "n8nとdifyの違い") Test the workflow to ensure all connections work properly How to customize the workflow Research depth: Increase max_results in Tavily search for more comprehensive data gathering. Query optimization: Modify system prompts in the Query Generator for domain-specific searches. Report format: Adjust the Report Agent's system message to change output structure, language, or focus areas. Multi-recipient delivery: Duplicate the Gmail node for multiple email destinations. The workflow processes Japanese and English queries effectively, with built-in support for Japanese language output, making it ideal for Japanese professionals who need multilingual research capabilities. Advanced search parameters ensure high-quality, relevant results for professional research applications.

How it works This template is a complete, hands-on tutorial for building a RAG (Retrieval-Augmented Generation) pipeline. In simple terms, you'll teach an AI to become an expert on a specific topic—in this case, the official n8n documentation—and then build a chatbot to ask it questions. Think of it like this: instead of a general-knowledge AI, you're building an expert librarian. The workflow is split into two main parts: Part 1: Indexing the Knowledge (Building the Library) This is a one-time process you run manually. The workflow automatically scrapes all the pages of the n8n documentation, breaks them down into small, digestible chunks, and uses an AI model to create a special numerical representation (an "embedding") for each chunk. These embeddings are then stored in your own private knowledge base (a Supabase vector store). This is like a librarian reading every book and creating a hyper-detailed index card for every paragraph. Part 2: The AI Agent (The Expert Librarian) This is the chat interface. When you ask a question, the AI agent doesn't guess the answer. Instead, it uses your question to find the most relevant "index cards" (chunks) from the knowledge base it just built. It then feeds these specific, relevant chunks to a powerful language model (like Gemini) with a strict instruction: "Answer the user's question using ONLY this information." This ensures the answers are accurate, factual, and grounded in your provided documents. Set up steps Setup time: ~15-20 minutes This is an advanced workflow that requires setting up a free external database. Follow these steps carefully. Set up Supabase (Your Knowledge Base): You need a free Supabase account. Follow the detailed instructions in the large Workflow Setup sticky notes in the top-right of the workflow to: Create a new Supabase project. Run the provided SQL query in the SQL Editor to prepare your database. Get your Project URL and Service Role Key. Configure n8n Credentials: In your n8n instance, create a new Supabase credential using the Project URL and Service Role Key from the previous step. Create a new Google AI credential with your Gemini API key. Configure the Workflow Nodes: Select your new Supabase credential in the three Supabase nodes: Your Supabase Vector Store, Official n8n Documentation and Keep Supabase Instance Alive. Select your new Google AI credential in the three Gemini nodes: Gemini Chunk Embedding, Gemini Query Embedding and Gemini 2.5 Flash. Build the Knowledge Base: Find the Start Indexing manual trigger node at the top-left. Click its "Execute workflow" button to start the indexing process. This will take several minutes as it scrapes and processes the entire n8n documentation. You only need to do this once. Chat with Your Expert Agent: Once the indexing is complete, Activate the entire workflow. Open the RAG Chatbot chat trigger node and copy its Public URL. Open the URL in a new tab and start asking questions about n8n! For example: "How does the IF node work?" or "What is a sub-workflow?".

Overview An intelligent email automation workflow that revolutionizes how you handle email responses. This sophisticated system monitors your Gmail inbox, uses AI to determine which emails require replies, generates professional responses, and sends them only after your approval via Telegram. Perfect for busy professionals who want to maintain personalized communication while leveraging AI efficiency. 🌟 Key Features Intelligent Email Analysis Smart Detection**: Automatically identifies emails that genuinely need responses Context Understanding**: Distinguishes between promotional content, newsletters, and actionable emails Priority Filtering**: Focuses on emails with questions, requests, or time-sensitive matters AI-Powered Response Generation Professional Tone**: Maintains appropriate business communication standards Contextual Replies**: Generates responses based on email content and context Structured Output**: Creates properly formatted subject lines and email bodies Customizable Prompts**: Easily adjust AI behavior to match your communication style Human-in-the-Loop Approval Telegram Integration**: Review and approve responses directly from your mobile device Visual Preview**: See both original email and AI-generated response before sending Dual Approval System**: Approve or reject with simple Telegram buttons Timeout Protection**: Automatically expires after 5 minutes to prevent accidental sends 🔧 How It Works Workflow Architecture Email Monitoring: Continuous Gmail inbox surveillance (every minute) Inbox Filtering: Processes only emails in your main inbox folder AI Analysis: Determines response necessity using advanced language models Response Generation: Creates professional, contextual replies when needed Telegram Notification: Sends preview to your Telegram for approval Conditional Sending: Executes email send only upon your explicit approval Decision Logic The AI evaluates emails based on: Question Detection**: Identifies direct questions requiring answers Action Requests**: Recognizes requests for information or tasks Urgency Assessment**: Prioritizes time-sensitive communications Context Analysis**: Considers sender, subject, and content relevance 🚀 Setup Requirements Prerequisites Gmail Account**: With OAuth2 authentication enabled OpenAI API Key**: For AI language model access Telegram Bot**: Personal bot token and chat ID N8N Instance**: Cloud or self-hosted environment Required Credentials Gmail OAuth2 credentials OpenAI API authentication Telegram bot token and chat configuration 📊 Use Cases Business Applications Customer Support**: Automated responses to common inquiries Sales Teams**: Quick replies to prospect questions Account Management**: Timely responses to client communications HR Operations**: Efficient handling of employee inquiries Personal Productivity Email Management**: Reduce inbox overwhelm Professional Communication**: Maintain consistent response quality Time Management**: Focus on high-priority tasks while AI handles routine replies Mobile Workflow**: Approve emails anywhere via Telegram ⚙️ Customization Options AI Behavior Tuning Response Style**: Adjust tone from formal to casual Content Filters**: Modify email analysis criteria Response Length**: Control reply brevity or detail level Language Patterns**: Customize communication style Workflow Modifications Polling Frequency**: Adjust email checking intervals Approval Timeout**: Modify decision time limits Multi-Account Support**: Extend to multiple Gmail accounts Category Routing**: Different handling for different email types 🔒 Security & Privacy Data Protection Local Processing**: All email analysis occurs within your N8N instance No Data Storage**: Email content is not permanently stored Secure Authentication**: OAuth2 and API key protection Encrypted Communication**: Secure Telegram API integration Access Control Personal Approval**: You control every outgoing message Audit Trail**: Complete workflow execution logging Fail-Safe Design**: Defaults to no action if approval isn't received 📈 Performance & Reliability Efficiency Metrics Processing Speed**: Sub-second email analysis Accuracy**: High-quality response generation Reliability**: Robust error handling and retry mechanisms Scalability**: Handles high email volumes efficiently Resource Usage Lightweight Operation**: Minimal server resource consumption API Optimization**: Efficient OpenAI token usage Rate Limiting**: Respects Gmail and Telegram API limits 💡 Best Practices Optimization Tips Monitor AI Responses**: Regularly review and refine AI prompts Approval Patterns**: Establish consistent approval workflows Response Templates**: Create reusable response patterns Performance Monitoring**: Track workflow efficiency metrics Common Configurations Business Hours**: Limit processing to working hours VIP Senders**: Priority handling for important contacts Subject Filters**: Custom rules for specific email types Escalation Rules**: Forward complex emails to human review 🏆 Benefits Productivity Gains Time Savings**: Reduce manual email composition time by 60-80% Consistency**: Maintain professional communication standards Responsiveness**: Faster reply times improve customer satisfaction Focus**: Concentrate on high-value tasks while AI handles routine communications Professional Advantages Always Available**: Respond to emails even when busy Quality Assurance**: AI ensures grammatically correct, professional responses Scalability**: Handle increasing email volumes without proportional time investment Competitive Edge**: Faster response times improve business relationships Tags: Email Automation, AI Assistant, Gmail Integration, Telegram Bot, Workflow Automation, OpenAI, Business Productivity, Customer Service, Response Management, Professional Communication

This guide walks you through setting up an automated workflow that compares live flight fares across multiple booking platforms (e.g., Skyscanner, Akasa Air, Air India, IndiGo) using API calls, sorts the results by price, and sends the best deals via email. Ready to automate your flight fare comparison process? Let’s get started! What’s the Goal? Automatically fetch and compare live flight fares from multiple platforms using scheduled triggers. Aggregate and sort fare data to identify the best deals. Send the comparison results via email for review or action. Enable 24/7 fare monitoring with seamless integration. By the end, you’ll have a self-running system that delivers the cheapest flight options effortlessly. Why Does It Matter? Manual flight fare comparison is time-consuming and often misses the best deals. Here’s why this workflow is a game-changer: Zero Human Error**: Automated data fetching and sorting ensure accuracy. Time-Saving Automation**: Instantly compare fares across platforms, boosting efficiency. 24/7 Availability**: Monitor fares anytime without manual effort. Cost Optimization**: Focus on securing the best deals rather than searching manually. Think of it as your tireless flight fare assistant that always finds the best prices. How It Works Here’s the step-by-step magic behind the automation: Step 1: Trigger the Workflow Set Schedule Node**: Triggers the workflow at a predefined schedule to check flight fares automatically. Captures the timing for regular fare updates. Step 2: Process Input Data Set Input Data Node**: Sets the input parameters (e.g., origin, destination, departure date, return date) for flight searches. Prepares the data to be sent to various APIs. Step 3: Fetch Flight Data Skyscanner API Node**: Retrieves live flight fare data from Skyscanner using its API endpoint. Akasa Air API Node**: Fetches live flight fare data from Akasa Air using its API endpoint. Air India API Node**: Collects flight fare data directly from Air India’s API. IndiGo API Node**: Gathers flight fare data from IndiGo’s API. Step 4: Merge API Results Merge API Data Node**: Combines the flight data from Skyscanner and Akasa Air into a single dataset. Merge Both API Data Node**: Merges the data from Air India and IndiGo with the previous dataset. Merge All API Results Node**: Consolidates all API data into one unified result for further processing. Step 5: Analyze and Sort Compare Data and Sorting Price Node**: Compares all flight fares and sorts them by price to highlight the best deals. Step 6: Send Results Send Response via Email Node**: Sends the sorted flight fare comparison results to the user via email for review or action. How to Use the Workflow? Importing this workflow in n8n is a straightforward process that allows you to use this pre-built solution to save time. Below is a step-by-step guide to importing the Flight Fare Comparison Workflow in n8n. Steps to Import a Workflow in n8n Obtain the Workflow JSON Source the Workflow: The workflow is shared as a JSON file or code snippet (provided earlier or exported from another n8n instance). Format: Ensure you have the workflow in JSON format, either as a file (e.g., workflow.json) or copied text. Access the n8n Workflow Editor Log in to n8n: Open your n8n instance (via n8n Cloud or self-hosted). Navigate to Workflows: Go to the Workflows tab in the n8n dashboard. Open a New Workflow: Click Add Workflow to create a blank workflow. Import the Workflow Option 1: Import via JSON Code (Clipboard): In the n8n editor, click the three dots (⋯) in the top-right corner to open the menu. Select Import from Clipboard. Paste the JSON code (provided earlier) into the text box. Click Import to load the workflow. Option 2: Import via JSON File: In the n8n editor, click the three dots (⋯) in the top-right corner. Select Import from File. Choose the .json file from your computer. Click Open to import the workflow. Setup Notes API Credentials**: Configure each API node (Skyscanner, Akasa Air, Air India, IndiGo) with the respective API keys and endpoints. Check the API provider’s documentation for details. Email Integration**: Authorize the Send Response via Email node with your email service (e.g., Gmail SMTP settings or an email API like SendGrid). Input Customization**: Adjust the Set Input Data node to include specific origin/destination pairs and date ranges as needed. Schedule Configuration**: Set the desired frequency in the Set Schedule node (e.g., daily at 9 AM IST). Example Input Send a POST request to the workflow (if integrated with a webhook) with: { "origin": "DEL", "destination": "BOM", "departureDate": "2025-08-01", "returnDate": "2025-08-07" } Optimization Tips Error Handling**: Add IF nodes to manage API failures or rate limits. Rate Limits**: Include a Wait node if APIs have strict limits. Data Logging**: Add a node (e.g., Google Sheets) to log all comparisons for future analysis. This workflow transforms flight fare comparison into an automated, efficient process, delivering the best deals directly to your inbox!

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. This n8n workflow automates invoice management by integrating Gmail, PDF analysis, and Azure OpenAI GPT-4.1, with an optional human verification step for accuracy and control. It's ideal for businesses or individuals who regularly receive invoice emails and want to streamline their accounts payable process with minimal manual effort. The system continuously monitors Gmail for new messages from specified senders. When it detects an email with a PDF attachment and relevant subject line (e.g., "Invoice"), it automatically extracts text from the PDF, analyzes it using Azure OpenAI, and determines if it is a valid invoice. If the AI is uncertain, the workflow sends a manual approval request to a human reviewer. Valid invoices are saved to local storage with a timestamped filename, and a confirmation email is sent upon successful processing. 🎯 Who This Is For Small to medium businesses Freelancers or consultants who receive invoices via email IT or automation teams looking to streamline document workflows Anyone using n8n with access to Gmail and Azure OpenAI ✅ Features Gmail Monitoring** – Automatically checks for new emails from trusted senders AI-Powered Invoice Detection** – Uses Azure GPT-4.1 to intelligently verify PDF contents PDF Text Extraction** – Extracts readable text for analysis Human-in-the-Loop Verification** – Requests approval when AI confidence is low Secure File Storag**e – Saves invoices locally with structured filenames Email Notifications** – Sends confirmations or manual review alerts ⚙️ Setup Instructions 1. Prerequisites An active n8n instance (self-hosted or cloud) A Gmail account with OAuth2 credentials An Azure OpenAI account with access to the GPT-4.1 model A local directory for saving invoices (e.g., C:/Test/Invoices/) 2. Gmail OAuth2 Setup In n8n, create Gmail OAuth2 credentials. Configure it with Gmail API access (read emails and attachments). Update the Gmail Trigger node to filter by sender email (e.g., sender@gmail.com). 3. Azure OpenAI Setup Create Azure OpenAI API credentials in n8n. Ensure your endpoint is correctly set and GPT-4.1 access is enabled. Link the credentials in the AI Analysis node. 4. Customize Workflow Settings Sender Email – Update in Gmail Trigger Notification Email – Update in Send Notification node Save Directory – Change in Save Invoice node 5. Testing the Workflow Send a test email from the configured sender with a PDF invoice. Wait for the workflow to trigger and check for: File saved in the directory Confirmation email received Manual review request (if needed) 🔄 Workflow Steps Gmail Trigger → Check for PDF Invoice → Extract PDF Text → Analyze with GPT-4.1 → ↳ If Invoice: Save & Notify ↳ If Uncertain: Request Human Review ↳ If Not Invoice: Send Invalid Alert

This n8n workflow automates the collection, enrichment, and analysis of e-commerce product listings using Bright Data and AI, then delivers an HTML email report with the most competitive offers. 🚀 What It Does Pulls product titles from a Google Sheet. For each product, searches a Bright Data marketplace dataset (Google Shopping) for available listings. Extracts relevant fields: price, title, seller name, and listing URL. Sends this data to Google Gemini for AI-powered Markdown report generation. Converts Markdown to HTML and styles the output for better email rendering. Sends an email report for each product with the top 20 most affordable offers. 🛠️ Step-by-Step Setup Load product list from Google Sheets. For each product title, run a Bright Data filter request (case-sensitive match). Poll the snapshot status until it is ready. Retrieve snapshot content and clean the results with a Code node. Pass the results to Gemini (PaLM/Gemini Flash) for analysis and report generation in Markdown. Convert Markdown into styled HTML using Markdown + Code nodes. Send formatted email to a predefined recipient. Return to the loop and repeat for the next product. 🧠 How It Works Loop Control: SplitInBatches handles product-by-product processing. Snapshot Handling: Snapshot status is polled every 30s until success/failure. AI Formatting: Gemini summarizes listings and formats content. Error Handling: Failed snapshots produce a warning message and resume the loop. 📨 Final Output Each email contains: The product name A clean HTML of up to 20 sellers with lowest prices Links to listings AI-generated pricing summary 🔐 Credentials Used Bright Data account Google Gemini (PaLM/Gemini Flash) Google Sheets (OAuth2) SMTP Email (emailSend node) ⚠️ Important Notes Item title search is case-sensitive. Typos or casing mismatches may result in no results. Requires n8n-nodes-brightdata community node to be installed.

This n8n template extends the idea of follow-up reminders by having an AI agent suggest and book the next call or message to re-engage prospects which have been ignored. What makes this template particularly interesting and actually usable is that it uses the Human-in-the-loop approach to wait for a user's approval before actually making the booking or otherwise not if the user declined. A twist on a traditional idea where we can reduce the number of actionable tasks a human has to make by delegating them to AI. How it works A scheduled trigger checks your google calendar for sales meetings which happened a few days ago. For each event, gmail search is used to figure out if a follow-up message has been sent or received from the other party since the meeting. If none, it might mean the user needs a reminder to follow-up. For leads applicable for follow-up, we first get an AI Agent to find available meeting slots in the calendar. These slots and reminder are sent to the user via send-and-approval mode of the gmail node. The user replies in natural language either picking a slot, suggesting an entirely new slot or declines the request. When accepted, another AI Agent books the meeting in the calendar with the proposed dates and lead. When declined, no action is taken. How to use Update all calendar nodes (+subnodes) to point to the right calendar. If this is a shared-purpose calendar, you may need to either filter or create a new calendar. Update the gmail nodes to point to the right accounts. Requirements Google OAuth for Email and Calendar OpenAI for LLM Customising the template Not using Google? Swap out for Microsoft Outlook/Calendar or something else. Try swapping out or adding in additional send-for-approval methods such as telegram or whatsapp.

The Project starter bot takes the hassle out of launching projects by automatically creating a well-structured folder system in Dropbox and sending timely notifications through Slack and Gmail. By combining n8n's intelligent automation and seamless integration with Dropbox, Slack, and Gmail, this workflow streamlines project setup, saving you time and keeping everyone in the loop effortlessly. 💡 Why Use Project Starter Bot? Save Time: Cut down on the tedious manual folder creation by automating nested project directories instantly. Avoid Mistakes: Eliminate human error when organizing project files and ensure every necessary sub-folder exists. Boost Team Collaboration: Notify your team immediately via Slack and Gmail once the project folders are ready, so no one's left out of the loop. Gain an Edge: Impress clients and colleagues with your rapid and professional project kickoff process – no coffee breaks needed! ⚡ Perfect For Project Managers:** Keep your projects organized from day one without lifting a finger Creative Teams:** Focus on creativity while the bot handles folder setup and notifications Freelancers & Agencies:** Accelerate project launches and maintain consistency across clients 🔧 How It Works ⏱ Trigger: When you send a chat message requesting a new project folder 📎 Process: The bot creates the main project folder and five standardized sub-folders in Dropbox 🤖 Smart Logic: It verifies success and asks if you want to send notifications before proceeding 💌 Output: Sends a Slack message in the #projects channel and an email via Gmail confirming the setup 🗂 Storage: All folders are neatly organized inside Dropbox ensuring your files are easy to find 🔐 Quick Setup Import JSON file to your n8n instance Add credentials: Dropbox OAuth2 Slack API token Gmail OAuth2 Customize: Adjust folder names or project path if needed Update: Change Slack channel URL or Gmail recipient details Test: Run with a sample project name to see folders and notifications in action 🧩 Requirements Active n8n instance Dropbox OAuth2 credentials Slack API token with chat permissions Gmail OAuth2 credentials 🛠️ Level Up Ideas Integrate with project management tools like Jira or Trello for automated task creation Add personalized email templates with dynamic project details Use AI-powered chatbots to handle more complex project setup conversations 🧠 Nodes Used When chat message received AI Agent Dropbox create folder Send a message in Slack Send a message in Gmail Simple Memory (for context) MCP triggers and clients 📋 Details Made by: khaisa Studio Tags: Project Management, Automation, Dropbox, Slack, Gmail Category: Workflow Automation Need custom work? Contact Me

This automated n8n workflow tracks booked flight fares post-purchase using Amadeus and Skyscanner APIs to detect drops for refund or credit opportunities. It streamlines fare monitoring, updates booking statuses, and notifies users via SMS or email. Fundamental Aspects Fare Check Trigger** - Initiates the workflow Get Tracked Bookings** - Retrieves existing booking data Prepare Fare Query** - Prepares query parameters Search Current Fares** - Queries Skyscanner for current fares Analyze Fare Drops** - Identifies significant fare reductions Update Fare Tracking** - Updates fare tracking records Update Booking Status** - Updates status based on fare changes Check if Notification Needed** - Determines if alerts are required Send Fare Drop Email** - Notifies users via email Notify Slack Team** - Alerts the team via Slack Check Refund Eligible** - Assesses refund eligibility Initiate Refund Process** - Starts refund procedure if eligible Check if SMS Needed** - Decides if SMS alert is necessary Send SMS Alert** - Sends SMS notification Setup Instructions Import the workflow into n8n Configure API credentials for Amadeus and Skyscanner Run the workflow Verify notifications and refund processes Features Fare Monitoring** - Tracks and compares fares using Amadeus and Skyscanner Alert System** - Sends email and SMS notifications for fare drops Refund Management** - Checks and initiates refund processes Trend Analysis** - Analyzes fare trends for strategic decisions DB Queries Get Tracked Bookings Columns:** - booking_id, passenger_name, email, phone, flight_number, departure_date, origin, destination, airline, booking_class, original_fare, booking_date, confirmation_code, tracking_enabled, last_checked, current_lowest_fare, trend. Update Fare Tracking Columns:** - booking_id, check_date, lowest_fare, fare_source, savings_amount, savings_percentage, fare_trend, priority_level, action_recommended, refund_eligible, available_fares_json, updated_at. Update Booking Status: Columns** - last_checked, current_lowest_fare, booking_id. DB Setup: Create tables 'bookings' and 'fare_tracking' with above columns, set 'booking_id' as primary key, and ensure proper indexing for performance. Run queries after configuring DB connection in n8n with appropriate credentials. Parameters to Configure amadeus_api_key**: Amadeus API key skyscanner_api_key**: Skyscanner API key email_recipients**: List of email addresses for alerts sms_recipients**: List of phone numbers for SMS alerts slack_channel**: Slack channel for team notifications refund_threshold**: Minimum fare drop for refund eligibility

Who Is This For This workflow is ideal for content creators, solo founders, marketers, and AI enthusiasts who want to automate the full process of blog content creation. It is especially useful for professionals in tech, AI, and automation who publish frequently and need SEO-ready content fast. What Problem Does This Workflow Solve Creating SEO-optimized blog content is time-consuming and requires consistency. Manually researching trending topics slows down the content pipeline. Formatting, publishing, and promoting across multiple platforms takes effort. This workflow automates the entire process from research to publication. What This Workflow Does Research: Uses Perplexity AI to gather up-to-date content ideas via form input. Content Generation: GPT-4 creates a short, SEO-optimized article (max 20 lines) with H1, H2 structure and meta-description. Publishing: Automatically posts the content to WordPress. Email Notification: Sends the article title and URL via Gmail. Slack Notification: Notifies a specified Slack channel when the article is live. Database Logging: Saves the article details to a Notion database. Setup Guide Prerequisites WordPress account with API access OpenAI API Key Perplexity API Key Slack Bot Token Notion integration (Database ID) Gmail API credentials (optional) Community Node Required: This workflow uses n8n-nodes-mcp, which only works on self-hosted instances of n8n. > To install: Go to Settings > Community Nodes > Install n8n-nodes-mcp Steps Import the workflow into your n8n instance Install the required community node (n8n-nodes-mcp) Set up API credentials for OpenAI, Perplexity, WordPress, Slack, Gmail, and Notion Customize the form trigger with your preferred prompt Run a test using a sample topic How to Customize This Workflow Modify the research prompt to match your niche or industry Adjust GPT-4 settings for tone, structure, or content length Customize Notion fields (e.g., add tags, categories, or labels) Add logic for generating or assigning featured images automatically