Workflow Templates

Automated Multilingual Gmail Draft Reply with OpenAI GPT-4o in n8n Who is this for? This workflow is ideal for anyone who receives a high volume of Gmail inquiries, especially those providing multilingual customer support or handling diverse client communications. What problem is this workflow solving? Managing frequent emails in multiple languages can be overwhelming. This workflow reduces manual drafting by automatically generating context-aware replies using OpenAI GPT-4o, letting users focus on personalization and quality assurance. What this workflow does Monitors your Gmail inbox for new emails with a specific label (e.g., "Inquiry"). Uses OpenAI GPT-4o for message assessment and language detection. Parses information using a JSON parser. Generates an AI-powered draft reply in the detected language via OpenAI GPT-4o. Converts the reply to HTML and saves it as a draft in the original Gmail thread for your review. Setup Connect your Gmail account and set up relevant labels in both Gmail and the workflow. Integrate your OpenAI credentials in n8n. Configure the workflow trigger for your desired labels. How to customize this workflow to your needs Adjust label names in both Gmail and the workflow for different email categories. Define custom starting and ending phrases for draft replies per supported language. Expand supported languages or modify AI prompt instructions to suit your brand’s tone.

This workflow allows users to generate AI videos using Google Veo3, save them to Google Drive, generate optimized YouTube titles with GPT-4o, and automatically upload them to YouTube with Upload-Post. The entire process is triggered from a Google Sheet that acts as the central interface for input and output. IT automates video creation, uploading, and tracking, ensuring seamless integration between Google Sheets, Google Drive, Google Veo3, and YouTube. Benefits of this Workflow 💡 No Code Interface**: Trigger and control the video production pipeline from a simple Google Sheet. ⚙️ Full Automation**: Once set up, the entire video generation and publishing process runs hands-free. 🧠 AI-Powered Creativity**: Generates engaging YouTube titles using GPT-4o. Leverages advanced generative video AI from Google Veo3. 📁 Cloud Storage & Backup**: Stores all generated videos on Google Drive for safekeeping. 📈 YouTube Ready**: Automatically uploads to YouTube with correct metadata, saving time and boosting visibility. 🧪 Scalable**: Designed to process multiple video prompts by looping through new entries in Google Sheets. 🔒 API-First**: Utilizes secure API-based communication for all services. How It Works Trigger: The workflow can be started manually ("When clicking ‘Test workflow’") or scheduled ("Schedule Trigger") to run at regular intervals (e.g., every 5 minutes). Fetch Data: The "Get new video" node retrieves unfilled video requests from a Google Sheet (rows where the "VIDEO" column is empty). Video Creation: The "Set data" node formats the prompt and duration from the Google Sheet. The "Create Video" node sends a request to the Fal.run API (Google Veo3) to generate a video based on the prompt. Status Check: The "Wait 60 sec." node pauses execution for 60 seconds. The "Get status" node checks the video generation status. If the status is "COMPLETED," the workflow proceeds; otherwise, it waits again. Video Processing: The "Get Url Video" node fetches the video URL. The "Generate title" node uses OpenAI (GPT-4.1) to create an SEO-optimized YouTube title. The "Get File Video" node downloads the video file. Upload & Update: The "Upload Video" node saves the video to Google Drive. The "HTTP Request" node uploads the video to YouTube via the Upload-Post API. The "Update Youtube URL" and "Update result" nodes update the Google Sheet with the video URL and YouTube link. Set Up Steps Google Sheet Setup: Create a Google Sheet with columns: PROMPT, DURATION, VIDEO, and YOUTUBE_URL. Share the Sheet link in the "Get new video" node. API Keys: Obtain a Fal.run API key (for Veo3) and set it in the "Create Video" node (Header: Authorization: Key YOURAPIKEY). Get an Upload-Post API key (for YouTube uploads) and configure the "HTTP Request" node (Header: Authorization: Apikey YOUR_API_KEY). YouTube Upload Configuration: Replace YOUR_USERNAME in the "HTTP Request" node with your Upload-Post profile name. Schedule Trigger: Configure the "Schedule Trigger" node to run periodically (e.g., every 5 minutes). Need help customizing? Contact me for consulting and support or add me on Linkedin.

This template will create a nightly backup of all your n8n workflows to a Dropbox folder. Each night, the previous night's backups are moved into an "old" folder, and renamed with the date they were taken. Backups over a specified age are deleted. (this is disabled by default for safety until you manually enable and verify it with your own setup) Prerequisites Dropbox account and credentials A destination folder for backups Setup Update all dropbox nodes with your credential Edit the Schedule Trigger node with the desired time to run the backup Edit the DESTINATION FOLDER node to specify the path in dropbox to upload to. This should be a folder and include the trailing / If you want to automatically purge old backups Edit the PURGE DAYS node to specify the age to purge Enable the PURGE DAYS node, and the 3 subsequent nodes Enable the workflow to run on the specified schedule

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. AI Arena - Debate of AI Agents to Optimize Answers and Simulate Diverse Scenarios Overview Version: 1.0 The AI Arena Workflow is designed to facilitate a refined answer generation process by enabling a structured debate among multiple AI agents. This workflow allows for diverse perspectives to be considered before arriving at a final output, enhancing the quality and depth of the generated responses. ✨ Features Multi-Agent Debate Simulation**: Engage multiple AI agents in a debate to generate nuanced responses. Configurable Rounds and Agents**: Easily adjust the number of debate rounds and participating agents to fit your needs. Contextualized AI Responses**: Each agent operates based on predefined roles and characteristics, ensuring relevant and focused discussions. JSON Output**: The final output is structured in JSON format, making it easy to integrate with other systems or workflows. 👤 Who is this for? This workflow is ideal for developers, data scientists, content creators, and businesses looking to leverage AI for decision-making, content generation, or any scenario requiring diverse viewpoints. It is particularly useful for those who need to synthesize information from multiple personalities or perspectives. 💡 What problem does this solve? The workflow addresses the challenge of generating nuanced responses by simulating a debate among AI agents. This approach ensures that multiple perspectives are considered, reducing bias and enhancing the overall quality of the output. Use-Case examples: 🗓️ Meeting/Interview Simulation ✔️ Quality Assurance 📖 Storywriter Test Environment 🏛️ Forum/Conference/Symposium Simulation 🔍 What this workflow does The workflow orchestrates a debate among AI agents, allowing them to discuss, critique, and suggest rewrites for a given input based on their roles and predefined characteristics. This collaborative process leads to a more refined and comprehensive final output. 🔄 Workflow Steps Input & Setup: The initial input is provided, and the AI environment is configured with necessary parameters. Round Execution: AI agents execute their roles, providing replies and actions based on the input and their individual characteristics. Round Results: The results of each round are aggregated, and a summary is created to capture the key points discussed by the agents. Continue to Next Round: If more rounds are defined, the process repeats until the specified number of rounds is completed. Final Output: The final output is generated based on the agents' discussions and suggestions, providing a cohesive response. ⚡ How to Use/Setup 🔐 Credentials Obtain an API key for the Mistral API or another LLM API. This key is necessary for the AI agents to function properly. 🔧 Configuration Set up the workflow in n8n, ensuring all nodes are correctly configured according to the workflow requirements. This includes setting the appropriate input parameters and defining the roles of each AI agent. This workflow uses a custom node for Global Variables called 'n8n-nodes-globals.' Alternatively, you can use the 'Edit Field (Set)' node to achieve the same functionality. ✏️ Customizing this workflow To customize the workflow, adjust the AI agent parameters in the JSON configuration. This includes defining their roles, personalities, and preferences, which will influence how they interact during the debate. One of the notes includes a ready-to-use example of how to customize the agents and the environment. You can simply edit it and insert it as your credential in the Global Variables node. 📌 Example An example with both input and final output is provided in a note within the workflow. 🛠️ Tools Used n8n: A workflow automation tool that allows users to connect various applications and services. Mistral API: A powerful language model API used for generating AI responses. (You can replace it with any LLM API of your choice) Podman: A container management tool that allows users to create, manage, and run containers without requiring a daemon. (It serves as an alternative to Docker for container orchestration.) ⚙️ n8n Setup Used n8n Version**: 1.100.1 n8n-nodes-globals**: 1.1.0 Running n8n via**: Podman 4.3.1 Operating System**: Linux ⚠️ Notes, Assumptions & Warnings Ensure that the AI agents are configured with clear roles to maximize the effectiveness of the debate. Each agent's characteristics should align with the overall goals of the workflow. The workflow can be adapted for various use cases, including meeting simulations, content generation, and brainstorming sessions. This workflow assumes that users have a basic understanding of n8n and JSON configuration. This workflow assumes that users have access to the necessary API keys and permissions to utilize the Mistral API or other LLM APIs. Ensure that the input provided to the AI agents is clear and concise to avoid confusion in the debate process. Ambiguous inputs may lead to unclear or irrelevant outputs. Monitor the output for relevance and accuracy, as AI-generated content may require human oversight to ensure it meets standards and expectations before being used in production. ℹ️ About Us This workflow was developed by the Hybroht team of AI enthusiasts and developers dedicated to enhancing the capabilities of AI through collaborative processes. Our goal is to create tools that harness the possibilities of AI technology and more.

Description: This template facilitates the transfer of a folder, along with all its files and subfolders, within a Nextcloud instance. The Nextcloud user must have access to both the source and destination folders. While Nextcloud allows folder movement, complications may arise when dealing with external storage that has rate limits. This workflow ensures the individual transfer of each file to avoid exceeding rate limits, particularly useful for setups involving external storage with rate limitations. How it works: Identify all files and subfolders within the specified source folder. Recursive search within subfolders for additional files. Replicate the folder structure in the target folder. Individually move each identified file to the corresponding location in the target folder. Set up steps: Set Nextcloud credentials for all Nextcloud nodes involved in the process. -Edit the trigger settings. Detailed instructions can be found within the respective trigger configuration. Initiate the workflow to commence the folder transfer process. Help If you need assistance with applying this template, feel free to reach out to me. You can find additional information about me and my services here. => https://nicokowalczyk.de/links I have also produced a video where I explain the workflow and provide an example. You can find this video over here. https://youtu.be/K1kmG_Q_jRk Cheers. Nico Kowalczyk

Automated Gmail Labeling and Brainstorming This template can be used to automatically label your incoming Gmail messages with AI and to build a knowledge graph from the emails tagged with a specific label to brainstorm new ideas based on them. You can also get notified about the emails with the most important labels via Telegram as well as receive new ideas as you are building a knowledge graph of incoming messages. The idea generation is based on the InfraNodus knowledge graph content gap detection algorithm, which builds a network from your content and then finds a blind spot and uses AI to generate an interesting research question or idea that can be used to bridge this gap. Why it works so well? Think of all the business emails you receive that bypass the spam filters. Probably, they are personalized to you already. Now imagine if you build a knowledge graph from them for over a month. You will then have a ideation device based on your interests and marketing profile. Now, if you identify the gaps inside and generate interesting research questions based on them, you will come up with new interesting ideas that will be relevant (because they touch on the topics that matter to you), but novel, because they bridge them in new ways. What is it useful for? Automate Gmail incoming message labeling** with the new Classifier n8n node — much more advanced than the default Gmail labeling rules. Get notified via Telegram (or a messenger of your choice) about the most important messages and be sure not to miss anything important. Keep the messages with a certain label saved into knowledge graph for brainstorming and ideation. Every time a new message of this category comes in, it's added into the graph, changing its structure, a new idea is generated. So instead of looking at each specific offer, you now use them to generate insights for you. How it works Step 1: This template can is triggered automatically when a new Gmail message arrives. Note: you need to connect your Gmail account here in this node Step 2: We use the new n8n AI Classifier Node to classify your email based on its content. You might need to update to n8n 1.94 version to make it work. Note: we like to use Gemini AI for that classifier as it's the same company as Gmail, so should be safe with data Step 3: After classifying the message, we label the message with the appropriate label. Note: you need to create the labels before in your Gmail account Step 4: For a certain category (e.g. "Business" you format the message and save it into your InfraNodus graph. *Note: specify your InfraNodus API here and choose the name of the graph. It will use the InfraNodus HTTP graphAndEntries endpoint and save your data to an InfraNodus graph. By default, we save the text knowledge graph using the contextSettings parameters (it will only build a text graph of the content), but you can take an alternative setting from this InfraNodus HTTP node's settings and create a social knowledge graph, that will also show email senders in the graph itself.* Step 5 (optional): Generate an interesting insight question with the graphAndAdvice endpoint) of InfraNodus. Step 6 (optional): Then send this insight via Telegram to a chat. Step 7 (optional): Link some important labels to the second Telegram notification node, so you receive important messages for specified labels. Step 8 (optional): Send a Telegram notification We use Telegram, because it takes only 30 seconds to set up a bot with an API (send /newbot to @botfather, unlike Discord or Slack, which is long and cumbersome to set up. You can also attach a Gmail send node and generate an email instead. How to use You need an InfraNodus GraphRAG API account and key to use this workflow. Create an InfraNodus account or log in. Get the API key at https://infranodus.com/api-access and create a Bearer authorization key for the InfraNodus HTTP nodes. Add this Authorization code in Steps 4 and 5 of the workflow. Come up with the name of the graph and change it in the HTTP InfraNodus nodes in the steps 4 and 5 and also in the Telegram node in Step 6 that sends a link to the graph. For additional text processing / idea generation settings you can use in the HTTP InfraNodus nodes, see the InfraNodus access points page. For example, in Step 4 you can change the text processing settings to build a social knowledge graph (settings are available in the Node's Notes section) and in Step 5 you can change the requestMode from question to idea to receive business ideas instead. Authorize your Gmail account for Steps 2, 3, 7 and 8 Gmail nodes. The easiest way to set it up is to open a free Google Console API account and to create an OAuth access point for n8n. You can then reuse it with other Google services like Google Sheets, Drive, etc. So it's a useful thing to have in general. Set up the Gemini AI API key using the instructions in the Step 2 Gemini AI classification node. Set up the Telegram node bot for the Step 8. It takes only 30 seconds: just go to @botfather and type in /newbot and you'll have an API key ready. To get the conversation ID, follow the n8n / Telegram instructions in the node itself. Once everything is ready, try to run the default automated workflow to test if everything works well. Requirements An InfraNodus account and API key An Google Cloud API OAuth client and key for Gmail access A Gemini AI API key A Telegram bot API key n8n version 1.94 and higher (for Text Classification AI node to work) Customizing this workflow Check our other n8n workflows at https://n8n.io/creators/infranodus/ for useful content gap analysis, expert panel, and marketing, and research workflows that utilize GraphRAG for better AI generation. Finally, check out https://infranodus.com to learn more about our network analysis technology used to build knowledge graphs from text. For support, please, contact https://support.noduslabs.com

AI-Powered SEO Keyword Research Workflow with n8n > automates comprehensive keyword research for content creation Table of Contents Introduction Workflow Architecture NocoDB Integration Data Flow Core Components Setup Requirements Possible Improvements Introduction This n8n workflow automates SEO keyword research using AI and data-driven analytics. It combines OpenAI's language models with DataForSEO's analytics to generate comprehensive keyword strategies for content creation. The workflow is triggered by a webhook from NocoDB, processes the input data through multiple stages, and returns a detailed content brief with optimized keywords. Workflow Architecture The workflow follows a structured process: Input Collection: Receives data via webhook from NocoDB Topic Expansion: Generates keywords using AI Keyword Metrics Analysis: Gathers search volume, CPC, and difficulty metrics Competitor Analysis: Analyzes competitor content for ranking keywords Final Strategy Creation: Combines all data to generate a comprehensive keyword strategy Output Storage: Saves results back to NocoDB and sends notifications NocoDB Integration Database Structure The workflow integrates with two tables in NocoDB: Input Table Schema This table collects the input parameters for the keyword research: | Field Name | Type | Description | | --------------- | ------------- | --------------------------------------------------------------------------- | | ID | Auto Number | Unique identifier | | Primary Topic | Text | The main keyword/topic to research | | Competitor URLs | Text | Comma-separated list of competitor websites | | Target Audience | Single Select | Description of the target audience (Solopreneurs, Marketing Managers, etc.) | | Content Type | Single Select | Type of content (Blog, Product page, etc.) | | Location | Single Select | Target geographic location | | Language | Single Select | Target language for keywords | | Status | Single Select | Workflow status (Pending, Started, Done) | | Start Research | Checkbox | Active Workflow when you set this to true | Output Table Schema This table stores the generated keyword strategy: | Field Name | Type | Description | | ------------------ | ----------- | ------------------------------------------------ | | ID | Auto Number | Unique identifier | | primary_topic_used | Text | The topic that was researched | | report_content | Long Text | The complete keyword strategy in Markdown format | | generatedAt | Datetime | Automatically generated by NocoDb | Webhook Settings NocoDB Webhook Settings Data Flow The workflow handles data in the following sequence: Webhook Trigger: Receives input from NocoDB when a new keyword research request is created Field Extraction: Extracts primary topic, competitor URLs, audience, and other parameters AI Topic Expansion: Uses OpenAI to generate related keywords, categorized by type and intent Keyword Analysis: Sends primary keywords to DataForSEO to get search volume, CPC, and difficulty Competitor Research: Analyzes competitor pages to identify their keyword rankings Strategy Generation: Combines all data to create a comprehensive keyword strategy Storage & Notification: Saves the strategy to NocoDB and sends a notification to Slack Core Components 1. Topic Expansion This component uses OpenAI and a structured output parser to generate: 20 primary keywords 30 long-tail keywords with search intent 15 question-based keywords 10 related topics 2. DataForSEO Integration Two API endpoints are used: Search Volume & CPC**: Gets monthly search volume and cost-per-click data Keyword Difficulty**: Evaluates how difficult it would be to rank for each keyword 3. Competitor Analysis This component: Analyzes competitor URLs to identify which keywords they rank for Identifies content gaps or opportunities Determines the search intent their content targets 4. Final Keyword Strategy The AI-generated strategy includes: Top 10 primary keywords with metrics 15 long-tail opportunities with low competition 5 question-based keywords to address in content Content structure recommendations 3 potential content titles optimized for SEO Setup Requirements To use this workflow, you'll need: n8n Instance: Either cloud or self-hosted NocoDB Account: For data input and storage API Keys: OpenAI API key DataForSEO API credentials Slack API token (for notifications) Database Setup: Create the required tables in NocoDB as described above Possible Improvements The workflow could be enhanced with the following improvements: Enhanced Keyword Strategy Add topic clustering to group related keywords Enhance the final output with more specific content structure suggestions Include word count recommendations for each content section Additional Data Sources Integrate Google Search Console data for existing content optimization Add Google Trends data to identify rising topics Include sentiment analysis for different keyword groups Improved Competitor Analysis Analyze content length and structure from top-ranking pages Identify common backlink sources for competitor content Extract content headings to better understand content organization Automation Enhancements Add scheduling capabilities to run updates on existing content Implement content performance tracking over time Create alert thresholds for changes in keyword difficulty or search volume Example Output Here is an example Output the Workflow generated based on the following inputs. Inputs: Primary Topic: AI Automation Competitor URLs: n8n.io, zapier.com, make.com Target Audience: Small Business Owners Content Type: Landing Page Location: United States Language: English Output: Final Keyword Strategy The workflow provides a powerful automation for content marketers and SEO specialists to develop data-driven keyword strategies with minimal manual effort. > Original Workflow: AI-Powered SEO Keyword Research Automation - The vibe Marketer

Automatic lead enrichment in Slack: monitors your Slack channel for new lead emails posted there, extracts each company’s name or domain, sends it to the Extruct API for data enrichment, then posts back a structured Slack card with company name, website, LinkedIn profile, number of employees, industry, recent news, and key contacts. Who’s it for: Sales teams, SDRs, and marketing ops who capture new lead information in Slack and want instant enrichment without leaving the channel. How it works: When a lead email is posted into your designated Slack channel, the workflow: Monitors for any new message containing a company name or domain. Extracts that company identifier. Sends it to Extruct API for research. Waits for enrichment to complete. Posts back into the same Slack thread a formatted card with: Company name Website LinkedIn profile Number of employees Industry Recent news Key contacts How to set up: Sign up for Extruct AI Copy the Extruct table ID Create & install your Slack app Configure n8n credentials & channel Activate & use Requirements: Extruct account & API token Extruct table template Slack workspace with permission to install apps

Who is this for? This workflow is designed for n8n users and developers who need to automate the documentation process of their n8n workflows. It's particularly useful for teams looking to streamline their documentation efforts and ensure consistency across their workflow documentation. What problem is this workflow solving? / Use case The primary problem this workflow addresses is the manual and time-consuming process of creating documentation for n8n workflows. It automates the generation of concise, clear, and comprehensive documentation directly from the workflow's JSON, making it easier for both technical and non-technical users to understand what the workflow does and how it operates. What this workflow does Upon receiving a form submission with the workflow title and JSON, this workflow automatically generates documentation that includes: A brief introduction to the workflow. The trigger mechanism (webhook URLs for test and production environments, or cron schedules). Setup requirements, including necessary credentials and external dependencies. Setup Credentials Setup: Ensure you have OpenAI API credentials configured in n8n to use the GPT model for generating documentation text. Form Submission: Users must submit the form with the workflow title and JSON. The form is accessible via: Test URL: domain/form-test/{webhookId} Production URL: domain/form/{webhookId} How to customize this workflow to your needs Modify Trigger URLs**: Adjust the webhook or form URLs based on your domain and specific n8n setup. Customize Documentation Template**: Edit the OpenAI node's prompt to change the structure or details of the generated documentation. Extend Functionality**: Add nodes to integrate with other systems (e.g., automatically publishing the documentation to a wiki or sending it via email). This workflow simplifies the documentation process, making it accessible and manageable for teams of all sizes and technical abilities. By automating documentation, it ensures that all workflows are properly documented, enhancing understanding and efficiency within teams.

Fetches workflow definitions from within n8n, selecting only the ones that have one or more (configurable) assigned tags and then: Derives a suitable backup filename by reducing the workflow name to a string with alphanumeric characters and no-spaces Note: This isn't bulletproof, but works as long as workflow names aren't too crazy. Determines which workflows need to be backed up based on whether each one: has been modified. (Note: Even repositioning a node counts.) ...or... is new. (Note: Renaming counts as this.) Commits JSON copies of each workflow, as necessary, to a Gitlab repository with a generated, date-stamped commit message. Setup Credentials Create a Gitlab Credentials item and assign it to all Gitlab nodes. Create an n8n Credentials item and assign it to the n8n node Note: This was tested with http://localhost:5678/api/v1 but should work with any reachable n8n instance and API key. Modify these values in the "Globals" Node gitlab_owner - {{your gitlab account}} gitlab_project - {{ your gitlab project name }} gitlab_workflow_path - {{ subdirectory in the project where backup files should be saved/committed }} tags_to_match_for_backup - {{tag(s) to match for backup selection}} *ALERT: According to the n8n node's Filters -> tags field annotations, and API documentation, this supports a CSV list of multiple tags (e.g. tag1,tag2), but the API behavior requires workflows to have all-of the listed tags, not any-of them.* See: https://github.com/n8n-io/n8n/issues/10348 TL/DR - Don't expect a multiple tag list to be more inclusive. Possible workaround: To match more than one tag value, duplicate the n8n node into multiple single-tag matches, or split and iterate multiple values, and merge the results. Possible Enhancements Make the branch ("Reference") for all the gitlab nodes configurable. Fixed on all as "main" in the template. Add an n8n node to generate an audit and store the output in gitlab along with the backups. Extend the workflow at the end to create a Gitlab release/tag whenever any backup files are actually updated or created.

This n8n template demonstrates how you can automate community moderation using human-in-the-loop functionality for Discord. The use-case is for detecting and dealing with spam messages in a predefined and consistent way. Human-in-the-loop allows for a balance between overly aggressive bots and time and effort from the moderation team. How it works A scheduled trigger is used to scan the most recent messages in a Discord Channel. Messages are tagged via the "Remove Duplicates" node so they don't get processed again in the future. Messages are grouped by user to allow for minimising of number of notifications sent. An AI text classifier node is then used to detect for spam in each user's message. When detected, a notification is sent to a moderation channel using the Send-and-wait mode for Discord. This notification comes with an n8n form and dropdown list of predefined actions to take in dealing with the spam messages. Once sent the workflow waits until a response is received. Once a moderator selects an action, the workflow continues and carries out a predefined moderation action. How to use Depending on how busy your community is and subject to spammers, you may need to increase the scheduled interval. Add as many or few moderation actions as required. Remember to activate the workflow to get it started. Requirements Discord channel for messages to moderate OpenAI for text classification Customising this template It is possible to cover multiple channels. Add as many as your community needs. Not using Discord. The template can also work in slack or other services which offer the same bot functionality.

🎥 Bulk TikTok Video Download Without Watermark to Google Drive This workflow automates the process of downloading TikTok videos and uploading them to Google Drive. It reads TikTok URLs from a Google Sheet, downloads the video using the TikTok Video Downloader — a tool for downloading TikTok videos without watermark in HD quality — uploads it to Drive, makes it public, and updates the same sheet with the Drive link. 🔧 What It Does ✅ Manually triggered when ready to run. 📄 Reads TikTok URLs from a Google Sheet. 🔁 Loops through each URL one at a time. 🌐 Fetches video download links using the TikTok Video Downloader — a reliable TikTok video downloader without watermark. ⬇️ Downloads each video in high-definition (HD) format using the direct media link. ☁️ Uploads the video to Google Drive. 🔓 Sets public sharing permission for the video. ✏️ Updates the original Google Sheet with the public Drive URL. 📋 Google Sheet Example Make sure your sheet has at least these columns: | url | drive_link (to be auto-filled) | |-------------------------------------|--------------------------------| | https://www.tiktok.com/@user1... | (blank initially) | | https://www.tiktok.com/@user2... | (blank initially) | > The workflow reads from url and fills in drive_link after upload. 🧩 Nodes Used | Node Name | Type | Purpose | |------------------------------|-------------------|-------------------------------------------------------| | When clicking ‘Execute’ | Manual Trigger | Starts the workflow manually | | Get Data From Google Sheets | Google Sheets | Fetches rows (TikTok URLs) | | Loop Over Items | Split In Batches | Iterates over each row | | Call TikTok Downloader | HTTP Request | Gets video download link from TikTok Video Downloader | | Wait | Wait | Optional delay to prevent overload | | Download File | HTTP Request | Downloads HD video using media link | | Upload File In Google Drive | Google Drive | Uploads the video to Google Drive | | Set Public Permission | Google Drive | Makes the uploaded file publicly accessible | | Update Row In Google Sheet | Google Sheets | Adds Drive link to the same row | | Sleep | Wait | Small delay between each iteration | 📝 Requirements ✅ Google API credentials (Service Account) with access to: Google Sheets Google Drive 🔐 RapidAPI Key for TikTok Video Downloader – a TikTok video downloader without watermark (HD supported) 🗂 A Google Sheet with a url column containing TikTok video URLs 🧩 Challenges Solved | ❗ Challenge | ✅ Solution | |-------------|-------------| | TikTok video URLs often have watermarks and low quality | Used TikTok Video Downloader API for HD + no watermark download links | | No easy way to bulk download and organize TikToks | Automated fetching, downloading, and uploading using n8n + Google Drive | | Manual video saving and re-uploading to Drive is time-consuming | Eliminated all manual steps with a fully automated workflow | | Tracking which videos are already processed | Automatically updates the Google Sheet row with the final Drive link | | Drive files are private by default | Automatically sets public sharing permission on uploaded videos | | Risk of API rate limits or throttling | Added Wait nodes and batch processing to avoid overload | 🎁 Benefits | 🌟 Benefit | 💬 Description | |------------|----------------| | 🚀 Saves Time | Fully automates a previously manual workflow | | 🎥 High Quality Content | Videos downloaded are HD + watermark-free — ready for reuse or archives | | 🔁 Reusable Setup | Can process unlimited TikTok URLs via the Google Sheet | | 📊 Organized Output | Keeps track of source URL and uploaded Drive link in a single sheet | | 🔐 Secure but Shareable | Drive links are auto-shared publicly while remaining under your control | | 🔄 Scalable | Can be run daily, weekly, or triggered by new rows — completely scalable | | 💸 Cost-Effective | No need for paid tools or manual freelancers — runs on n8n + free APIs | 💡 Use Cases Content curation from TikTok Archiving user-submitted TikToks Automating social-to-cloud workflows Bulk migration of video content Saving TikTok videos in HD without watermark for sharing or archiving 📌 Tips Replace manual trigger with Cron for full automation. Use the TikTok Video Downloader responsibly — check API limits. Store metadata (e.g., uploader, hashtags) in additional Google Sheet columns. This tool helps ensure you're always downloading high-quality TikTok videos without watermark.