Automate blog creation in brand voice with AI
This n8n template demonstrates a simple approach to using AI to automate the generation of blog content which aligns to your organisation's brand voice and style by using examples of previously published articles. In a way, it's quick and dirty "training" which can get your automated content generation strategy up and running for very little effort and cost whilst you evaluate our AI content pipeline. How it works In this demonstration, the n8n.io blog is used as the source of existing published content and 5 of the latest articles are imported via the HTTP node. The HTML node is extract the article bodies which are then converted to markdown for our LLMs. We use LLM nodes to (1) understand the article structure and writing style and (2) identify the brand voice characteristics used in the posts. These are then used as guidelines in our final LLM node when generating new articles. Finally, a draft is saved to Wordpress for human editors to review or use as starting point for their own articles. How to use Update Step 1 to fetch data from your desired blog or change to fetch existing content in a different way. Update Step 5 to provide your new article instruction. For optimal output, theme topics relevant to your brand. Requirements A source of text-heavy content is required to accurately breakdown the brand voice and article style. Don't have your own? Maybe try your competitors? OpenAI for LLM - though I recommend exploring other models which may give subjectively better results. Wordpress for blog but feel free to use other preferred publishing platforms. Customising this workflow Ideally, you'd want to "train" your agent on material which is similar to your output ie. your social media post may not get the best results from your blog content due to differing formats. Typically, this brand voice extraction exercise should run once and then be cached somewhere for reuse later. This would save on generation time and overall cost of the workflow.
By JimleukNarrating over a video using multimodal AI
This n8n template takes a video and extracts frames from it which are used with a multimodal LLM to generate a script. The script is then passed to the same multimodal LLM to generate a voiceover clip. This template was inspired by Processing and narrating a video with GPT's visual capabilities and the TTS API How it works Video is downloaded using the HTTP node. Python code node is used to extract the frames using OpenCV. Loop node is used o batch the frames for the LLM to generate partial scripts. All partial scripts are combined to form the full script which is then sent to OpenAI to generate audio from it. The finished voiceover clip is uploaded to Google Drive. Sample the finished product here: https://drive.google.com/file/d/1-XCoii0leGB2MffBMPpCZoxboVyeyeIX/view?usp=sharing Requirements OpenAI for LLM Ideally, a mid-range (16GB RAM) machine for acceptable performance! Customising this workflow For larger videos, consider splitting into smaller clips for better performance Use a multimodal LLM which supports fully video such as Google's Gemini.
By JimleukMonday.com useful utilities
This template is a set of building blocks to access Monday.com in ways not supported by the official Monday node. Prerequisites Monday account and Monday credentials. Included are setups to: Find a column value by the column's name (instead of a numerical index which can change when board structure is changed) Find a column value by the column's ID (again, instead of using a numerical index) Pull a board relation column, and get all the related pulses Pull an items subitems and split them out Upload a file to an item's files field Setup Create a Monday.com credential Update the nodes in the template to use your credential Copy/Paste the nodes you need from this template into any other workflow To retreive a column by name: Route a Monday.com node that gets an item to the COLUMN BY NAME node Edit the COLUMN BY NAME node, and enter the name in the first line of code. To retreive a column by its ID: Follow Monday.com's instructions to locate the column's ID Route a Monday.com node that gets an item to the COLUMN BY ID node -Edit the COLUMN BY ID node, and enter the ID in the first line of code. To retreive all linked pulses from a Board Relation column: Route a Monday.com node that gets an item to the GET BOARD RELATION node Edit the GET BOARD RELATION node to specify the column name. All linked pulses will be retrieved by the subsequent PULL LINKEDPULSE node To pull all subitems from an item: Route a Monday.com node that gets an item to the PULL SUBITEMS node All subitems will be retrieved by the subsequent GET EACH SUBITEM node To upload a File: Repalce the Convert to File node with whatever node you are using to output your binary file data Enable the MONDAY UPLOAD node If the destination column is named anything other then the default of "file" - edit the MONDAY UPLOAD node and change column_id:"file" in the first Value field to match the name of your file column
By Joey D’AnnaCentralized n8n error management system with automated email alerts via Gmail
Advanced n8n Error Handling: Automated Email Alerts & Global Error Workflow Configuration In any automated environment, n8n workflows, while powerful, can sometimes encounter unexpected issues or fail during execution. Without a dedicated error handling strategy, these failures might go unnoticed, leading to incomplete processes, data inconsistencies, or critical operational disruptions. Manually monitoring every workflow execution or sifting through logs for error details is inefficient and can significantly delay crucial fixes. This is where a centralized, automated error management system becomes essential to maintain reliability and quickly address any problems. The "Advanced n8n Error Handling: Automated Email Alerts & Global Error Workflow Configuration" template provides a robust solution to proactively manage and respond to errors within your n8n instance. For more powerful n8n templates, visit our website or contact us at AI Automation Pro. We help your business build custom AI workflow automation and apps. Highlight features Automated Email Notifications: Sends detailed HTML emails via Gmail for both execution and trigger failures, ensuring you're promptly informed. Centralized Error Management: Acts as a single, dedicated workflow to catch and process errors from multiple other n8n workflows. Proactive Global Error Handler Configuration: A scheduled task automatically scans and updates other active n8n workflows to use this workflow as their default error handler, ensuring consistent error management. Comprehensive Error Reporting: Notification emails are rich with information, including error messages, stack traces, the last executed node, direct links to failed executions, and detailed trigger failure context. Dynamic Email Content: The subject line and body of the notification email are dynamically adjusted based on whether the failure was an execution error or a trigger failure. Highly Customizable: Offers flexibility to modify email content (HTML), change the notification channel (e.g., Slack, other email providers), and adjust the logic for updating other workflows' error handlers. Scheduled Operation: The global configuration part runs on a user-definable schedule (e.g., daily, hourly) for proactive and automated error handling setup across your n8n instance. Who is this for? This workflow is designed for n8n users and administrators who want to: Establish a resilient and centralized error handling mechanism across their n8n instance. Receive immediate and detailed email notifications for any workflow failures. Automate the process of assigning a default error handling workflow to all their active n8n workflows. Save time on manually configuring error handlers for each individual workflow and ensure comprehensive error coverage. What problem is this workflow solving? / use case In an n8n environment with multiple workflows, errors can occur without immediate visibility. This can lead to: Unnoticed failures, potentially causing data loss or incomplete automated processes. Time-consuming diagnosis of issues due to a lack of readily available, detailed error information. Inefficiency and oversight from manually setting an error workflow for every new or existing workflow. This template tackles these issues by providing a proactive error management system. It not only alerts you to failures with comprehensive details but also ensures that your other workflows are automatically configured to use this centralized handler. What this workflow does This workflow operates in two distinct yet complementary parts: 1\. Scheduled Global Error Handler Configuration: Trigger: Initiates based on a configurable schedule (e.g., daily, hourly). Identify Self: Retrieves its own workflow ID to use as the designated error handler. Scan Workflows: Fetches a list of all other workflows within your n8n instance. Conditional Update Logic: For each active workflow found, it checks if: An error workflow (errorWorkflow setting) is not currently set, OR The currently set errorWorkflow is different from this central error handling workflow. The workflow is active. Apply Default Handler: If the above conditions are met, it automatically updates the target workflow's settings. This sets the current workflow as its default error handler, ensuring that any future errors in those workflows are routed here. The callerPolicy setting is also removed during this update. 2\. Error Notification via Email: Trigger: Activates whenever an error occurs in any n8n workflow that has this workflow designated as its errorWorkflow. Gather Error Context: Collects vital information about the failure, such as: The base URL of your n8n instance. Specific details of the workflow that failed (name, ID). The nature of the error: whether it's an "execution error" (occurring mid-workflow) or a "trigger failure" (occurring at the start). Format Detailed Error Message: Constructs a comprehensive HTML email tailored to the error type: For Execution Errors: The email includes a direct link to the failed execution's page, the timestamp of the error, the name of the last node that successfully executed, the error message, and the full error stack trace. For Trigger Failures: The email includes the timestamp, operational mode, error message, error name and description, relevant context data, details about the cause (message, name, code, status), and the stack trace. Send Email Notification: Dispatches the formatted HTML email using Gmail to a predefined recipient. The email subject line dynamically indicates the name of the failing workflow and the type of error, providing a quick overview. Setup Import Workflow: Import the JSON file into your n8n instance. Configure Credentials: n8n API Access: Locate the nodes: "N8n Get Error Handler", "N8n Get All Workflows", and "N8n Update Workflow". For each, select or create new n8n API credentials. These credentials must have permissions to read all workflows (workflows.read) and update workflows (workflows.update). Gmail Access: Locate the "Gmail Send Notification" node. Select or create new Gmail OAuth2 credentials to authorize n8n to send emails on your behalf. Set Email Recipient and Sender Details: Navigate to the "Settings" node, which is connected directly after the "Error Trigger" node. Modify the value for the Email Receiver variable to the email address where error notifications should be sent. Optionally, update the Email Sender Name variable. Configure Schedule (Optional): Select the "Schedule Trigger" node. Adjust the "Trigger Interval" (e.g., Every Day, Every Hour) according to how frequently you want the workflow to scan and update the error handler settings for other workflows in your n8n instance. Activate Workflow: Ensure this workflow is toggled to "Active". Once active, its scheduled component will begin operating, and it will be ready to process and notify on errors from other linked workflows. Manual Configuration (Optional): While this workflow automates the assignment, you can also manually set this workflow as the errorWorkflow in the settings of any critical existing workflows for immediate protection. How to customize this workflow to your needs Email Content & Formatting: Modify the HTML content within the "HTML For Execution Error" and "HTML For Trigger Error" nodes to alter the appearance, structure, or information included in the notification emails. Alternative Notification Channels: Replace the "Gmail Send Notification" node with a different email service node (e.g., Microsoft Outlook, SendGrid) or integrate other notification platforms like Slack, Microsoft Teams, or Discord. Remember to adjust the input data mappings for the new node. Refine Global Update Logic: Adjust the conditions within the "If No Default Error Handler Set" node if you need more granular control over which workflows are automatically updated (e.g., filter by workflow tags, names, or explicitly exclude certain workflows). Enrich Error Data: Insert additional nodes after the "Error Trigger" but before the "Settings" node if you need to fetch more context about the error or the workflow that failed (e.g., look up related information from a database or API). Advanced Notification Routing: Implement more complex logic prior to sending notifications. For example, you could use a Switch node to route error alerts to different email addresses or channels based on the name of the failing workflow or the severity of the error. Handling of callerPolicy: The "Set Data" node is configured to remove the callerPolicy setting from workflows it updates. If your workflows rely on this setting, you may need to modify or remove this part of the "Set Data" node's code. Adjust Scheduled Task: Change the frequency or timing of the "Schedule Trigger" to better suit your operational needs for the global error handler update.
By Daniel NgMerge binary objects on multiple items into a single item
This workflow is the opposite of this one. It transforms multiple different items with one binary object named data into a single item with multiple binary objects: This can be useful when creating a single .zip archive for example. It uses the updated Code node instead of the older Function node.
By TomExtract customer pain points from support forums with Bright Data & GPT-4
This workflow contains community nodes that are only compatible with the self-hosted version of n8n. This workflow automatically monitors customer support forums and Q&A platforms to extract valuable customer insights and pain points. It saves you time by eliminating the need to manually browse through forum discussions and provides structured analysis of customer questions, answers, and recurring issues. Overview This workflow automatically scrapes customer support forums like Stack Exchange and SuperUser to find questions and discussions related to specific topics or brands. It uses AI to analyze forum content, extract customer pain points, and identify recurring issues, then sends structured insights directly to your product team via email. Tools Used n8n: The automation platform that orchestrates the workflow Bright Data: For scraping forum pages and Q&A platforms without being blocked OpenAI: AI agent for intelligent forum content analysis and insight extraction Gmail: For sending automated insight reports to your team How to Install Import the Workflow: Download the .json file and import it into your n8n instance Configure Bright Data: Add your Bright Data credentials to the MCP Client node Set Up OpenAI: Configure your OpenAI API credentials Configure Gmail: Connect your Gmail account for sending team notifications Customize: Set target forum URLs and define the topics or brands to monitor Use Cases Product Teams: Identify customer pain points and feature requests from forum discussions Customer Support: Monitor common issues and questions customers are asking Market Research: Understand customer needs and challenges in your industry Competitive Analysis: Track how customers discuss competitor products and services Connect with Me Website: https://www.nofluff.online YouTube: https://www.youtube.com/@YaronBeen/videos LinkedIn: https://www.linkedin.com/in/yaronbeen/ Get Bright Data: https://get.brightdata.com/1tndi4600b25 (Using this link supports my free workflows with a small commission) n8n automation forummonitoring customersupport brightdata webscraping customerinsights n8nworkflow workflow nocode forumautomation customerresearch supportmonitoring painpointanalysis communitymonitoring forumanalysis customerfeedback productinsights supportforums stackexchange customervoice userresearch productfeedback techsupport communitylistening customerexperience supportanalysis forumdata qandamonitoring customerpainpoints
By Yaron BeenCreate an event in PostHog when a request is made to a webhook URL
This workflow automatically creates an event in PostHog when a request is made to a webhook URL. Prerequisites A PostHog account and credentials Nodes Webhook node triggers the workflow when a URL is accessed. PostHog node creates a new event in PostHog.
By Harshil AgrawalVisual storytelling content factory: Gemini & Replicate AI with human-in-the-loop publishing
This n8n workflow automates the entire content creation and publishing pipeline for engaging, AI-generated visual stories, ensuring image and video quality with human-in-the-loop approvals. What it does: It takes a narrative concept (e.g., 'A Day in the Life of a Serene Skeleton') and transforms it into a series of unique images and videos, which are then published across multiple social media platforms. How it works: Creative Conceptualization: An AI 'Creative Director' develops a detailed narrative, including scenes, moods, and character details. Prompt Engineering: An AI 'Creative Technician' translates the narrative into precise text-to-image and text-to-video prompts, maintaining a consistent artistic style, lighting, and character appearance. AI Asset Generation: Replicate's AI models (Qwen-Image for images and Seedance-1-Lite for videos) create the visual content from these prompts. Human-in-the-Loop Approval: Generated images and videos are sent to Slack for manual review. Users can approve or request regeneration, ensuring creative control and quality. Multi-Platform Publishing: Approved content is automatically published via Blotato to Instagram and Facebook (videos), and TikTok (image slideshows), ready for your audience. Technical Requirements: Replicate Account with Balance: For image and video generation (using Qwen-Image and Seedance-1-Lite). Blotato Subscription: For seamless publishing to multiple social media platforms. OpenRouter Account with Balance: To access various Large Language Models (LLMs) like Gemini 2.5 Flash for creative direction and prompt generation. Slack Account: For the human-in-the-loop approval process. Customization Potential: This workflow serves as a robust foundation that can be easily adapted for various use cases beyond story narratives, such as: Automating product publishing with AI-generated visuals and descriptions. Creating dynamic advertising content for campaigns. Generating personalized visual content for marketing. Scaling content creation for personal or e-commerce brands. Why use it? Ideal for content creators, marketers, and businesses seeking to scale their visual content production, maintain creative control through human oversight, and automate distribution (with scheduling option) to key social media channels (Instagram, Facebook, TikTok, X, Pinterest, YouTube, and more). Customize the initial story brief to unleash endless themed narratives tailored to your brand.
By Nadia PrivalikhinaAnalyze images & extract text with GPT-4o Vision and Telegram
Who’s it for Teams and makers who want a plug-and-play vision bot: users send a photo in Telegram, the bot returns a concise description plus OCR text. No custom servers required—just n8n, a Telegram bot, and an AIMLAPI key. What it does / How it works The workflow listens for new Telegram messages, fetches the highest-resolution photo, converts it to base64, normalizes the MIME type, and calls AIMLAPI (GPT-4o Vision) via the HTTP Request node using the OpenAI-compatible messages format with an image_url data URI. The model returns a short caption and extracted text. The answer is sent back to the same Telegram chat. Requirements n8n instance (self-hosted or cloud) Telegram bot token (from @BotFather) AIMLAPI account and API key (OpenAI-compatible endpoint) How to set up Create a Telegram bot with @BotFather and copy the token. In n8n, add Telegram credentials (no hardcoded tokens in nodes). Add AIMLAPI credentials with your API key (base URL: https://api.aimlapi.com/v1). Import the workflow JSON and connect credentials in the nodes. Execute the trigger and send a photo to your bot to test. How to customize the workflow Modify the vision prompt (e.g., add brand, language, or formatting rules). Switch models within AIMLAPI (any vision-capable model using the same messages schema). Add an IF branch for text-only messages (reply with guidance). Log usage to Google Sheets or a database (user id, file id, response). Add rate limits, user allowlists, or Markdown formatting in Telegram responses. Increase timeouts/retries in the HTTP Request node for long-running images.
By AI/ML API | D1m7asisGenerate multiple AI images with DALL·E 2 and upload to Google Drive
n8n Workflow: OpenAI DALL·E 2 Image Generation & Google Drive Upload Description This n8n workflow automates the process of generating multiple AI-created images from a single prompt using OpenAI's DALL·E 2, then uploads the results directly to a Google Drive folder. It includes a loop to produce several image variations for the same prompt, making it ideal for creative projects, marketing materials, or content experimentation. --- Step-by-Step Setup Instructions Prepare Your API Keys OpenAI API Key Sign up or log in at https://platform.openai.com/ Go to API Keys and create a new one. Copy and store this securely — you'll need it in n8n. Google Drive API Go to https://console.cloud.google.com/ Create a project and enable Google Drive API. Create OAuth 2.0 credentials and set the redirect URI to your n8n OAuth redirect (found in your n8n Google Drive node setup). Connect your Google account when adding credentials in n8n. --- Workflow Nodes Overview Manual Trigger – Starts the workflow manually. Set Image Prompt – Stores the prompt text and base file name (e.g., “Make an image of an attractive woman standing in New York City”). Duplicate Rows (Code Node) – Creates multiple "runs" of the same prompt for variation. Loop Over Items – Processes each variation one at a time. Generate an image (OpenAI DALL·E 2) – Sends the prompt to OpenAI and retrieves an image. Upload to Google Drive – Saves each generated image to your chosen Google Drive folder. --- Building the Workflow in n8n Step 1 — Manual Trigger Add a Manual Trigger node to start the workflow manually when testing. Step 2 — Set Image Prompt Add a Set node with two fields: Prompt → The image description text. Name → The base name for the saved file. Example: | Name | Value | |--------|---------------------------------------------------------------| | Prompt | Make an image of an attractive woman standing in New York City | | Name | woman-nyc | Step 3 — Duplicate Rows (Code Node) Use this JavaScript to create three copies of the prompt (run 1, run 2, run 3): javascript const original = items[0].json; return [ { json: { ...original, run: 1 } }, { json: { ...original, run: 2 } }, { json: { ...original, run: 3 } }, ]; Step 4 — Loop Over Items Insert a Split in Batches node and set the batch size to 1. This ensures each prompt variation runs through the image generation process individually. Connect this node so it runs after the Duplicate Rows node. Step 5 — Generate Image Add the OpenAI Image Generation node and configure it as follows: Model: dall-e-2 Prompt: ={{ $json.Prompt }} Leave other options at their defaults unless you want to specify image size or style. Connect your OpenAI API credentials created in Step 1. This node will send the current prompt in the batch to OpenAI's DALL·E 2 model and return an AI-generated image. Step 6 — Upload to Google Drive Add a Google Drive node and configure it to store the generated image: File Name: ={{ $('Set Image Prompt').item.json.Name }} - {{ $('Duplicate Rows').item.json.run }} Folder ID: Select the target Google Drive folder where images should be saved. Connect your Google Drive OAuth2 API credentials. The node will upload each generated image to your chosen Google Drive location, with a unique filename for each variation. --- Running the Workflow Execute the workflow manually. The process will: Loop through each prompt variation. Generate an image using OpenAI DALL·E 2. Upload the image to Google Drive with a unique name. You will find all generated images in the selected Google Drive folder. --- Customization Tips Change the number of variations by editing the Duplicate Rows code. Adjust the prompt dynamically from other data sources like Google Sheets, webhooks, or forms. Schedule the workflow to run at specific times or trigger it via an API call. --- Created by Robert A. – Ynteractive Website: https://ynteractive.com Email: robert@ynteractive.com
By Robert BreenExtract clinical data from medical documents with PDF vector & HIPAA compliance
Overview Healthcare organizations face significant challenges in digitizing and processing medical records while maintaining strict HIPAA compliance. This workflow provides a secure, automated solution for extracting clinical data from various medical documents including discharge summaries, lab reports, clinical notes, prescription records, and scanned medical images (JPG, PNG). What You Can Do Extract clinical data from medical documents while maintaining HIPAA compliance Process handwritten notes and scanned medical images with OCR Automatically identify and protect PHI (Protected Health Information) Generate structured data from various medical document formats Maintain audit trails for regulatory compliance Who It's For Healthcare providers, medical billing companies, clinical research organizations, health information exchanges, and medical practice administrators who need to digitize and extract data from medical records while maintaining HIPAA compliance. The Problem It Solves Manual medical record processing is time-consuming, error-prone, and creates compliance risks. Healthcare organizations struggle to extract structured data from handwritten notes, scanned documents, and various medical forms while protecting PHI. This template automates the extraction process while maintaining the highest security standards for Protected Health Information. Setup Instructions: Configure Google Drive credentials with proper medical record access controls Install the PDF Vector community node from the n8n marketplace Configure PDF Vector API credentials with HIPAA-compliant settings Set up secure database storage with encryption at rest Define PHI handling rules and extraction parameters Configure audit logging for regulatory compliance Set up integration with your Electronic Health Record (EHR) system Key Features: Secure retrieval of medical documents from Google Drive HIPAA-compliant processing with automatic PHI masking OCR support for handwritten notes and scanned medical images Automatic extraction of diagnoses with ICD-10 code validation Medication list processing with dosage and frequency information Lab results extraction with reference ranges and flagging Vital signs capture and normalization Complete audit trail for regulatory compliance Integration-ready format for EHR systems Customization Options: Define institution-specific medical terminology and abbreviations Configure automated alerts for critical lab values or abnormal results Set up custom extraction fields for specialized medical forms Implement medication interaction warnings and contraindication checks Add support for multiple languages and international medical coding systems Configure integration with specific EHR platforms (Epic, Cerner, etc.) Set up automated quality assurance checks and validation rules Implementation Details: The workflow uses advanced AI with medical domain knowledge to understand clinical terminology and extract relevant information while automatically identifying and protecting PHI. It processes various document formats including handwritten prescriptions, lab reports, discharge summaries, and clinical notes. The system maintains strict security protocols with encryption at rest and in transit, ensuring full HIPAA compliance throughout the processing pipeline. Note: This workflow uses the PDF Vector community node. Make sure to install it from the n8n community nodes collection before using this template.
By PDF VectorAI-powered YouTube meta generator with GPT-4o, Gemini & content enrichment
🎯 AI-Powered Advanced YouTube Meta Generator in n8n Automatically generate SEO-optimized YouTube Titles, Descriptions, Tags & Hashtags – enriched with blog articles, affiliate links, and product recommendations! --- Who is this for? This workflow is built for content creators, affiliate marketers, educators, and agencies who want to instantly enhance their YouTube videos with smart metadata and contextual linking — without wasting hours on research or copywriting. --- 🧠 What problem does it solve? Writing compelling, keyword-rich video metadata is essential for discoverability, engagement, and monetization. But doing this manually for every video is time-consuming. This workflow automates: Title & description writing Tag & hashtag generation Transcript analysis Affiliate link embedding Internal link recommendations (related blogs & videos) All in one flow — saving hours per video. --- ⚙️ What this workflow does 🔗 Accepts a YouTube video link + optional keywords 🧠 Uses Gemini or GPT-4o to analyze the transcript 📝 Auto-generates: SEO-friendly Title (under 70 chars) Catchy, benefit-focused Description with timestamps Tags (450+ chars) Hashtags (5–10 optimized) 🔁 Fetches your blog sitemap and matches relevant articles 📹 Finds similar past videos using AI 🛍 Embeds recommended affiliate links via Airtable 🔧 Updates YouTube video with new metadata via API --- 🛠 Setup 🔌 Connect APIs: YouTube Data API (OAuth 2.0) Gemini or OpenAI GPT-4o Airtable (for affiliate links) Kome AI for transcripts WordPress sitemap (for internal links) 📋 Deploy this workflow and open the form URL to input: YouTube Video Link (Optional) Focus Keywords 💬 Connect your accounts and authorize required scopes 🧠 AI will handle the rest: from fetching data to publishing metadata. --- ✏️ How to customize this workflow Replace Gemini with OpenAI / Claude / DeepSeek in the AI nodes Point the sitemap node to your own blog Modify the Airtable structure for affiliate links: Name, Type, Platform, URL, Keywords Change tag/hashtag formatting Modify prompt instructions in AI nodes for brand tone --- 📌 Sticky Notes Included ⚡ Form: “Enter Video Link + Optional Keywords” 🔍 Sitemap Extraction: “Get blog URLs for related links” 🧠 AI Logic: “Generate Metadata” ✅ Update Metadata: “Publish updated title/description/tags” 🧾 Completion Confirmation + Attribution to Amjid Ali --- 🌐 Useful Links 🧠 Learn n8n Automation 🎓 n8n Learning Guidebook 🚀 n8n Cloud Signup 🔧 SyncBricks Tools & Blog 🛍 Affiliate Product Hub --- 🔗 Why this workflow? This workflow is ideal for users exploring n8n AI, working with the n8n API, building AI agents in n8n, deploying via Docker or MCP, integrating with GitHub, automating processes using n8n automation, leveraging tools like n8n chat extension, enhancing YouTube metadata with AI, and incorporating cutting-edge platforms such as Context7, Blotato, and OpenAI, whether using n8n Cloud or setting up self-hosted n8n installations.
By Amjid Ali