by Don Jayamaha Jr
Gain full visibility into decentralized exchanges using CoinMarketCap’s DEXScan API—powered by AI. This workflow is part of the CoinMarketCap AI Analyst system and delivers real-time and historical insights on spot trading pairs, DEX liquidity, trading activity, and OHLCV data across chains like Ethereum, Polygon, Solana, and more. Use this workflow as a sub-agent triggered by a parent supervisor workflow, or run it manually with inputs sessionId and message. 🔧 Supported Tools (8 Total) DEX Metadata → Static info (name, launch date, logo, URLs) DEX Networks List → All supported DEX chains + network metadata DEX Listings Quotes → Ranked list of DEXs with live trading volume, market share DEX Pair Quotes (Latest) → Real-time liquidity, price, and buy/sell stats DEX OHLCV Historical → Time-series data (daily/hourly/1m) DEX OHLCV Latest → Today’s price, volume, open/close for pairs DEX Trades Latest → Up to 100 recent trades for any DEX pair DEX Spot Pairs Latest → Active token pairs across DEXs + filters (volume, liquidity, volatility) Agent Architecture AI Model**: gpt-4o-mini Context Memory**: Window buffer using sessionId Trigger Input**: message, sessionId Execution**: Via Execute Workflow or parent AI supervisor Design**: Tool-based LangChain agent with CMC DEXScan endpoints 💡 Use Cases 🔹 Find top DEXs by 24h volume 🔹 Get spot pairs with highest liquidity on a specific network 🔹 Track historical OHLCV for Uniswap pairs 🔹 View latest trades for SOL/USDC pool 🔹 Analyze tax, pooled % and holders for specific pairs 🔹 Filter pairs by 24h volume, percent change, liquidity, or number of transactions ✅ Example Queries ✅ "Top 5 DEXs by 24h volume on Ethereum" ✅ "Get historical OHLCV for SOL-USDC on Solana" ✅ "Latest trades for a PancakeSwap pair" ✅ "Show all spot pairs with over $500K in liquidity on Polygon" ✅ "Retrieve metadata for Uniswap and SushiSwap" 🛠️ Setup Instructions Get a CoinMarketCap API Key Sign up at: https://coinmarketcap.com/api/ Add API Key to Credentials in n8n Use HTTP Header Auth method Trigger from Parent Workflow (Optional) Use Execute Workflow and pass message and sessionId Test Prompt Ideas Try: "Compare liquidity of Uniswap and Curve pairs on Ethereum" Sticky Notes Included DEXScan Agent Guide – Workflow architecture + supported tools Usage & API Call Examples – Prompts, test inputs, setup flow Error Codes + Licensing – 400/401/429/500 troubleshooting, IP rights ✅ Final Notes This agent is part of the CoinMarketCap AI Analyst System, which includes multiple specialized agents for cryptocurrencies, exchanges, and community data. Visit my Creator profile to find the full suite of tools. Master DEX analytics with AI—get powerful liquidity, trading, and pair insights in seconds.
by irfan saeed
Auto-Generate YouTube Chapters with AI-Powered Transcript Analysis Overview This workflow uses YouTube Data API v3 and Google Gemini 1.5 Flash AI to automatically generate timestamped chapters for videos by analyzing SRT captions. It enhances viewer navigation, improves SEO , and saves creators time by automating manual tasks. Prerequisites YouTube API Setup Create a Google Cloud Project Go to the Google Cloud Console. Click Select a project > New Project and name it (e.g., "YouTube Chapters Automation") . Enable YouTube Data API v3 Navigate to APIs & Services > Library. Search for "YouTube Data API v3" and click Enable . Configure OAuth Consent Screen Go to APIs & Services > OAuth consent screen. Select External (public) or Internal (testing), then add required details (app name, support email) . Generate OAuth 2.0 Credentials Under Credentials, click Create Credentials > OAuth client ID. Choose Web app, then download the JSON key file . Add Credentials to n8n Other Requirements Google Gemini API**: Configure access for the gemini-1.5-flash-8b-exp-0924 model by getting the api key. Workflow Steps Set Video ID Input the target video ID (e.g., r1wqsrW2vmE) using the Set Video ID node. Fetch Video Metadata Use the YouTube API node to retrieve the video’s title, category, and existing description . Download SRT Captions Get Caption ID: Call https://www.googleapis.com/youtube/v3/captions to fetch the caption track ID . Download Transcript: Use the ID to retrieve SRT data via https://www.googleapis.com/youtube/v3/captions/{{ID}}?tfmt=srt . Analyze Transcript with Gemini AI Process the SRT file with Google Gemini AI to identify chapters using a prompt like: "Classify this transcript into timestamped chapters (e.g., 00:00 - Introduction)." Validate output with a structured parser (e.g., Structured Captions node) . Update Video Description Append chapters to the description using the YouTube API’s videos.update method . Value Proposition Viewer Experience**: Chapters improve navigation and reduce drop-off rates . SEO Benefits**: Structured descriptions enhance search visibility . Time Savings**: Eliminates manual chapter creation .
by Sagar
This template streamlines your Instagram content posting workflow by connecting Google Drive for image storage, using OpenAI for AI-generated captions, and leveraging Facebook Graph API for automated publishing. Pre-requisites Before setting up this workflow, ensure you have: A Google account with access to Google Drive An OpenAI API key for AI caption generation A Facebook Developer account with Instagram Graph API access An Instagram Business or Creator account connected to a Facebook Page n8n.io account with workflow access Setup Instructions Configure Data Source Create a Google Sheet with the following columns: Name: Filename of your image in Google Drive Caption: Optional custom caption (leave empty for AI-generated captions) URL: your Video Reel or Image in Google Drive Connect Google Drive Add your Google Drive credentials in the "Google Drive" node Specify the folder path where your Instagram image/Video are stored Configure the node to retrieve image files based on filenames from your Google Sheet Set Up OpenAI Integration Add your OpenAI API key to the credentials Configure the OpenAI node to generate engaging captions based on image content Adjust temperature and model parameters for desired creativity level Configure Facebook Graph API Connect your Facebook account with Instagram access Set up the Facebook Graph API node to post to your Instagram Business/Creator account Ensure proper image formatting (1:1, 4:5, or 16:9 aspect ratios supported by Instagram) Workflow Automation Setup Configure the scheduler node to run at your preferred frequency Set up error handling to notify you of any posting failures Add conditional nodes to use either custom or AI-generated captions Execution Instructions After completing all connections, test the workflow with a single image Monitor the execution in the n8n dashboard to ensure proper functioning View the "Executions" tab to track successful posts and troubleshoot any errors Adjust posting frequency and scheduling as needed This template saves hours of manual Instagram posting work while maintaining an authentic presence. Perfect for social media managers, content creators, and businesses looking to maintain consistent Instagram activity without the daily manual effort. The workflow handles image retrieval, caption generation or customization, proper Instagram API formatting, scheduled posting, and execution tracking - all in one automated solution.
by Łukasz
Who is it for? If you are getting a lot of emails into your Gmail inbox, then probably some of those can be solved easly by replying or by doing specific short tasks. But analyzing whole email thread content just to catch up with multiple threads can be very wasteful. So by using AI you can actually get simple propositions of what should be done before closing this specific email and actual proposed answer to that email. This is especially useful if you need to do some actions before replying to email. In that case you can simply assign task to specific person, await until it's done, copy-paste AI answer when it's done, and close. Another good use would be if on one inbox there are working multiple people. It can make the process much more streamlined. How It Works? Script runs on your selected trigger. If you are using section "Read and Star", then you may use "Email Trigger". Automation is looking for exiting open Todoist tasks, that have the same title as email If task does not exist, then we are asking AI to analyze thread and give output that is Todoist-API-ready: having summary of email content having proposed actions to be taken having proposed answer to this email If email was unstarred for some reason but task was not closed, then task is being closed automatically. Script FOR PURPOSE is not trying to unstar messagess which have closed tasks, because this could lead to some inconsistencies. How to set up? Select and setup your triggers, depending on your needs Setup connections using N8N instructions. You will need: Gmail Todoist AI (in this workflow OpenAI is used) (Optional) Remove "Read and Star" section if you don't want tasks automatically read and starred. (Optional) Adjust AI node - especially useful if you want to use different model or have response in different language NOTE Chat does not heave memory attached on purpose. The purpose is that it should analyze each inbox message separately, not in thread. When using memory, it can get lost easily. NOTE2 You might want to adjust limits on nodes "Get Unread From Inbox", "Get Starred From Inbox" and "Get Open Tasks", especially if having issues with model complying to output structure. And that's it. I hope that this automation will make your Gmail <-> Todoist process much more streamlined! What's More? There is actually more that you could do with this automation, but it really depends on your needs. For example, you could add Form trigger to handle incoming support requests. Another thing is that you could replace Todoist with Asana or any database (like NocoDB) if you are using it for your task management.
by Ranjan Dailata
Who this is for? This workflow is designed for professionals and teams who need real-time, structured insights from Google Search results without manual effort. What problem is this workflow solving? This n8n workflow solves the problem of automating Google Search result extraction, cleanup, summarization, and AI-enhanced formatting for downstream use like sending the results to a webhook or another system. What this workflow does Automates Google Search via Bright Data Uses Bright Data’s proxy-based SERP API to run a Google Search query programmatically. Makes the process repeatable and scriptable with different search terms and regions/zones. Cleans and Extracts Useful Content The Google Search Data Extractor uses LLM based cleaning to remove HTML/CSS/JS from the response and extract pure text data. Converts messy, unstructured web content into structured, machine-readable format. Summarizes Search Results Through the Gemini Flash + Summarization Chain, it generates a concise summary of the search results. Ideal for users who don’t have time to read full pages of search results. Formats Data Using AI Agent The AI Agent acts like a virtual assistant that: Understands search results Formats them in a readable, JSON-compatible form Prepares them for webhook delivery Delivers Results to Webhook Sends the final summary + structured search result to a webhook (could be your app, a Slack bot, Google Sheets, or CRM). Setup Sign up at Bright Data. Navigate to Proxies & Scraping and create a new Web Unlocker zone by selecting Web Unlocker API under Scraping Solutions. In n8n, configure the Header Auth account under Credentials (Generic Auth Type: Header Authentication). The Value field should be set with the Bearer XXXXXXXXXXXXXX. The XXXXXXXXXXXXXX should be replaced by the Web Unlocker Token. A Google Gemini API key (or access through Vertex AI or proxy). Update the Google Search query as you wish by navigating to the Set Google Search Query node. Update the Webhook HTTP Request node with the Webhook endpoint of your choice. How to customize This Workflow to your needs 1. Change the Search Input Default: It searches a fixed query or dataset. Customize: Accept input from a Google Sheet, Airtable, or a form. Auto-trigger searches based on keywords or schedules. 2. Customize Summarization Style (LLM Output) Default: General summary using Google Gemini or OpenAI. Customize: Add tone: formal, casual, technical, executive-summary, etc. Focus on specific sections: pricing, competitors, FAQs, etc. Translate the summaries into multiple languages. Add bullet points, pros/cons, or insight tags. 3.Choose Where the Results Go Options: Email, Slack, Notion, Airtable, Google Docs, or a dashboard. Auto-create content drafts for WordPress or newsletters. Feed into CRM notes or attach to Salesforce leads.
by Ranjan Dailata
Who this is for? This workflow automates the process of Wikipedia data extraction using the Bright Data Web Unlocker, parsing and cleaning the data, and then sending the results to a specified webhook URL for downstream processing, reporting, or integration. What problem is this workflow solving? Researchers who need structured information from Wikipedia pages regularly. Data Engineers building knowledge bases or enriching datasets with factual data. Digital Marketers or Content Writers automating fact-checking or content sourcing. Automation Enthusiasts who want to trigger external systems with rich context from Wikipedia. What this workflow does This workflow addresses the challenges of manually retrieving, structuring, and using data from Wikipedia at scale. Workflow Breakdown Trigger Type: Scheduled or Manual Purpose: Starts the workflow either on a fixed schedule (e.g., daily) or on-demand via a manual trigger or incoming webhook. Bright Data Wikipedia Scraping Tool Used: Bright Data Web Unlocker Action: Scrape the HTML content of one or multiple Wikipedia article URLs. Parse & Extract Structured Data The Basic LLM Chain node is responsible for producing a human readable content. Summarization Summarize the Wikipedia content by utilizing the Summarization Chain node. Send to Webhook Initiates a Webhook notification to the specified URL as part of the "Summary Webhook Notifier" node. Setup Sign up at Bright Data. Navigate to Proxies & Scraping and create a new Web Unlocker zone by selecting Web Unlocker API under Scraping Solutions. In n8n, configure the Header Auth account under Credentials (Generic Auth Type: Header Authentication). The Value field should be set with the Bearer XXXXXXXXXXXXXX. The XXXXXXXXXXXXXX should be replaced by the Web Unlocker Token. In n8n, configure the Google Gemini(PaLM) Api account with the Google Gemini API key (or access through Vertex AI or proxy). Update the Set Wikipedia URL with Bright Data Zone node with the Wikipedia URL and Bright Data Zone. Update the Summary Webhook Notifier node with the Webhook endpoint of your choice. How to customize this workflow to your needs Update Wikipedia URL Replace with your own Wikipedia URL of your interest. Make sure to set the Wikipedia URL as part of the "Set Wikipedia URL with Bright Data Zone" node. Modify Data Extraction Logic Extract entire article content or just specific sections by extending the "LLM Data Extractor" node prompt. Extend AI Summarization Extract key bullet points or entities. Create short-form summaries by extending the "Concise Summary Generator" node. Extend Summary Webhook Notifier Send to Slack, Discord, Telegram, MS Teams via the Webhook notification mechanism. Connect to your internal database/API via the Webhook notification mechanism.
by merfy
Use Case Manually extracting images from PDF files for analysis is often slow and inefficient. Many users resort to taking screenshots of each page, uploading them to an AI tool like OpenAI for image analysis, and then manually copying the insights into a document. This manual process is time-consuming and prone to errors. This workflow streamlines the entire process by automatically extracting images from a PDF, analyzing them using the GPT-4o model, and saving the results in seconds—eliminating the need for manual effort. What This Workflow Does Extracts all images from the uploaded PDF file automatically The workflow scans each page of the PDF and identifies embedded images without manual intervention. Uses the GPT-4o model to analyze each extracted image Each image is processed through GPT-4o to generate descriptive insights, summaries, or context-specific analysis depending on the use case. Saves the analysis results to a .txt file, including image URLs The final output is a plain text file containing both the image URLs (e.g., hosted on cloud storage) and the corresponding GPT-4o analysis, ready for further use or sharing. Setup 1.Set up your credentials when you first open the workflow. You’ll need accounts for OpenAI, Convert API, and Google Drive. 2.Convert API does not rate-limit your API, sometimes you may receive 503 service unavailable error. Nevertheless, it doesn’t mean that you cannot convert your file. It simply means that you should retry the conversion in a few seconds. 3.Upload a PDF with images to Google Drive. 4.Remove unnecessary parts and retrieve image-related information. 5.Integrate image and image analysis information together. 6.Analyze each image using the OPENAI GPT-4o model. 7.Retrieve all image analysis content and image URL 8.Integrate multiple image URLs and analysis content 9.Output content to a .txt file. Template was created in n8n v1.83.2 How to Customize Replace the manual trigger with a Google Drive trigger or other automation triggers Change the image analysis model (e.g., switch or fine-tune GPT-4o) Send the results to other platforms (e.g., Slack, Telegram, LINE, etc.) instead of saving to a .txt file
by GuanNan
Who is this for? This template is designed for anyone who wants to integrate MCP with their AI Agents. Whether you're a developer, a data analyst, or an automation enthusiast, if you're looking to leverage the power of MCP and Google Calendar in your n8n workflows, this template is for you. What problem is this workflow solving? This template caters to MCP beginners seeking a hands - on example and developers looking to integrate Google Calendar MCP service. When integrating MCP with Google Calendar, manually updating AI Agents after changes to Google Calendar tools on the MCP Server is time - consuming and error - prone. This template automates the process, enabling the AI Agent to instantly recognize changes made to Google Calendar on the MCP Server. In project management, for example, it ensures that task schedule updates in Google Calendar are automatically detected by the AI Agent. With detailed steps, it simplifies the integration process for all users. What this workflow does This workflow focuses on integrating MCP with Google Calendar within n8n. Specifically, it allows you to build an MCP Server and Client using Google Calendar nodes in n8n. Any changes made to the Google Calendar tools on the MCP Server are automatically recognized by the MCP Client in the workflow. This means that you can make changes to your Google Calendar (such as adding, deleting, or modifying events) on the MCP Server, and the MCP Client in the n8n workflow will immediately detect these changes without any manual intervention. Setup Requirements An active n8n account. Access to Google Calendar API. You need to enable the Google Calendar API, and create the necessary credentials (OAuth 2.0 client ID). Basic knowledge of n8n workflows and MCP concepts. Step - by - step guide Create a new workflow in n8n: Log in to your n8n account and create a new workflow. Add Google Calendar nodes: Search for and add the Google Calendar nodes to your workflow. Configure the nodes with your Google Calendar API credentials. Set up the MCP Server and Client: Use the appropriate nodes in n8n to set up the MCP Server and Client. Connect the Google Calendar nodes to the MCP nodes as required. Test the workflow: Make some changes to your Google Calendar on the MCP Server and check if the MCP Client in the n8n workflow can detect these changes. How to customize this workflow to your needs If you want to customize this workflow, you can: Modify the triggers**: You can change the conditions under which the MCP Client detects changes. For example, you can set it to detect only specific types of events in Google Calendar. Integrate with other services**: You can add more nodes to the workflow to integrate with other services, such as sending notifications to Slack or saving data to a database when a change is detected.
by Jimleuk
This n8n template imports purchase order submissions from Outlook and converts attached purchase order forms in XLSX format into structured output. Data entry jobs with user-submitted XLSX forms are time consuming, incredibly mundane but necessary tasks which in likelihood are inherited and critical to business operation. While we could dream of system overhauls and modernisation, the fact is that change is hard. There is another way however - using n8n and AI! N8N offers an end-to-end solution to parse XLSX form attachments using LLM-powered OCR and send the extracted output to your ERP or otherwise. How it works An Outlook trigger is used to watch for incoming purchase order forms submitted via a shared inbox. The email attachment for the submission is a form in xlsx format - like this one Purchase Order Example - which is imported into the workflow. The 'Extract from File' node is used with the 'code' node to convert the xlsx file to markdown. This is so our LLM can understand it. The Information Extractor node is used to read and extract the relevant purchase order details and line items from the form. A simple validation step is used to check for common errors such as missing PO number or the amounts not matching up. A notification is automated to reply to the buyer if so. Once validation passes, a confirmation is sent to the buyer and the purchase order structured output can be sent along to internal systems. How to use This template only works if you're expecting and receiving forms in XLSX format. These can be invoices, request forms as well as purchase order forms. Update the Outlook nodes with your email or other emails as required. What's next? I've omitted the last steps to send to an ERP or accounting system as this is dependent on your org. Requirements Outlook for Emails Check out how to setup credentials here: https://docs.n8n.io/integrations/builtin/credentials/microsoft OpenAI for LLM document understanding and extraction. Customising the workflow This template should work for other Excel files. Some will be more complicated than others so experiment with different parsers and extraction tools and strategies. Customise the Information Extractor Schema to pull out the specific data you need. For example, capture any notes or comments given by the buyer.
by RealSimple Solutions
🧠 Analyze and Diagnose n8n Workflow Errors Automatically via OpenAI and Email > ⚠️ This template is available on ☁️ Cloud & 🖥️ self-hosted n8n instances with the OpenAI node enabled. 👤 Who is this for? This workflow is designed for n8n developers, automation engineers, and DevOps teams who want to automatically capture and analyze workflow errors, and receive professional HTML-styled diagnostics directly in their inbox. 💥 What problem does this solve? Manually troubleshooting failed workflows in n8n can be time-consuming. This template streamlines error detection by: Capturing workflow failures using the Error Trigger node Diagnosing root causes with the help of OpenAI Sending a fully-formatted, human-readable HTML error report via email Including practical resolutions and next-step suggestions This helps you or your team resolve issues faster and avoid repeated manual debugging. ⚙️ What this workflow does ⚡ Triggers on any n8n workflow error 📦 Extracts relevant error metadata including node, execution ID, and timestamps 🧠 Sends error content to OpenAI for analysis and recommendations 💌 Generates an HTML email report with inline styles and clear formatting 📥 Emails the result to a system administrator or support email 🛠️ Setup Install the OpenAI node in your self-hosted n8n instance. Add your OpenAI API Key securely in credentials. Configure the SMTP Email node with your email credentials. Adjust the Error Trigger to monitor specific workflows or all workflows. Set your preferred admin or dev email address in the final node. 🔧 How to customize this workflow to your needs 🧩 Use a [Set node] to define your variables, such as: Default admin email Workflow filter (optional) ✍️ Customize the prompt sent to OpenAI if you want deeper or more specific analysis 🎨 Modify the email HTML styles to match your brand or internal format 💾 Add additional logging (e.g., to Airtable, Google Sheets, or Notion) for long-term error tracking 📌 Sticky Note Title: Automated Error Reporter with AI-Powered Diagnosis Description: Captures any n8n error, sends it to OpenAI, and emails a beautiful HTML report to the administrator with steps to resolve the issue. Requires OpenAI credentials and SMTP configured.
by SamirLiu
📝 What this workflow does Every morning at 8 a.m., this workflow fetches the latest AI-related articles from both GNews and NewsAPI. It merges up to 40 new articles daily, selects the 15 most relevant ones on AI technology and applications, and uses GPT-4.1 to generate concise summaries in accurate Traditional Chinese (while preserving essential English technical terms). Each summary also includes the article link for easy referral. The compiled digest is then posted to your designated Telegram account or group. 👥 Who is this for? AI enthusiasts, professionals, and anyone interested in artificial intelligence news Individuals and teams wanting a concise daily digest of AI developments in Traditional Chinese Telegram users who prefer automated information delivery 🎯 What problem does this workflow solve? With the rapid evolution of AI technology, it can be overwhelming to keep up with new developments. This workflow addresses information overload by automatically collecting, summarizing, and translating the most important AI news each morning — all delivered conveniently to your chosen Telegram channel or group. ⚙️ Setup 🔑 Add NewsAPI and GNews API Keys Register for accounts on NewsAPI.org and GNews to obtain your API keys. Input your NewsAPI key directly into the Fetch NewsAPI articles node. Input your GNews API key into the Fetch GNews articles node. 🤖 Set up your Telegram Bot Create a Telegram Bot via BotFather and copy the generated Bot Token. In n8n, create Telegram Bot credentials using this token. In the Send summary to Telegram node, enter the chat ID of your target user, group, or channel to receive the messages. 🧠 Configure OpenAI Credentials In n8n, create a new credential using your OpenAI API key. Assign this credential to the GPT-4.1 Model node (or equivalent OpenAI/AI nodes). After completing these steps, your workflow is fully configured to fetch, summarize, and deliver daily AI news to your selected Telegram chat automatically. 🛠️ How to customize this workflow 🔍 Change the topic:** Update the keywords in the NewsAPI and GNews nodes for other subjects (e.g., "blockchain", "quantum computing"). ⏰ Adjust delivery time:** Modify the scheduled trigger to your preferred hour. ✍️ Tweak summary style or language:** Refine the prompt in the AI summarizer node for different tones or translate into other languages as needed. 📦 Dependencies NewsAPI account GNews account Telegram Bot OpenAI API access (for GPT-4.1) or compatible AI model for Langchain agent
by Samir Saci
Tags: Accessibility, SEO, Blogging, Marketing, Automation, AI, Web Auditing Context Hey! I’m Samir, a Supply Chain Engineer and Data Scientist from Paris, and the founder of LogiGreen Consulting. In my personal blog, I share insights on how to use AI, automation, and data analytics to improve logistics, operations, and digital sustainability practices. > Have you heard about accessibility? In this workflow, I use n8n to improve the quality of alternative texts for images on my personal website. 📬 For business inquiries, you can connect with me on LinkedIn Who is this template for? This workflow is for: Bloggers* and *website owners* who want to *improve accessibility** SEO professionals** looking to boost page performance Web developers* and *product teams** automating web audits What does it do? This n8n workflow: 🔍 Downloads the HTML of a blog or web page 🖼️ Extracts all ` tags and their alt` attributes 📉 Detects missing or too-short alt texts 🤖 Sends those images to GPT-4o (with vision) to generate new alt descriptions 📄 Saves the results into a Google Sheet, updating the alt text when needed How it works Set a page URL using the Set node Download HTML content Extract image src and alt using a Code node Store results in a Google Sheet Filter images with altLength < 50 Send image URL to GPT-4o Update the Google Sheet with the newly generated newAlt text The AI alt texts are concise, descriptive, and accessibility-compliant. What do I need to get started? You’ll need: A Google Sheet to store the audit results An OpenAI account with GPT-4o access Follow the Guide! Follow the sticky notes in the workflow or check my tutorial to configure each node and start using AI to improve the accessibility of your website. 🎥 Watch My Tutorial Notes GPT-generated alt texts are limited to ~125–150 characters for best results Use this to comply with WCAG and improve Google indexing Easily adapt it to audit multiple domains or e-commerce catalogues This workflow was built using n8n version 1.85.4 Submitted: April 21, 2025