Workflow Templates

🔐 Advanced SSL Health Monitor 👤 Who is this for? This workflow is designed for DevOps engineers, IT administrators, and security professionals who need comprehensive SSL certificate monitoring and health assessment across multiple domains — featuring dual verification and professional reporting without relying on expensive monitoring services. 🧩 What It Does Daily Trigger runs the workflow every morning for proactive monitoring. URL Collection fetches the list of website URLs to monitor from your data source. Dual SSL Analysis: Free SSL Assessment Script — Get from sysadmin-toolkit on Github SSL-Checker.io API — External verification for cross-validation Comprehensive Health Check: Certificate expiration monitoring (customizable threshold) SSL configuration security assessment Protocol support analysis (TLS 1.3, 1.2, deprecated protocols) Cipher suite strength evaluation Vulnerability scanning (POODLE, BEAST, etc.) Compliance checking (PCI DSS, NIST, FIPS) Smart Alert System sends Discord notifications when: Certificates expire within threshold (default: 30 days) SSL configuration issues detected (weak ciphers, deprecated protocols) Security vulnerabilities found Compliance standards not met Grade drops below acceptable level (configurable) 🎯 Key Features 🔄 Dual Verification**: Cross-checks results between internal scanner and external API 📊 SSL Labs-Style Grading**: A+ to F rating system with detailed analysis 🛡️ Security Assessment**: Vulnerability detection and compliance checking 📱 Discord Integration**: Rich embed notifications with color-coded alerts ⚙️ Setup Instructions Data Source: Configure your URL source from Notion Ensure it contains a URL column with domains to monitor Credentials: Set up Discord webhook for alert notifications Configure any required API credentials for data sources Customize Thresholds: Expiration Alert: Days before expiry (default: 30 days) Grade Threshold: Minimum acceptable SSL grade (default: B) Alert Severity: Choose which issues trigger notifications Advanced Configuration: Modify vulnerability checks based on your security requirements Adjust compliance standards for your industry needs Customize Discord message formatting and alert channels 🧠 Technical Notes Dual-Check Reliability**: Combines custom Bubobot scanner with ssl-checker.io for maximum accuracy No Vendor Lock-in**: Uses free public APIs and open-source tools Professional Reporting**: Generates SSL Labs-quality assessments Security-First Approach**: Comprehensive vulnerability and compliance checking Flexible Alerting**: Discord integration with rich formatting and conditional logic This workflow provide a comprehensive SSL security monitoring solution that rivals enterprise-grade tools while remaining completely open-source and free.

Complete MCP server exposing 2 IP Geolocation API operations to AI agents. ⚡ Quick Setup Need help? Want access to more workflows and even live Q&A sessions with a top verified n8n creator.. All 100% free? Join the community Import this workflow into your n8n instance Credentials Add IP Geolocation API credentials Activate the workflow to start your MCP server Copy the webhook URL from the MCP trigger node Connect AI agents using the MCP URL 🔧 How it Works This workflow converts the IP Geolocation API into an MCP-compatible interface for AI agents. • MCP Trigger: Serves as your server endpoint for AI agent requests • HTTP Request Nodes: Handle API calls to https://api.bigdatacloud.net • AI Expressions: Automatically populate parameters via $fromAI() placeholders • Native Integration: Returns responses directly to the AI agent 📋 Available Operations (2 total) 🔧 Data (2 endpoints) • GET /data/ip-geolocation-full: IP Geolocation with Confidence Area and Hazard Report API • GET /data/ip-geolocation-with-confidence: IP Geolocation with Confidence Area API 🤖 AI Integration Parameter Handling: AI agents automatically provide values for: • Path parameters and identifiers • Query parameters and filters • Request body data • Headers and authentication Response Format: Native IP Geolocation API responses with full data structure Error Handling: Built-in n8n HTTP request error management 💡 Usage Examples Connect this MCP server to any AI agent or workflow: • Claude Desktop: Add MCP server URL to configuration • Cursor: Add MCP server SSE URL to configuration • Custom AI Apps: Use MCP URL as tool endpoint • API Integration: Direct HTTP calls to MCP endpoints ✨ Benefits • Zero Setup: No parameter mapping or configuration needed • AI-Ready: Built-in $fromAI() expressions for all parameters • Production Ready: Native n8n HTTP request handling and logging • Extensible: Easily modify or add custom logic > 🆓 Free for community use! Ready to deploy in under 2 minutes.

How it works: Accesses a target website, searches for new PDFs, and downloads them automatically. Extracts content from each PDF and sends it to an AI for summarization. Delivers the AI-generated summary directly to a Discord channel. Marks processed URLs in Google Sheets to avoid duplicates. Set up steps: Configure the website URL in the HTTP Request node. Connect to Google Cloud API (enable Drive & Sheets) and link your spreadsheet. Set up an OpenRouter API key and choose your preferred AI model. Create a Discord webhook for notifications.

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

Apply to jobs automatically from Google Sheets with status tracking Who's it for Job seekers who want to streamline their application process, save time on repetitive tasks, and never miss following up on applications. Perfect for anyone managing multiple job applications across different platforms. What it does This workflow automatically applies to jobs from a Google Sheet, tracks application status, and keeps you updated with notifications. It handles the entire application lifecycle from submission to status monitoring. Key features: Reads job listings from Google Sheets with filtering by priority and status Automatically applies to jobs on LinkedIn, Indeed, and other platforms Updates application status in real-time Checks application status every 2 days and notifies you of changes Sends email notifications for successful applications and status updates Prevents duplicate applications and manages rate limiting How it works The workflow runs on two main schedules: Daily Application Process (9 AM, weekdays): Reads your job list from Google Sheets Filters for jobs marked as "Not Applied" with Medium/High priority Processes each job individually to prevent rate limiting Applies to jobs using platform-specific APIs (LinkedIn, Indeed, etc.) Updates the sheet with application status and reference ID Sends confirmation email for each application Status Monitoring (Every 2 days at 10 AM): Checks all jobs with "Applied" status Queries job platforms for application status updates Updates the sheet if status has changed Sends notification emails for status changes (interviews, rejections, etc.) Requirements Google account with Google Sheets access Gmail account for notifications Resume stored online (Google Drive, Dropbox, etc.) API access to job platforms (LinkedIn, Indeed) - optional for basic version n8n instance (self-hosted or cloud) How to set up Step 1: Create Your Job Tracking Sheet Create a Google Sheet with these exact column headers: | Job_ID | Company | Position | Status | Applied_Date | Last_Checked | Application_ID | Notes | Job_URL | Priority | |--------|---------|----------|--------|--------------|--------------|----------------|-------|---------|----------| | JOB001 | Google | Software Engineer | Not Applied | | | | | https://careers.google.com/jobs/123 | High | | JOB002 | Microsoft | Product Manager | Not Applied | | | | | https://careers.microsoft.com/jobs/456 | Medium | Column explanations: Job_ID**: Unique identifier (JOB001, JOB002, etc.) Company**: Company name Position**: Job title Status**: Not Applied, Applied, Under Review, Interview Scheduled, Rejected, Offer Applied_Date**: Auto-filled when application is submitted Last_Checked**: Auto-updated during status checks Application_ID**: Platform reference ID (auto-generated) Notes**: Additional information or application notes Job_URL**: Direct link to job posting Priority**: High, Medium, Low (Low priority jobs are skipped) Step 2: Configure Google Sheets Access In n8n, go to Credentials → Add Credential Select Google Sheets OAuth2 API Follow the OAuth setup process to authorize n8n Test the connection with your job tracking sheet Step 3: Set Up Gmail Notifications Add another credential for Gmail OAuth2 API Authorize n8n to send emails from your Gmail account Test by sending a sample email Step 4: Update Workflow Configuration In the "Set Configuration" node, update these values: spreadsheetId**: Your Google Sheet ID (found in the URL) resumeUrl**: Direct link to your resume (make sure it's publicly accessible) yourEmail**: Your email address for notifications coverLetterTemplate**: Customize your cover letter template Step 5: Customize Application Logic For basic version (no API access): The workflow includes placeholder HTTP requests that you can replace with actual job platform integrations. For advanced version (with API access): Replace LinkedIn/Indeed HTTP nodes with actual API calls Add your API credentials to n8n's credential store Update the platform detection logic for additional job boards Step 6: Test and Activate Add 1-2 test jobs to your sheet with "Not Applied" status Run the workflow manually to test Check that the sheet gets updated and you receive notifications Activate the workflow to run automatically How to customize the workflow Adding New Job Platforms Update Platform Detection: Modify the "Check Platform Type" node to recognize new job board URLs Add New Application Node: Create HTTP request nodes for new platforms Update Status Checking: Add status check logic for the new platform Customizing Application Strategy Rate Limiting**: Add "Wait" nodes between applications (recommended: 5-10 minutes) Application Timing**: Modify the cron schedule to apply during optimal hours Priority Filtering**: Adjust the filter conditions to match your criteria Multiple Resumes**: Use conditional logic to select different resumes based on job type Enhanced Notifications Slack Integration**: Replace Gmail nodes with Slack for team notifications Discord Webhooks**: Send updates to Discord channels SMS Notifications**: Use Twilio for urgent status updates Dashboard Updates**: Connect to Notion, Airtable, or other productivity tools Advanced Features AI-Powered Personalization**: Use OpenAI to generate custom cover letters Job Scoring**: Implement scoring logic based on job requirements vs. your skills Interview Scheduling**: Auto-schedule interviews when status changes Follow-up Automation**: Send follow-up emails after specific time periods Important Notes Platform Compliance Always respect rate limits to avoid being blocked Follow each platform's Terms of Service Use official APIs when available instead of web scraping Don't spam job boards with excessive applications Data Privacy Store credentials securely using n8n's credential store Don't hardcode API keys or personal information in nodes Regularly review and clean up old application data Ensure your resume link is secure but accessible Quality Control Start with a small number of jobs to test the workflow Review application success rates and adjust strategy Monitor for errors and set up proper error handling Keep your job list updated and remove expired postings This workflow transforms job searching from a manual, time-consuming process into an automated system that maximizes your application efficiency while maintaining quality and compliance.

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

This n8n template introduces the Dynamic Prompts Ai workflow pattern which are incredible for certain types of data extraction tasks where attributes are unknown or need to remain flexible. The general idea behind this pattern is that the prompts for requested attributes to be extracted live outside the template and so can be changed at any time - without needing to edit the template. This seriously cuts down on maintainance requirements and is reusable for any number of tables at little cost. Check out the video demo I did for n8n Studio here: https://www.youtube.com/watch?v=_fNAD1u8BZw Check out the example Airtable here: https://airtable.com/appAyH3GCBJ56cfXl/shrXzR1Tj99kuQbyL Looking for the Baserow Version? https://n8n.io/workflows/2780-ai-data-extraction-with-dynamic-prompts-and-baserow/ How it works Given we have an "input" field for context and a number of fields for the data we want to extract, this template will run in the background to react to any changes to either the "input" or fields and automatically update the rows accordingly. The key is that Airtable fields have a special property called the "field description". In this pattern, we use this property to allow the user to store a simple prompt describing the data that should exist in the column. Our n8n template reads these column descriptions aka "prompts" to use as instructions to perform tasks on the "input". In this template, the "input" is a PDF of a resume/CV and the columns are attributes a HR person would want to extract from it - such as full name, address, last position, years of experience etc. How to use First publish this template and ensure it's accessible via webhook URL. You then have to run the "create airtable webhooks" mini-flow to configure your Airtable to send change events to the n8n template. This mini-flow exists in the template but you'll have to update the IDs. Check the template for more instructions. Requirements Airtable for Tables/Database OpenAI for LLM and extraction. Feel free to choose another LLM if preferred. Customising this workflow If you're not using files, you can replace the "input" field with anything you like. For example, the "input" could be single line text.

Video Guide I prepared a comprehensive guide detailing how to create a Smart Agent that automates meeting task management by analyzing transcripts, generating tasks in Airtable, and scheduling follow-ups when necessary. Youtube Link Who is this for? This workflow is ideal for project managers, team leaders, and business owners looking to enhance productivity during meetings. It is particularly helpful for those who need to convert discussions into actionable items swiftly and effectively. What problem does this workflow solve? Managing action items from meetings can often lead to missed tasks and poor follow-up. This automation alleviates that issue by automatically generating tasks from meeting transcripts, keeping everyone informed about their responsibilities and streamlining communication. What this workflow does The workflow leverages n8n to create a Smart Agent that listens for completed meeting transcripts, processes them using AI, and generates tasks in Airtable. Key functionalities include: Capturing completed meeting events through webhooks. Extracting relevant meeting details such as transcripts and participants using API calls. Generating structured tasks from meeting discussions and sending notifications to clients. Webhook Integration: Listens for meeting completion events to trigger subsequent actions. API Requests for Data: Pulls necessary details like transcripts and participant information from Fireflies. Task and Notification Generation: Automatically creates tasks in Airtable and notifies clients of their responsibilities. Setup N8N Workflow Configure the Webhook: Set up a webhook to capture meeting completion events and integrate it with Fireflies. Retrieve Meeting Content: Use GraphQL API requests to extract meeting details and transcripts, ensuring appropriate authentication through Bearer tokens. AI Processing Setup: Define system messages for AI tasks and configure connections to the AI chat model (e.g., OpenAI's GPT) to process transcripts. Task Creation Logic: Create structured tasks based on AI output, ensuring necessary details are captured and records are created in Airtable. Client Notifications: Use an email node to notify clients about their tasks, ensuring communications are client-specific. Scheduling Follow-Up Calls: Set up Google Calendar events if follow-up meetings are required, populating details from the original meeting context.

Introduction **Manual LinkedIn data collection is time-consuming, error-prone, and results in inconsistent data quality across CRM/database records.** This workflow is great for organizations that struggle with: Incomplete contact records with only LinkedIn URLs but missing profile details Hours spent manually copying LinkedIn information into databases Inconsistent data formats due to copy-paste from LinkedIn (emojis, styled text, special characters) Outdated profile information that doesn't reflect current roles/companies No systematic way to enrich contacts at scale Primary Users Sales & Marketing Teams Event Organizers & Conference Managers for event materials Recruitment & HR Professionals CRM Administrators Specific Problems Addressed Data Completeness: Automatically fills missing profile fields (headline, bio, skills, experience) Data Quality: Sanitizes problematic characters that break databases/exports Time Efficiency: Reduces hours of manual data entry to automated monthly updates Error Handling: Gracefully manages invalid/deleted LinkedIn profiles Scalability: Processes multiple profiles in batch without manual intervention Standardization: Ensures consistent data format across all records Cost Each URL scraped by Apify costs $0.01 to get all the data above. Apify charges per scrape, regardless of how much dta or fields you extract/use. Setup Instructions Prerequisites n8n Instance: Access to a running n8n instance (self-hosted or cloud) NocoDB Account: Database with a table containing LinkedIn URLs Apify Account: Free or paid account for LinkedIn scraping Required fields in NocoDB table Input: single LinkedIn URL NocoDB Field name LinkedIn Output: first/last/full name e-mail bio headline profile pic URL current role country skills current employer employer URL experiences (all previous jobs) personal website publications (articles) NocoDB Field names linkedin_full_name linkedin_first_name: linkedin_headline: linkedin_email: linkedin_bio: linkedin_profile_pic linkedin_current_role linkedin_current_company linkedin_country linkedin_skills linkedin_company_website linkedin_experiences linkedin_personal_website linkedin_publications linkedin_scrape_error_reason linkedin_scrape_last_attempt linkedin_scrape_status linkedin_last_modified Technically you also need an Id field, but that is always there so no need to add it :) n8n Setup 1. Import the Workflow Copy the workflow JSON from the template In n8n, click "Add workflow" → "Import from JSON" Paste the workflow and click "Import" 2. Configure NocoDB Connection Click on any NocoDB node in the workflow Add new credentials → "NocoDB Token account" Enter your NocoDB API token (found in NocoDB → User Settings → API Tokens) Update the projectId and table parameters in all NocoDB nodes 3. Set Up Apify Integration Create an Apify account at apify.com Generate an API token (Settings → Integrations → API) In the workflow, update the Apify token in the "Get Scraper Results" node Configure HTTP Query Auth credentials with your token 4. Map Your Database Fields Review the "Transform & Sanitize Data" node Update field mappings to match your NocoDB table structure Ensure these fields exist in your table: LinkedIn (URL field) linkedin_headline, linkedin_full_name, linkedin_bio, etc. linkedin_scrape_status, linkedin_last_modified 5. Configure the Filter In "Get Guests with LinkedIn" node Adjust the filter to match your requirements Default: (LinkedIn,isnot,null)~and(linkedin_headline,is,null) 6. Test the Workflow Click "Execute Workflow" with Manual Trigger Monitor execution for any errors Verify data is properly updated in NocoDB 7. Activate Automated Schedule Configure the Schedule Trigger node (default: monthly) Toggle the workflow to "Active" Monitor executions in n8n dashboard Customization Options 1. Data Source Modifications Different Database: Replace NocoDB nodes with Airtable, Google Sheets, or PostgreSQL Multiple Tables: Add parallel branches to process different contact tables Custom Filters: Modify the WHERE clause to target specific record subsets 2. Enrichment Fields Add Fields: Include additional LinkedIn data like education, certifications, or recommendations Remove Fields: Simplify by removing unnecessary fields (publications, skills) Custom Transformations: Add business logic for field calculations or formatting 3. Scheduling Options Frequency: Change from monthly to daily, weekly, or hourly Time-based: Set specific times for different timezones Event-triggered: Replace with webhook trigger for on-demand processing 4. Error Handling Enhancement Notifications: Add email/Slack nodes to alert on failures Retry Logic: Implement wait and retry for temporary failures Logging: Add database logging for audit trails 5. Data Quality Rules Validation: Add IF nodes to validate data before updates Duplicate Detection: Check for existing records before creating new ones Data Standardization: Add custom sanitization rules for industry-specific needs 6. Integration Extensions CRM Sync: Add nodes to push data to Salesforce, HubSpot, or Pipedrive AI Enhancement: Use OpenAI to summarize bios or extract key skills Image Processing: Download and store profile pictures locally 7. Performance Optimization Batch Size: Adjust the number of profiles processed per run Rate Limiting: Add delays between API calls to avoid limits Parallel Processing: Split large datasets across multiple workflow executions 8. Compliance Additions GDPR Compliance: Add consent checking before processing Data Retention: Implement automatic cleanup of old records Audit Logging: Track who accessed what data and when These customizations allow the workflow to adapt from simple contact enrichment to complex data pipeline scenarios across various industries and use cases.

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 low-code automation enables all eCommerce store visitors to upload a photo of themselves and virtually “try on” a garment in just a few clicks. With this workflow, WooCommerce, Prestashop, Shopify and more merchants can offer a cutting-edge “virtual try-on” feature with minimal development effort, enhancing customer engagement and reducing product returns. Key Advantages Zero-Coding, Visual Setup** Build end-to-end e-commerce features with drag-and-drop nodes instead of custom backend code. Asynchronous, Scalable Processing** Non-blocking “Wait” + “If” loop handles multi-second AI jobs gracefully, freeing up the workflow for other tasks. Dynamic Inputs & URLs** Query strings (e.g. ?Product=IMAGE_URL) allow you to embed the form on any product page and pass the garment image on the fly. Seamless User Experience** Instant pop-up within your storefront and automatic redirect to the generated mock-up keeps shoppers engaged without page reloads. Easy Credential Management** API keys, FTP credentials, and webhook IDs are all stored securely in n8n’s credential manager. How It Works Form Submission: A user submits a form with their name, an image of themselves ("Me"), and a hidden product image URL ("Product"). The form is triggered via the On form submission node, which collects the input data. Image Upload: The uploaded image ("Me") is sent to an FTP server for temporary storage using the FTP node. The filename includes a timestamp to ensure uniqueness. Virtual Try-on Request: The Create Image node sends a POST request to the Fal.run API, providing: The uploaded human image URL (from FTP). The product image URL (from the hidden form field). This generates a virtual try-on result. Result Processing: The workflow checks the status of the image generation (Get status node) in a loop (with a 10-second wait between checks) until it is marked as "COMPLETED." Once ready, the final image URL is fetched (Get Url image node) and displayed to the user via a redirect (Form node). User Experience: The user is redirected to the generated try-on image, completing the process. Set Up Steps API Key Setup: Create an account and obtain an API key. Configure the Create Image node with HTTP Header Authentication: Name: Authorization Value: Key YOURAPIKEY FTP/S3 Configuration: Set up an FTP server or S3 bucket to temporarily store uploaded user images. Configure the FTP node with your FTP credentials and storage path. Ecommerce Integration: On your WooCommerce site, add a "Try On" button that opens the form in a pop-up. Dynamically pass the product image URL as a query parameter: Example: https://URL_N8N/form/ca1c314d-46c6-4eeb-b6a5-359XXXXXX?Product=IMAGE_URL Testing: Verify the workflow by submitting a test form and ensuring the virtual try-on image is generated and displayed correctly. Need help customizing? Contact me for consulting and support or add me on Linkedin.

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