Category: n8n Workflows

What This Workflow Does

This automated workflow analyzes X-ray images using advanced Vision Language Model (VLM) technology integrated with OpenAI-compatible APIs. Once an X-ray is uploaded through a form, the system automatically detects abnormalities, generates diagnostic insights, and distributes the analysis results across multiple communication channels including Gmail, Telegram, and Google Drive for seamless team collaboration and record-keeping.

How It Works

The workflow follows a structured automation process designed for medical imaging analysis:

• A form trigger captures X-ray image uploads from users
• The image is processed and converted into an appropriate file format
• The VLM Agent analyzes the X-ray using OpenAI-compatible endpoints to identify abnormalities and generate diagnostic insights
• Analysis results are compiled and formatted for distribution
• The workflow automatically sends detailed reports via Gmail to designated recipients
• Simultaneous notifications are dispatched through Telegram for immediate alerts
• A copy of the analysis is archived in Google Drive for long-term storage and compliance documentation

Use Cases

• Medical imaging centers automating X-ray analysis and report distribution to radiologists and referring physicians
• Hospitals integrating AI-assisted diagnostics into existing workflows with automatic report generation and multi-channel notification systems
• Telemedicine platforms providing real-time X-ray analysis to remote specialists with instant communication and document archival
• Diagnostic clinics streamlining the process of image review, analysis, and patient communication through automated channels
• Healthcare networks distributing imaging reports across departments while maintaining centralized documentation in cloud storage

Nodes Used

• Sticky Note – Workflow documentation and notes
• Form Trigger – Captures X-ray image uploads from users
• Code – Custom logic for image processing and data manipulation
• Set – Assigns and transforms data for workflow steps
• Convert to File – Transforms analysis results into shareable file formats
• Merge – Combines data from multiple workflow branches
• HTTP Request – Communicates with OpenAI-compatible VLM API endpoints
• OpenAI – Vision Language Model for X-ray image analysis
• Gmail – Sends detailed analysis reports via email
• Telegram – Delivers instant notifications to team members
• Google Drive – Archives analysis records for compliance and future reference

Prerequisites

• Active n8n instance with workflow automation capabilities
• OpenAI API key or compatible VLM service endpoint configured
• Gmail account with app-specific password or OAuth credentials for email distribution
• Telegram bot token and authorized chat IDs for message delivery
• Google Drive API credentials for document storage and archival
• Access to medical imaging files in common formats (JPEG, PNG, DICOM)
• Basic understanding of n8n workflow configuration and node setup

Difficulty Level

Intermediate to Advanced. This workflow requires experience with API integration, authentication setup across multiple services (Gmail, Telegram, Google Drive), and understanding of VLM capabilities. Users should be comfortable configuring OpenAI API connections and managing multi-channel distribution systems. Prior experience with n8n workflows is recommended.

This workflow template is shared under the n8n fair-code license. Free to use and modify.

What This Workflow Does

This n8n workflow automates the process of monitoring Zoom meeting attendance and initiating follow-up actions for participants with attendance issues. It runs on a scheduled basis to evaluate attendance patterns and automatically sends notifications or creates records for further action.

How It Works

The workflow operates through the following process:

• A scheduled trigger activates the workflow at specified intervals, typically aligned with when your meetings conclude
• The workflow connects to your Zoom account via OAuth2 credentials to retrieve meeting data from the last 24 hours
• Participant attendance information is extracted, including join times, leave times, and duration of attendance
• The attendance data is processed through conditional logic to identify participants who did not meet attendance requirements
• Follow-up actions are triggered automatically, which may include sending emails or creating records in Google Sheets
• Optional integration with Google Drive allows storage of attendance reports for record-keeping and compliance

Use Cases

• Educational institutions can monitor student attendance in online classes and automatically notify instructors of absent or tardy students
• Corporate training departments can track employee participation in mandatory meetings and generate compliance reports
• Event organizers can monitor attendee engagement across multiple Zoom sessions and follow up with no-shows automatically
• Healthcare providers can ensure patient attendance at telehealth appointments and send automated reminder follow-ups
• Project management teams can track team member availability during standup meetings and log attendance for project records

Nodes Used

• Schedule Trigger: Sets the timing for when the workflow executes, typically on an hourly basis
• Zoom Node: Connects to your Zoom account to retrieve recent meeting and participant data
• Item Lists: Processes and structures the attendance data for further evaluation
• HTTP Request: Makes API calls to fetch or send data to external services
• Code Node: Executes custom JavaScript to perform complex data transformations and calculations
• If Node: Creates conditional logic to route data based on attendance criteria
• Google Drive Node: Stores attendance reports and documentation in your Google Drive
• Email Send Node: Sends automated follow-up communications to participants or administrators
• Google Sheets Node: Records attendance data in spreadsheets for tracking and analysis

Prerequisites

• An active Zoom account with administrator or host permissions to access meeting data
• Zoom OAuth2 credentials configured within n8n for secure API access
• A Google account with access to Google Drive and Google Sheets for data storage and reporting
• Email service credentials configured in n8n for sending automated follow-up messages
• Understanding of your organization’s attendance requirements and follow-up procedures
• Basic familiarity with n8n workflow configuration and node setup

Difficulty Level

Intermediate. This workflow requires configuration of multiple external service connections including Zoom and Google services. Users should be comfortable setting up OAuth2 credentials and customizing conditional logic to match their specific attendance criteria. The code node may need customization depending on your particular attendance evaluation rules.

This workflow template is shared under the n8n fair-code license. Free to use and modify.

What This Workflow Does

This n8n workflow automates the process of scraping business data from online directories and automatically saves the results to a Google Sheet. It eliminates manual data entry and allows you to build targeted lead lists quickly and efficiently.

How It Works

• A manual trigger starts the workflow, though you can replace it with a Cron node to run on a schedule
• The BrowserAct node performs web scraping tasks with customizable inputs such as directory URLs and search parameters
• A code node processes and formats the scraped data to ensure consistency
• Google Sheets node automatically inserts the cleaned data into your spreadsheet
• Results are organized in columns for easy analysis and follow-up

Use Cases

• Generate local business leads from industry-specific directories for sales prospecting
• Monitor competitor listings and pricing changes across multiple directories automatically
• Build comprehensive contact databases for networking and partnership outreach
• Track business information updates and maintain an accurate client database
• Analyze market trends by collecting business data across geographic regions and industries

Nodes Used

• Manual Trigger – Initiates the workflow when you choose to run it
• BrowserAct – Performs automated web scraping and browser interactions
• Code – Processes and transforms the scraped data
• Google Sheets – Writes data directly to your spreadsheet
• Sticky Note – Documentation node for workflow notes and instructions

Prerequisites

• An active n8n account with access to workflow creation
• A Google account with Google Sheets enabled
• BrowserAct credentials configured in your n8n instance
• A prepared Google Sheet with headers matching your data structure
• Basic understanding of the directories you want to scrape

Difficulty Level

Intermediate. This workflow requires some familiarity with n8n, web scraping concepts, and Google Sheets integration, but includes helpful documentation through the sticky note node.

This workflow template is shared under the n8n fair-code license. Free to use and modify.

What This Workflow Does

This n8n workflow enables intelligent document interaction through Telegram. Users can upload PDF files to a Telegram bot, and the system indexes them using vector embeddings. Once indexed, users can ask questions about the document content, and the workflow retrieves relevant information and generates accurate answers powered by Google Gemini AI.

How It Works

The workflow operates in two primary modes: document indexing and question answering.

Document Processing: When a user uploads a file to Telegram, the trigger captures it. The document loader extracts text content, which is then split into manageable chunks using recursive character splitting. These chunks are converted into vector embeddings via Google Gemini and stored in Pinecone vector database for semantic search capabilities.

Question Answering: When a user sends a text message, the workflow routes it to the retrieval QA chain. The system searches the Pinecone vector store for relevant document chunks, passes them to Google Gemini along with the user’s question, and generates contextual answers. Responses are sent back to the user via Telegram.

A conditional router determines whether incoming messages are documents or text queries, directing them to the appropriate processing path. Rate limiting ensures the bot handles requests efficiently.

Use Cases

• Customer Support: Companies can upload product documentation, manuals, or FAQ documents. Support teams use Telegram to query these documents instantly, providing faster customer responses without searching through multiple files.
• Research Assistance: Researchers and students can upload academic papers, whitepapers, or study materials. They can ask specific questions about content and receive AI-generated summaries or explanations directly in Telegram.
• Legal Document Review: Law firms can index contracts, policies, or regulatory documents. Lawyers and paralegals can query these documents via Telegram to find specific clauses, definitions, or compliance requirements.
• Knowledge Management: Organizations can maintain a library of internal guides, procedures, and policies. Employees use the Telegram bot as a searchable knowledge base, reducing time spent looking for information.
• Training and Onboarding: Companies can upload training materials and employee handbooks. New employees can interact with these documents through Telegram to quickly find answers to onboarding questions.

Nodes Used

• Telegram Trigger: Listens for incoming messages and files from Telegram users
• Document Default Data Loader: Extracts text content from uploaded PDF files
• Text Splitter Recursive Character: Breaks documents into overlapping chunks for optimal embedding and retrieval
• Embeddings Google Gemini: Converts text chunks into vector embeddings for semantic search
• Vector Store Pinecone: Stores and retrieves vector embeddings from the Pinecone database
• Retriever Vector Store: Searches the vector database for relevant document chunks based on user queries
• Chain Retrieval QA: Combines retrieval results with the language model to generate contextual answers
• LM Chat Google Gemini: AI language model that generates responses based on retrieved context and user questions
• If Node: Routes messages to different processing paths based on message type
• Code Node: Custom logic for data transformation and validation
• Limit Node: Implements rate limiting to control request frequency
• Stop and Error: Handles error cases and halts execution when necessary
• Telegram Node: Sends responses back to users in Telegram
• Sticky Note: Documentation and notes within the workflow

Prerequisites

• Active n8n instance (self-hosted or cloud)
• Telegram Bot Token from BotFather
• Google Cloud account with Gemini API access and credentials
• Pinecone account with an active vector database index
• API keys for Google Gemini and Pinecone configured in n8n credentials
• PDF files ready for upload and indexing
• Basic understanding of RAG (Retrieval Augmented Generation) concepts

Difficulty Level

Intermediate to Advanced: This workflow requires knowledge of vector databases, embeddings, and LLM integration. Users should be comfortable configuring API credentials, understanding prompt engineering basics, and troubleshooting multi-step automation flows. However, the workflow provides a solid foundation for those new to RAG systems and can be modified for various document interaction use cases.

This workflow template is shared under the n8n fair-code license. Free to use and modify.

What This Workflow Does

This n8n workflow automates the collection and delivery of YouTube analytics data on a weekly basis. It fetches your channel’s performance metrics and sends a comprehensive report directly to Telegram, eliminating the need for manual data gathering and report creation.

How It Works

The workflow operates on a scheduled trigger that runs once per week. It begins by making an HTTP request to retrieve your YouTube analytics data, processes the information through custom code logic, merges the results into a formatted message, and delivers the final report to your Telegram channel or chat. This ensures you stay informed about your channel’s performance without lifting a finger.

Use Cases

• Content creators monitoring weekly growth metrics including views, watch time, and subscriber changes
• YouTube channel managers tracking performance trends to optimize content strategy
• Digital marketers analyzing audience engagement data for multiple client channels
• Small business owners keeping tabs on their YouTube marketing ROI and audience behavior
• Content agencies distributing weekly performance summaries to team members and stakeholders

Nodes Used

• Schedule Trigger: Initiates the workflow on a weekly schedule
• HTTP Request: Fetches YouTube analytics data via API
• Code: Processes and transforms the raw analytics data
• Merge: Combines processed data into a formatted message structure
• Telegram: Sends the final report to your designated Telegram recipient

Prerequisites

• An active n8n instance or account
• YouTube API credentials and proper authentication setup
• A Telegram bot token and chat ID for message delivery
• Basic understanding of workflow configuration and API integration
• YouTube channel with analytics data available

Difficulty Level

Intermediate. This workflow requires knowledge of API authentication, basic data transformation, and Telegram bot setup. Users comfortable with n8n’s core features and API configuration will find this workflow straightforward to implement and customize.

This workflow template is shared under the n8n fair-code license. Free to use and modify.

What This Workflow Does

This YouTube Community Post Automation workflow automatically generates engaging community posts with dynamic images on a scheduled basis. It uses artificial intelligence to create original content, retrieves data from Google Sheets, and publishes directly to YouTube. The workflow eliminates manual content creation while maintaining quality and consistency across your YouTube community engagement strategy.

How It Works

The workflow operates through a series of integrated steps that work together seamlessly. A scheduled trigger activates the automation at your specified intervals. The system retrieves data from Google Sheets to gather content parameters and context. The code node processes this information and prepares it for AI processing. Multiple AI models through OpenRouter generate original, engaging community post content. Finally, the HTTP request node sends the formatted post with dynamic images to YouTube Community. This creates a fully automated content pipeline from data collection to publishing.

Use Cases

• Content Creators: Schedule daily or weekly community posts that keep audiences engaged without manual effort, perfect for creators managing multiple channels.
• Educational Channels: Automatically generate discussion prompts and learning resources that encourage viewer interaction and community participation.
• Business Channels: Post regular product updates, tips, and announcements with branded imagery to maintain consistent channel activity and subscriber engagement.
• Gaming Channels: Create event announcements, community challenges, and interactive posts with custom graphics that drive viewer interaction and retention.
• News and Commentary Channels: Schedule timely community posts that complement main video releases and encourage viewer discussions on trending topics.

Nodes Used

• Schedule Trigger: Initiates the workflow at predetermined intervals such as daily, weekly, or custom schedules based on your content calendar.
• Code Node: Processes raw data and transforms it into structured formats compatible with AI models and YouTube API requirements.
• Chain LLM: Orchestrates multiple AI language model calls in sequence to generate layered, complex content with improved quality and relevance.
• LM Chat OpenRouter: Connects to advanced language models through OpenRouter to generate creative, contextual community post content.
• Google Sheets: Serves as your data source, storing content ideas, scheduling information, and dynamic variables for post customization.
• HTTP Request: Sends the finalized community post with images to YouTube using the Community API endpoints for automated publishing.

Prerequisites

• Active n8n instance with workflow creation capabilities and access to community nodes.
• YouTube channel with community posting privileges and active API credentials configured.
• Google Sheets account with at least one spreadsheet containing your content data and posting schedule.
• OpenRouter API key for accessing language models and AI content generation capabilities.
• Basic understanding of n8n node configuration and API authentication methods.
• Image assets or access to image generation tools for creating dynamic post graphics.

Difficulty Level

This workflow is suitable for intermediate to advanced n8n users. While the core concept is straightforward, successful implementation requires familiarity with API authentication, Google Sheets integration, and AI model prompt engineering. Users should have experience setting up OAuth connections and understanding JSON data structures. Beginners can still deploy this workflow by following detailed setup documentation but may need to customize AI prompts and data mapping based on their specific needs. The complexity primarily lies in integrating multiple external services rather than the workflow logic itself.

This workflow template is shared under the n8n fair-code license. Free to use and modify.

What This Workflow Does

This n8n workflow automates your complete YouTube content strategy using artificial intelligence, web scraping, and data analysis. It systematically analyzes YouTube niches, identifies trending content opportunities, evaluates competitor strategies, and generates actionable content recommendations—all without manual research.

How It Works

The workflow operates across five integrated phases that work together to transform raw YouTube data into strategic insights:

• Phase 1: Niche Outliers – Identifies unusual and emerging content patterns in your target niche that competitors might be missing
• Phase 2: Broad Niche Insights (Weekly) – Conducts comprehensive weekly analysis of trending topics, popular formats, and audience engagement patterns across your entire niche
• Phase 3: Niche Insights (Daily) – Monitors daily changes in niche trends, new video uploads, and shifting audience interests for real-time strategy adjustments
• Phase 4: Comment Analysis – Extracts and analyzes viewer comments to understand audience pain points, questions, and content preferences
• Phase 5: Ideation – Generates original video ideas based on all collected data, gaps in competitor content, and identified audience needs

Use Cases

• YouTube Channel Growth – Rapidly scale subscriber counts by creating content that matches proven demand and audience preferences in your niche
• Competitor Analysis – Understand what successful channels in your space are doing right and identify gaps where your content can stand out
• Content Calendar Planning – Generate weeks worth of data-backed video ideas automatically, eliminating creator’s block and guesswork
• Trend Identification – Stay ahead of trending topics in your niche before they become saturated with competition
• Audience Research – Discover exactly what questions viewers are asking and what problems they want solved through video content

Nodes Used

This workflow leverages 16 specialized n8n nodes to orchestrate the entire YouTube strategy automation:

• formTrigger – Accepts manual input to start the workflow
• scheduleTrigger – Schedules automated daily and weekly analysis runs
• set – Initializes and configures workflow variables
• splitOut – Distributes data across parallel processing paths
• splitInBatches – Divides large datasets into manageable chunks
• httpRequest – Connects to Apify for web scraping YouTube data
• @n8n/agent – Coordinates AI-powered analysis tasks
• @n8n/lmChatOpenRouter – Processes natural language analysis via OpenRouter
• @n8n/openAi – Generates insights and content ideas using OpenAI models
• @n8n/outputParserStructured – Formats AI responses into structured data
• googleSheets – Stores results in Google Sheets for easy access and sharing
• merge – Combines data from multiple processing paths
• aggregate – Summarizes and consolidates analysis results
• sort – Organizes insights by relevance and priority
• filter – Removes low-quality or irrelevant suggestions
• limit – Caps results to focus on top recommendations
• slack – Sends notifications of key findings to your Slack workspace

Prerequisites

Before deploying this workflow, ensure you have access to the following services and credentials:

• An active n8n account with workflow creation permissions
• Apify API key for YouTube data scraping capabilities
• OpenAI API key for advanced content analysis and ideation
• OpenRouter API key for alternative language model processing
• Google Sheets API credentials for spreadsheet integration
• Slack workspace access if you want automated notifications
• A target YouTube niche or channel URL to analyze

Difficulty Level

Intermediate. This workflow requires basic familiarity with n8n, API key management, and connecting third-party services. While the nodes are pre-configured, you will need to add your own API credentials and customize the analysis parameters to match your specific YouTube niche and goals. No coding knowledge is required, but attention to detail during setup is important for optimal results.

This workflow template is shared under the n8n fair-code license. Free to use and modify.

What This Workflow Does

This workflow automates the entire YouTube thumbnail creation process by extracting video metadata from YouTube links and generating custom, professional thumbnails. Once created, thumbnails are automatically stored in Google Drive and can be distributed via email or other channels. This eliminates manual thumbnail design work and ensures consistent, branded visuals for your YouTube content.

How It Works

The automation begins when you send a YouTube video link through Telegram. The workflow then processes your request through the following sequence:

• Receives the YouTube URL via Telegram trigger
• Extracts video metadata and information using the YouTube API
• Generates a custom thumbnail design using Templated.io integration
• Uploads the generated thumbnail to Google Drive for storage and access
• Sends the thumbnail via email notification
• Returns confirmation message through Telegram

Use Cases

• YouTube content creators looking to streamline thumbnail production and maintain visual consistency across their channel
• Content marketing teams managing multiple video assets and needing automated design workflows
• Social media managers creating branded thumbnails for video content distribution
• Digital agencies handling thumbnail creation for multiple client YouTube channels
• Bulk video uploaders who need quick thumbnail generation without design software

Nodes Used

• Telegram Trigger – Receives YouTube URLs and initiates the workflow
• HTTP Request – Communicates with YouTube API and external services
• Code – Processes and transforms data between workflow steps
• Google Drive – Stores generated thumbnails in cloud storage
• Google Sheets – Optional logging and tracking of created thumbnails
• Gmail – Sends email notifications with thumbnail attachments
• Telegram – Sends completion confirmations back to users
• OpenAI – Generates descriptive text and metadata for thumbnails
• Templated.io – Creates custom thumbnail designs
• Blotato – Additional processing and image manipulation
• Wait – Manages timing between API calls and processing steps

Prerequisites

• Active YouTube account with API access enabled
• Telegram account and Telegram bot token
• Google Account with Drive and Gmail access
• Templated.io account and API credentials
• OpenAI API key for text generation features
• n8n instance or n8n cloud account
• Basic understanding of workflow automation concepts

Difficulty Level

Intermediate to Advanced. This workflow requires multiple API integrations and basic knowledge of workflow automation. Users should be comfortable setting up API credentials, understanding node connections, and troubleshooting integration issues. However, the workflow is well-structured and can be modified by users with moderate automation experience.

This workflow template is shared under the n8n fair-code license. Free to use and modify.

What This Workflow Does

This n8n workflow automates the complete YouTube video publishing process. It monitors a Google Drive folder for new video files, extracts the video transcript, generates SEO-optimized metadata including titles and descriptions using AI, and automatically uploads the video to YouTube with all metadata applied.

How It Works

The workflow operates through the following sequence of steps:

• Google Drive Trigger monitors a specified folder for newly uploaded video files
• Google Drive node retrieves file information and content from the detected video
• OpenAI processes the video to extract transcripts and understand content context
• Google Gemini AI generates SEO-optimized titles, descriptions, and tags based on the transcript
• Agent node coordinates the workflow logic and decision-making between different AI models
• HTTP Request node handles API communications for additional services if needed
• Code node performs custom transformations on the generated metadata
• YouTube node uploads the video with all generated metadata applied automatically

Use Cases

• Content creators managing multiple YouTube channels who need to batch upload videos with minimal manual effort
• Educational institutions publishing lecture videos and course materials with automatically generated descriptions
• Podcast networks converting audio content to video format and distributing across YouTube
• Marketing agencies managing client YouTube channels and ensuring consistent metadata optimization
• News organizations publishing daily video content with AI-generated summaries and SEO optimization

Nodes Used

• googleDriveTrigger – Monitors Google Drive folder for new video uploads
• googleDrive – Retrieves video files and metadata from Google Drive
• @n8n/openAi – Processes video transcripts and generates content analysis
• @n8n/lmChatGoogleGemini – Generates SEO-optimized metadata and descriptions
• @n8n/agent – Coordinates workflow logic and AI model interactions
• httpRequest – Handles external API requests and data transmission
• code – Executes custom JavaScript for metadata transformation
• youTube – Uploads videos and applies metadata to YouTube channel
• stickyNote – Provides workflow documentation and step annotations
• set – Manages and formats workflow variables

Prerequisites

• Active n8n instance with workflow execution capabilities
• Google Drive account with video files stored in an accessible folder
• YouTube channel with upload permissions and API credentials configured
• OpenAI API key for transcript processing and content analysis
• Google Gemini API access for metadata generation
• Proper OAuth2 authentication set up for Google services and YouTube API
• Video files in supported formats (MP4, MOV, AVI, etc.)
• Sufficient API quota for both OpenAI and Gemini services

Difficulty Level

Advanced. This workflow requires familiarity with multiple API integrations, OAuth2 authentication, and AI model configuration. Users should have experience setting up Google Drive and YouTube API credentials, understanding how to manage API keys securely, and basic knowledge of AI prompt engineering for optimal metadata generation.

This workflow template is shared under the n8n fair-code license. Free to use and modify.

What This Workflow Does

This n8n workflow automatically monitors a YouTube channel for new videos and posts the video link directly to a Slack channel. When a new video is published, the workflow detects it and sends a formatted message to your Slack workspace within 30 minutes, keeping your team instantly notified about fresh content.

How It Works

The workflow operates on a scheduled interval using a cron trigger that checks for updates every 30 minutes. It fetches the YouTube channel RSS feed to identify new videos, processes the data with custom code to extract video details, and then sends a formatted message to your designated Slack channel. The system intelligently tracks the last video posted to avoid duplicate notifications.

• Cron scheduler initiates the workflow at regular 30-minute intervals
• HTTP request node retrieves the YouTube RSS feed for your channel
• Code node parses the XML feed and extracts video information
• Slack node delivers the formatted message to your channel
• Workflow maintains state to prevent duplicate posts

Use Cases

• Content Team Notifications: Keep your marketing and social media teams informed immediately when new videos go live for coordinated promotion
• Community Engagement: Notify community members or Discord-to-Slack bridges about new educational or entertainment content instantly
• Multi-Channel Publishing: Use Slack as a hub to trigger additional publishing workflows to other platforms when videos are detected
• Video Analytics Tracking: Create a Slack-based archive of all published videos with timestamps for content performance monitoring
• Client Reporting: Automatically notify clients or stakeholders when their commissioned videos are published

Nodes Used

• Sticky Note: Documentation node for setup instructions and workflow overview
• Cron: Scheduler that triggers the workflow every 30 minutes
• HTTP Request: Fetches the YouTube channel RSS feed using the channel ID
• Code: Processes and parses the RSS XML data to extract video titles, URLs, and metadata
• Slack: Sends formatted messages with video links to your specified Slack channel

Prerequisites

• Active YouTube channel with public access enabled
• YouTube Channel ID found in your channel URL (format: UC followed by alphanumeric characters)
• Slack workspace with permissions to create OAuth connections
• Slack channel where the bot has message posting permissions
• n8n account with access to create and manage workflows
• Basic understanding of RSS feeds and Slack integration setup

Difficulty Level

Beginner to Intermediate: This workflow requires minimal coding knowledge as most functionality uses pre-built nodes. However, you will need to locate your YouTube Channel ID, configure Slack OAuth authentication, and potentially adjust the cron schedule based on your preferences. The setup process takes approximately 10-15 minutes for users with basic familiarity with YouTube and Slack.

This workflow template is shared under the n8n fair-code license. Free to use and modify.