Workflow Templates

This n8n workflow demonstrates how to automate image captioning tasks using Gemini 1.5 Pro - a multimodal LLM which can accept and analyse images. This is a really simple example of how easy it is to build and leverage powerful AI models in your repetitive tasks. How it works For this demo, we'll import a public image from a popular stock photography website, Pexel.com, into our workflow using the HTTP request node. With multimodal LLMs, there is little do preprocess other than ensuring the image dimensions fit within the LLMs accepted limits. Though not essential, we'll resize the image using the Edit image node to achieve fast processing. The image is used as an input to the basic LLM node by defining a "user message" entry with the binary (data) type. The LLM node has the Gemini 1.5 Pro language model attached and we'll prompt it to generate a caption title and text appropriate for the image it sees. Once generated, the generated caption text is positioning over the original image to complete the task. We can calculate the positioning relative to the amount of characters produced using the code node. An example of the combined image and caption can be found here: https://res.cloudinary.com/daglih2g8/image/upload/f_auto,q_auto/v1/n8n-workflows/l5xbb4ze4wyxwwefqmnc Requirements Google Gemini API Key. Access to Google Drive. Customising the workflow Not using Google Gemini? n8n's basic LLM node supports the standard syntax for image content for models that support it - try using GPT4o, Claude or LLava (via Ollama). Google Drive is only used for demonstration purposes. Feel free to swap this out for other triggers such as webhooks to fit your use case.

Transform YouTube comments into actionable insights with automated AI analysis and professional email reports. This intelligent workflow monitors your Google Sheets for YouTube video IDs, fetches comments using YouTube API, performs comprehensive AI sentiment analysis, and delivers formatted email reports with viewer insights - helping content creators understand their audience and improve engagement. 🚀 What It Does Smart Video Monitoring: Watches Google Sheets for new YouTube video IDs marked as "Pending" and triggers automated analysis Complete Comment Collection: Fetches up to 100 top comments per video using YouTube API with relevance-based ordering AI-Powered Analysis: Uses GPT-4 to analyze comments for sentiment, themes, questions, feedback, and actionable insights Professional Email Reports: Generates detailed HTML reports with statistics, sentiment breakdown, and improvement recommendations Automated Status Tracking: Updates spreadsheet status to prevent duplicate processing and maintain organized workflow 🎯 Key Benefits ✅ Deep Audience Insights: Understand what viewers really think about your content ✅ Save Hours of Manual Work: Automated comment analysis vs reading hundreds of comments ✅ Improve Content Strategy: Get actionable feedback for better video performance ✅ Track Sentiment Trends: Monitor positive/negative feedback patterns ✅ Professional Reporting: Receive formatted analysis reports via email ✅ Scalable Analysis: Process multiple videos automatically 🏢 Perfect For Content Creators & YouTubers Individual creators tracking audience engagement Educational channels analyzing learning feedback Entertainment creators understanding viewer preferences Business channels monitoring brand sentiment Marketing & Business Applications Brand Monitoring**: Track sentiment on branded content and partnerships Audience Research**: Understand viewer demographics and preferences Content Optimization**: Identify what resonates with your audience Competitor Analysis**: Analyze comments on competitor videos (where allowed) ⚙️ What's Included Complete Analytics Workflow: Ready-to-deploy YouTube comment analysis system Google Sheets Integration: Simple spreadsheet-based video management YouTube API Integration: Automated comment fetching with proper authentication AI Analysis Engine: GPT-4 powered sentiment and insight generation Email Reporting System: Professional HTML-formatted reports Status Management: Automatic processing tracking and duplicate prevention 🔧 Setup Requirements n8n Platform**: Cloud or self-hosted instance YouTube API Credentials**: Google Cloud Console API access OpenAI API**: GPT-4 access for comment analysis Google Sheets**: Video ID management and status tracking Gmail Account**: For receiving analysis reports 📊 Required Google Sheets Structure | ID | Video Title | YouTube Video ID | Status | |----|-------------|------------------|---------| | 1 | My Tutorial | dQw4w9WgXcQ | Pending | | 2 | Product Demo| abc123def456 | Mail Sent | | 3 | Weekly Vlog | xyz789uvw012 | Draft | Status Options: Draft → Pending → Mail Sent 📧 Sample Analysis Report 📺 YouTube Comments Analysis Report Video: "How to Build Your First Website" 📊 Quick Statistics: • Total Comments Analyzed: 87 • Average Likes per Comment: 3.2 • Total Replies: 156 • Sentiment Summary: Positive: 65%, Negative: 10%, Neutral: 25% ❓ Common Questions: • "What hosting service do you recommend?" • "Can I do this without coding experience?" • "How much does domain registration cost?" 💡 Key Feedback Points: • Tutorial pace is perfect for beginners • More examples of finished websites requested • Viewers want follow-up video on advanced features 🎯 Actionable Insights: • Create hosting comparison video • Add timestamps for different skill levels • Consider beginner-friendly series expansion 🎨 Customization Options Analysis Depth: Adjust AI prompts for different analysis focuses (engagement, education, entertainment) Comment Limits: Modify maximum comments processed (default: 100, AI analysis: 50) Report Recipients: Send reports to multiple team members or clients Custom Metrics: Add specific analysis criteria for your content niche Multi-Channel: Process videos from multiple YouTube channels Scheduling: Set up regular analysis of your latest videos 🏷️ Tags & Categories #youtube-analytics #comment-analysis #content-creator-tools #ai-sentiment-analysis #video-insights #audience-research #youtube-api #content-optimization #social-media-analytics #creator-economy #video-marketing #engagement-analysis #content-strategy #ai-reporting #youtube-automation 💡 Use Case Examples Educational Channel: Analyze tutorial comments to identify confusing concepts and improve teaching methods Product Reviews: Monitor sentiment on review videos to understand customer satisfaction trends Entertainment Creator: Track audience reactions to different content formats and optimize future videos

Overview This workflow aims to provide data visualization capabilities to a native SQL Agent. Together, they can help foster data analysis and data visualization within a team. It uses the native SQL Agent that works well and adds visualization capabilities thanks to OpenAI’s Structured Output and Quickchart.io. How it works Information Extraction: The Information Extractor identifies and extracts the user's question. If the question includes a visualization aspect, the SQL Agent alone may not respond accurately. SQL Querying: It leverages a regular SQL Agent: it connects to a database, queries it, and translates the response into a human-readable format. Chart Decision: The Text Classifier determines whether the user would benefit from a chart to support the SQL Agent's response. Chart Generation: If a chart is needed, the sub-workflow dynamically generates a chart and appends it to the SQL Agent’s response. If not, the SQL Agent’s response is output as is. Calling OpenAI for Chart Definition: The sub-workflow calls OpenAI via the HTTP Request node to retrieve a chart definition. Building and Returning the Chart: In the "Set Response" node, the chart definition is appended to a Quickchart.io URL, generating the final chart image. The AI Agent returns the response along with the chart. How to use it Use an existing database or create a new one. For example, I've used this Kaggle dataset and uploaded it to a Supabase DB. Add the PostgreSQL or MySQL credentials. Alternatively, you can use SQLite binary files (check this template). Activate the workflow. Start chatting with the AI SQL Agent. If the Text Classifier determines a chart would be useful, it will generate one in addition to the SQL Agent's response. Notes The full Quickchart.io specifications have not been fully integrated, so there may be some glitches (e.g., radar graphs may not display properly due to size limitations).

This n8n template builds upon a simple appointment request form design which uses AI to qualify if the incoming enquiry is suitable and/or time-worthy of an appointment. This demonstrates a lighter approach to using AI in your templates but handles a technically difficult problem - contextual understanding! This example can be used in a variety of contexts where figuring out what is and isn't relevant can save a lot of time for your organisation. How it works We start with a form trigger which asks for the purpose of the appointment. Instantly, we can qualify this by using a text classifier node which uses AI's contextual understanding to ensure the appointment is worthwhile. If not, an alternative is suggested instead. Multi-page forms are then used to set the terms of the appointment and ask the user for a desired date and time. An acknowledgement is sent to the user while an approval by email process is triggered in the background. In a subworkflow, we use Gmail with the wait for approval operation to send an approval form to the admin user who can either confirm or decline the appointment request. When approved, a Google Calendar event is created. When declined, the user is notified via email that the appointment request was declined. How to use Modify the enquiry classifier to determine which contexts are relevant to you. Configure the wait for approval node to send to an email address which is accessible to all appropriate team members. Requirements OpenAI for LLM Gmail for Email Google Calendar for Appointments Customising this workflow Not using Google Mail or Calendar? Feel free to swap this with other services. The wait for approval step is optional. Remove if you wish to handle appointment request resolution in another way.

🧠 Sentiment Analyzer Google Sheets → OpenAI GPT-4o → QuickChart → Gmail 🚀 What this workflow does Fetches customer reviews from a Google Sheet. Classifies each review as Positive, Neutral or Negative with GPT-4o-mini. Writes the sentiment back to your sheet. Builds a doughnut chart summarising the totals. Emails the chart to your chosen recipient so the whole team stays in the loop. Perfect for support teams, product managers or anyone who wants a zero-code mood ring for their users’ feedback. 🗺️ Node-by-node tour | 🔩 Node | 💡 Purpose | | ------------------------------------------------------- | ---------------------------------------------------------- | | Manual Trigger | Lets you test the workflow on demand. | | Select Google Sheet | Points to the spreadsheet that holds your reviews. | | Loop Over Items | Feeds each row through the analysis routine. | | Sentiment Analysis (LangChain) | Calls GPT-4o-mini and returns only the sentiment category. | | Update Google Sheet | Writes the new Sentiment value into column C. | | Read Data from Google Sheet | Pulls the full sheet again to create a summary. | | Extract Number of Answers per Sentiment (Code node) | Tallies up how many reviews fall into each category. | | Generate QuickChart | Creates a doughnut (or pie) chart as a PNG. | | Send Gmail with Sentiment Chart | Fires the chart off to your inbox. | | (Sticky Notes) | Friendly setup tips scattered around the canvas. | 🛠️ Setup checklist | ✅ Step | Where | | ------------------------------------------------------------------------------------- | -------------------------------- | | Connect Google Sheets → paste your Spreadsheet ID & choose the correct sheet. | All Google Sheets nodes | | Add OpenAI credentials (sk-… key). | Sentiment Analysis node | | Configure Gmail OAuth2 + recipient address. | Gmail node | | Match your sheet columns → “Review title”, “Review text”, empty “Sentiment”. | Google Sheet itself | | (Optional) Switch to gpt-4o for maximum accuracy. | Sentiment Analysis “Model” param | 🏃‍♂️ How to run Drop a few sample reviews into the sheet. Click “Test workflow” on the Manual Trigger. Watch each row march through → sentiment appears in column C. After all rows finish, check your inbox for a fresh chart. ✔️ ✨ Ideas for next level Schedule** the trigger (Cron) to auto-process new reviews daily. Feed the counts to Slack or Discord instead of email. Add a second GPT call to generate a short summary for each review. Happy automating! 🎉

This workflow shows how to use a self-hosted Large Language Model (LLM) with n8n's LangChain integration to extract personal information from user input. This is particularly useful for enterprise environments where data privacy is crucial, as it allows sensitive information to be processed locally. 📖 For a detailed explanation and more insights on using open-source LLMs with n8n, take a look at our comprehensive guide on open-source LLMs. 🔑 Key Features Local LLM Connect Ollama to run Mistral NeMo LLM locally Provide a foundation for compliant data processing, keeping sensitive information on-premises Data extraction Convert unstructured text to a consistent JSON format Adjust the JSON schema to meet your specific data extraction needs. Error handling Implement auto-fixing for LLM outputs Include error output for further processing ⚙️ Setup and сonfiguration Prerequisites n8n AI Starter Kit installed Configuration steps Add the Basic LLM Chain node with system prompts. Set up the Ollama Chat Model with optimized parameters. Define the JSON schema in the Structured Output Parser node. 🔍 Further resources Run LLMs locally with n8n Video tutorial on using local AI with n8n Apply the power of self-hosted LLMs in your n8n workflows while maintaining control over your data processing pipeline!

Webhook | Paper Summarization Who is this for? This workflow is designed for researchers, students, and professionals who frequently read academic papers and need concise summaries. It is useful for anyone who wants to quickly extract key information from research papers hosted on arXiv. What problem is this workflow solving? Academic papers are often lengthy and complex, making it time-consuming to extract essential insights. This workflow automates the process of retrieving, processing, and summarizing research papers, allowing users to focus on key findings without manually reading the entire paper. What this workflow does This workflow extracts the content of an arXiv research paper, processes its abstract and main sections, and generates a structured summary. It provides a well-organized output containing the Abstract Overview, Introduction, Results, and Conclusion, ensuring that users receive critical information in a concise format. Setup Ensure you have n8n installed and configured. Import this workflow into your n8n instance. Configure an external trigger using the Webhook node to accept paper IDs. Test the workflow by providing an arXiv paper ID. (Optional) Modify the summarization model or output format according to your preferences. How to customize this workflow to your needs Adjust the HTTPRequest node to fetch papers from other sources beyond arXiv. Modify the Summarization Chain node to refine the summary output. Enhance the Reorganize Paper Summary step by integrating additional language models. Add an email or Slack notification step to receive summaries directly. Workflow Steps Webhook receives a request with an arXiv paper ID. Send an HTTP request using "Request to Paper Page" to fetch the HTML content of the paper. Extract the abstract and sections using "Extract Contents". Split out all sections using "Split out All Sections" to process individual paragraphs. Clean up text using "Remove useless links" to remove unnecessary elements. Summarize extracted content using "Summarization Chain". Aggregate summarized content using "Aggregate summarized content". Reorganize the paper summary into structured sections using "Reorganize Paper Summary". Extract key information using "Content Extractor" to classify data into Abstract Overview, Introduction, Results, and Conclusion. Respond to the webhook with the structured summary. Note: This workflow is designed for use with arXiv research papers but can be adapted to process papers from other sources.

Description This automation template is designed for content creators, digital marketers, and social media managers looking to simplify their video posting workflow. It automates the process of generating engaging video descriptions and uploading content to both Instagram and TikTok, making your social media management more efficient and error-free. Who Is This For? Content Creators & Influencers:** Streamline your video uploads and focus more on creating content. Digital Marketers:** Ensure consistent posting across multiple platforms with minimal manual intervention. Social Media Managers:** Automate repetitive tasks and maintain a steady online presence. What Problem Does This Workflow Solve? Manually creating descriptions and uploading videos to different platforms can be time-consuming and error-prone. This workflow addresses these challenges by: Automating Video Uploads:** Monitors a designated Google Drive folder for new videos. Generating Descriptions:** Uses OpenAI to transcribe video audio and generate engaging, customized social media descriptions. Ensuring Multi-Platform Consistency:** Simultaneously posts your video with the generated description to Instagram and TikTok. Error Notifications:** Optional Telegram integration sends alerts in case of issues, ensuring smooth operations. How It Works Video Upload: Place your video in the designated Google Drive folder. Description Generation: The automation triggers OpenAI to transcribe your video’s audio and generate a captivating description. Content Distribution: Automatically uploads the video and description to both Instagram and TikTok. Error Handling: Sends Telegram notifications if any issues arise during the process. Setup Generate an API token at upload-post.com and configure it in both the Upload to TikTok and Upload to Instagram nodes. Google Cloud Project: Create a project in Google Cloud Platform, enable the Google Drive API, and generate the necessary OAuth credentials to connect to your Google Drive account. Set up your Google Drive folder in the Google Drive Trigger node. Customize the OpenAI prompt in the Generate Social Description node to match your brand’s tone. (Optional) Configure Telegram credentials for error notifications. Requirements Accounts:** upload-post.com, Google Drive, and (optionally) Telegram. API Keys & Credentials:** Upload-post.com API token, OpenAI API key, and (optional) Telegram bot token. Google Cloud:** A project with the Google Drive API enabled and valid OAuth credentials. Use this template to enhance your productivity, maintain consistency across your social media channels, and engage your audience with high-quality video content.

This n8n workflow automates YouTube video metadata generation using AI. It extracts video transcripts, analyzes content, and produces optimized titles, descriptions, tags, hashtags, and call-to-action elements. Additionally, the workflow integrates affiliate and promotional links to enhance overall video performance. Key Features Automated Metadata Generation Utilizes an AI agent integrated with OpenAI GPT-4 to generate engaging metadata based on the provided video transcript. SEO and Engagement Optimization Creates keyword-rich, well-structured content that boosts search engine visibility and audience engagement. Affiliate and Promotional Integration Retrieves pre-set promotional and affiliate links using a Google Docs integration. Direct YouTube Update Automatically updates video details on YouTube via the YouTube API. Customization Allows you to modify the AI prompt to tailor metadata for your specific niche. Workflow Breakdown User Submission Users supply the YouTube video link, transcript, and optionally, focus keywords. Video ID Extraction The workflow converts the YouTube URL into a video ID to streamline automation. Link Retrieval Affiliate and course links are fetched from a designated Google Docs file. AI-Powered Metadata Generation The AI agent generates the video title, description, tags, hashtags, and call-to-action elements. Metadata Formatting and Update The generated metadata is structured and directly updated on YouTube. Confirmation A success message is displayed upon completion of the update process. Setup and Configuration Deploying the Workflow Deploy the workflow in n8n and ensure all integrations are properly set up. Configuring Integrations Google Docs:** Configure credentials to retrieve affiliate and promotional links. OpenAI (GPT-4):** Set up credentials for AI-powered metadata generation. YouTube API:** Enter your API credentials to enable automatic video updates. User Input Requirements Provide a valid YouTube video link and its corresponding transcript. Optionally, include focus keywords to further enhance metadata accuracy. Ideal For YouTube Content Creators:** Automate video descriptions and boost SEO. Digital Marketers:** Enhance content for improved search rankings and audience engagement. Affiliate Marketers:** Simplify the insertion of promotional and affiliate links. AI & Automation Enthusiasts:** Explore the integration of AI into automated workflows. Additional Resources For further guidance, refer to the tutorial video on this workflow. More courses and resources are available on the SyncBricks website. For support or inquiries, contact Amjid Ali at info@syncbricks.com. You can also support this work via PayPal donations and subscribe for additional AI and automation workflows. Watch the Tutorial:** YouTube Video on This Workflow More Courses & Resources:** SyncBricks LMS Full Course on ERPNext & AI Automation Connect:** Email: info@syncbricks.com Website: SyncBricks YouTube: SyncBricks Channel LinkedIn: Amjid Ali Support & Subscribe:** Donate via PayPal Subscribe for More AI & Automation Workflows

Are you a cord-cutter? Do you find yourself looking through the many titles of videos uploaded to Youtube, just to find the ones you want to watch? Even when you subscribe to the channels you like, do you find that you want to watch the news now and my tech/n8n videos later? Well, now you can have n8n grab the last 8 videos, posted in the last 24 hours, and put them in a playlist for the day; and, each day the old playlist is deleted. Are you tired of a channel filling your subscriptions with tons of videos a day; this workflow can be used for any channel, whether you are subscribed to the channel or not. It's a YouTube playlist automation. How it works: Create your list of prefered Youtube Channels in a Google Sheet and it will create you a daily playlist; and, it will delete the playlist created yesterday. Instructions To set this up, you need to create a Google Sheet with the following headings in line 1: Channel User Name Channel Name Channel Link Channel ID Copy the 'Create your Channel List' into it's own workflow and link the Sheets links to your new sheet. To get the 'Create your Channel List' to work, you need to visit each channel's page that you want included in your playlist; you need to get the "@" name of the channel and add it to the 'Channel User Name' column of your Google Sheet. For example: if you wanted to include this channel: Recruit Training Videos - Corporal Stock, you would search for the name, to add to the next available row of the 'Channel User Name' column: @CorporalStock Once you add all Channel User Names, run the 'Create your Channel list workflow, and it will fill in the remaining details. Now the 'YT Playlist Creator' can be run. Note: The first time the workflow us run, disconnect the 'Delete Yesterday's Playlist' leg, or the workflow will error and stop (because there is no 'Yesterday's Playlist'. Note: this was made to create a playlist every day, delete yesterday's playlist, and only get the last 8 videos posted within the last 24 hours. I choose to put the date (YYMMDD format) in front of the playlist, to ensure that it doesn't conflict with another playlist. Also, I have it notifying me in Telegram, so I know that the new playlist is posted.

Explorium Event-Triggered Outreach This n8n and agent-based workflow automates outbound prospecting by monitoring Explorium event data (e.g. product launches, new office opening, new investment and more), researching companies, identifying key contacts, and generating tailored sales emails leveraging the Explorium MCP server. Template Workflow Overview Node 1: Webhook Trigger Purpose: Listens for real-time product launch events pushed from Explorium's webhook system. How it works: Explorium sends HTTP POST requests containing event data The webhook payload includes company name, business ID, domain, product name, and event type Pay attention: Product launch is just one example. You can easily enroll to many more meaningful events. to learn about events and how to enroll to events, visit the events documentation. Node 2: Company Research Agent Agent Type: Tools Agent Purpose: Enrich company data after an event occurs. How it works: Uses Explorium MCP via the MCP Client tool to gather additional company data Uses Anthropic Claude (Chat Model) to process and interpret company information for downstream personalization Node 3: Employee Data Retrieval Purpose: Retrieve prospect-level data for targeting. How it works: Uses HTTP Request node to call Explorium's fetch_prospects endpoint Filters prospects by: Company business_id Departments: Product, R&D, etc... Seniority levels: owner, cxo, vp, director, senior, manager, partner, etc... Pay Attention: Follow our fetch prospect documentation for the full list of filter and best practice. Limits results to top 5 relevant employees Code nodes handle: Filtering logic Cleaning API response Formatting data for downstream agents Node 4: Conditional Branch - Prospect Data Check If Node: Checks whether prospect data was successfully retrieved Logic: If prospects found → personalized emails per person If no prospects → fallback to company-level general email Node 5A: Email Writer #1 (No Prospect Data) Agent Type: Tools Agent Purpose: Write generic outbound email using only company-level research and event info. Powered by: Anthropic Chat Model Node 5B: Loop Over Prospects → Email Writer #2 (Personalized) Agent Type: Tools Agent Purpose: Write highly personalized email for each identified employee. How it works: Loops through each individual prospect Passes company research + employee data to LLM agent Generates customized emails referencing: Prospect's title & department Product launch Role-relevant Explorium value proposition Node 6: Slack Notifications Purpose: Posts completed emails to internal Slack channel for review or testing before final deployment. Future State: Can be swapped with an email sequencing platform in production. Setup Requirements Explorium API Access MCP Client credentials for company enrichment and prospect fetching Registered webhook for event listening Get explorium api key n8n Configuration Secure environment variables for API keys & webhook secret Code nodes configured for JSON transformation, filtering & signature validation Customization Options Personalization Logic Update LLM prompt instructions to reflect ICP priorities Modify email templates based on role, department, or tenure logic Adjust fallback behavior when prospect data is unavailable API Request Tuning Adjust page_size for number of prospects retrieved Fine-tune seniority and department filters to match evolving targeting Future Expansion Swap Slack notifications for outbound email automation Integrate call task assignment directly into CRM Introduce engagement scoring feedback loop (opens, clicks, replies) Troubleshooting Tips Validate webhook signature matching to prevent unauthorized requests Ensure correct business_id is passed to prospect fetching endpoint Confirm business enrichment returns sufficient data for company researcher agents Review agent LLM responses for correct output structure and parsing consistency

WebSecScan: AI-Powered Website Security Auditor This n8n workflow provides comprehensive website security analysis by leveraging OpenAI's models to detect vulnerabilities, configuration issues, and security misconfigurations. The workflow generates a professional HTML security report delivered directly via Gmail. Key Features Dual-Layer Security Analysis:** Performs parallel security audits using specialized OpenAI agents: Header Configuration Audit: Analyzes HTTP headers, CORS policies, CSP implementation, and cookie security Vulnerability Assessment: Identifies XSS vectors, information disclosure, and client-side weaknesses Detailed Security Grading:** Automatically calculates a security grade (A+ to F) based on findings severity and quantity Professional Report Generation:** Creates a comprehensive HTML report with: Security grade visualization Color-coded vulnerability categories Detailed recommendations with example configuration fixes Header presence/absence indicators Implementation guidance for remediation Non-Invasive Testing:** Performs analysis without active scanning or exploitation attempts Technical Implementation Multi-Agent Architecture:** Utilizes two specialized OpenAI agents with custom prompts tailored for security analysis Advanced Header Analysis:** Detects presence and proper implementation of critical security headers: Content-Security-Policy Strict-Transport-Security X-Content-Type-Options X-Frame-Options Referrer-Policy Permissions-Policy Intelligent Issue Detection:** Uses JavaScript processing to analyze OpenAI outputs and count critical/warning issues Responsive HTML Report:** Dynamically generates a mobile-friendly report with detailed findings and recommendations Setup Requirements 1. OpenAI API Configuration Create an OpenAI API key at platform.openai.com In n8n, go to Settings → Credentials → New → OpenAI API Enter your API key and save 2. Gmail Integration Navigate to Settings → Credentials → New → Gmail OAuth2 API Complete the OAuth authentication flow Configure recipient email in the "Send Security Report" node 3. Workflow Customization (Optional) Modify the form title/description in the Landing Page node Upgrade from gpt-4o-mini to gpt-4o for more comprehensive analysis Add additional recipients to the email report Usage Instructions Activate the workflow and access the form via the generated URL Enter any website URL to analyze (including the http:// or https:// prefix) Receive a detailed security report via email within minutes Share findings with your development team to implement fixes This workflow represents a non-invasive security assessment tool. For production environments, complement with professional penetration testing services.