Clone viral TikToks with AI avatars & auto-post to 9 platforms using Perplexity & Blotato
Clone a viral TikTok with AI and auto-post it to 9 platforms using Perplexity & Blotato Who is this for? This workflow is perfect for: Content creators looking to repurpose viral content Social media managers who want to scale short-form content across multiple platforms Entrepreneurs and marketers aiming to save time and boost visibility with AI-powered automation What problem is this workflow solving? Reproducing viral video formats with your own branding and pushing them to multiple platforms is time-consuming and hard to scale. This workflow solves that by: Cloning a viral TikTok videoโs structure Generating a new version with your avatar Rewriting the script, caption, and overlay text Auto-posting it to 9 social media platforms โ without manual uploads What this workflow does From a simple Telegram message with a TikTok link, the workflow: Downloads a TikTok video and extracts its thumbnail, audio, and caption Transcribes the audio and saves original text into Google Sheets Uses Perplexity AI to suggest a new content idea in the same niche Rewrites the script, caption, and overlay using GPT-4o Generates a new video with your avatar using Captions.ai Adds subtitles and overlay text with JSON2Video Saves metadata to Google Sheets for tracking Sends the final video to Telegram for preview Auto-publishes the video to Instagram, YouTube, TikTok, Facebook, LinkedIn, Threads, X (Twitter), Pinterest, and Bluesky via Blotato Setup Connect your Telegram bot to the trigger node. Add your OpenAI, Perplexity, Cloudinary, Captions.ai, and Blotato API keys. Make sure your Google Sheet is ready with the appropriate columns. Replace the default avatar name in the Captions.ai node with yours. Fill in your social media account IDs in the "Assign Platform IDs" node. Test by sending a TikTok URL to your Telegram bot. How to customize this workflow to your needs Change avatar output style: adjust resolution, voice, or avatar ID. Refine script structure: tweak GPT instructions for different tone/format. Swap Perplexity with ChatGPT or Claude if needed. Filter by platform: disable any Blotato nodes you donโt need. Add approval step: insert a Telegram confirmation node before publishing. Adjust subtitle style or overlay text font in JSON2Video. ๐ Documentation: Notion Guide --- Need help customizing? Contact me for consulting and support : Linkedin / Youtube
By Dr. FirasBuild your own N8N workflows MCP server
This n8n template shows you how to create an MCP server out of your existing n8n workflows. With this, any MCP client connected can get more done with powerful end-to-end workflows rather than just simple tools. Designing agent tools for outcome rather than utility has been a long recommended practice of mine and it applies well when it comes to building MCP servers; In gist, agents to be making the least amount of calls possible to complete a task. This is why n8n can be a great fit for MCP servers! This template connects your agent/MCP client (like Claude Desktop) to your existing workflows by allowing the AI to discover, manage and run these workflows indirectly. How it works An MCP trigger is used and attaches 4 custom workflow tools to discover and manage existing workflows to use and 1 custom workflow tool to execute them. We'll introduce an idea of "available" workflows which the agent is allowed to use. This will help limit and avoid some issues when trying to use every workflow such as clashes or non-production. The n8n node is a core node which taps into your n8n instance API and is able to retrieve all workflows or filter by tag. For our example, we've tagged the workflows we want to use with "mcp" and these are exposed through the tool "search workflows". Redis is used as our main memory for keeping track of which workflows are "available". The tools we have are "add Workflow", "remove workflow" and "list workflows". The agent should be able to manage this autonomously. Our approach to allow the agent to execute workflows is to use the Subworkflow trigger. The tricky part is figuring out the input schema for each but was eventually solved by pulling this information out of the workflow's template JSON and adding it as part of the "available" workflow's description. To pass parameters through the Subworkflow trigger, we can do so via the passthrough method - which is that incoming data is used when parameters are not explicitly set within the node. When running, the agent will not see the "available" workflows immediately but will need to discover them via "list" and "search". The human will need to make the agent aware that these workflows will be preferred when answering queries or completing tasks. How to use First, decide which workflows will be made visible to the MCP server. This example uses the tag of "mcp" but you can all workflows or filter in other ways. Next, ensure these workflows have Subworkflow triggers with input schema set. This is how the MCP server will run them. Set the MCP server to "active" which turns on production mode and makes available to production URL. Use this production URL in your MCP client. For Claude Desktop, see the instructions here - https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-langchain.mcptrigger/integrating-with-claude-desktop. There is a small learning curve which will shape how you communicate with this MCP server so be patient and test. The MCP server will work better if there is a focused goal in mind ie. Research and report, rather than just a collection of unrelated tools. Requirements N8N API key to filter for selected workflows. N8N workflows with Subworkflow triggers! Redis for memory and tracking the "available" workflows. MCP Client or Agent for usage such as Claude Desktop - https://claude.ai/download Customising this workflow If your targeted workflows do not use the subworkflow trigger, it is possible to amend the executeTool to use HTTP requests for webhooks. Managing available workflows helps if you have many workflows where some may be too similar for the agent. If this isn't a problem for you however, feel free to remove the concept of "available" and let the agent discover and use all workflows!
By JimleukScrape any web page into structured JSON data with ScrapeNinja and AI
Disclaimer: This template only works on self-hosted for now, as it uses a community node. Use Case Web scrapers often break due to web page layout changes. This workflow attempts to mitigate this problem by auto-generating web scraping data extractor code via LLM. How It Works This workflow leverages ScrapeNinja n8n community node to: scrape webpage HTML, feed it into LLM (Google Gemini) and ask to write a JS extractor function code, then it executes the written JS extractor against scraped HTML to extract useful data from webpage (the code is safely executed in a sandbox) Installation To install ScrapeNinja n8n node, in your self-hosted instance, go to Settings -> Community nodes, enter "n8n-nodes-scrapeninja", and install. Make sure you are using at least v0.3.0. See this in action: https://www.linkedin.com/feed/update/urn:li:activity:7289659870935490560/
By Anthony๐ค๐ง AI agent chatbot + LONG TERM memory + note storage + Telegram
This workflow template creates an AI agent chatbot with long-term memory and note storage using Google Docs and Telegram integration. Google Docs Integration ๐ n8n Google Docs Node Setup Google Credentials Telegram Integration ๐ฌ Telegram Setup Core Features ๐ AI Agent Integration ๐ค Implements a sophisticated AI agent with memory management capabilities Uses GPT-4o-mini and DeepSeek models for intelligent conversation handling Maintains context awareness through session management Memory System ๐ง Long-term memory storage using Google Docs Separate note storage system for specific information Window buffer memory for maintaining conversation context Intelligent memory retrieval and storage mechanisms Communication Interface ๐ฌ Telegram integration for message handling Real-time message processing and response generation Technical Components ๐ง Memory Architecture ๐ Dual storage system separating memories from notes Automated memory retrieval before each interaction Structured memory saving with timestamps AI Models ๐ค Primary GPT-4o-mini mini model for general interactions DeepSeek-V3 Chat for specialized processing Custom agent system with tool integration Storage Integration ๐พ Google Docs integration for persistent storage Separate document management for memories and notes Automated document updates and retrievals
By Joseph LePage๐ Learn n8n expressions with an interactive step-by-step tutorial for beginners
How it works This template is an interactive, step-by-step tutorial designed to teach you the most important skill in n8n: using expressions to access and manipulate data. If you know what JSON is but aren't sure how to pull a specific piece of information from one node and use it in another, this workflow is for you. It starts with a single "Source Data" node that acts as our filing cabinet, and then walks you through a series of lessons, each demonstrating a new technique for retrieving and transforming that data. You will learn how to: Access a simple value from a previous node. Use n8n's built-in selectors like .last() and .first(). Get a specific item from a list (Array). Drill down into nested data (Objects). Combine these techniques to access data in an array of objects. Go beyond simple retrieval by using JavaScript functions to do math or change text. Inspect data with utility functions like Object.keys() and JSON.stringify(). Summarize data from multiple items using .all() and arrow functions. Set up steps Setup time: 0 minutes! This workflow is a self-contained tutorial and requires no setup or external credentials. Click "Execute Workflow" to run the entire tutorial. Follow the flow from the "Source Data" node to the "Final Exam" node. For each lesson, click on the node to see how its expressions are configured in the parameters panel. Read the detailed sticky note next to each lessonโit breaks down exactly how the expression works and why. By the end, you'll have the foundational knowledge to connect data and build powerful, dynamic workflows in n8n.
By Lucas PeyrinAI agent for Instagram DM/inbox. Manychat + Open AI integration
Automate Instagram DMs with OpenAI GPT and ManyChat How It Works: Once connected, GPT will automatically initiate conversations with messages from new recipients in Intagram. Who Is This For? This workflow is ideal for marketers, business owners content creators who want to automatically respond to Instagram direct messages using OpenAI GPT. By integrating ManyChat, you can manage conversations, nurture leads, and provide instant replies at scale. What This Workflow Does Captures incoming Instagram DMs through ManyChatโs integration. Processes messages with GPT to generate a relevant response. Delivers instant replies back to Instagram users, creating efficient, AI-driven communication. Setup Import the Template: Copy the n8n workflow into your workspace. OpenAI Credentials: Add your OpenAI API key in n8n so GPT can generate responses. ManyChat Account: Create (or log in to) your ManyChat account. Connect Instagram: Link your Instagram profile as a channel in ManyChat. ManyChat Custom Field: Create a custom field for storing user input or conversation context. Configure Default Reply: In ManyChat, set up the default Instagram reply flow to point to your n8n webhook. Add External Request: Create an external request step in ManyChat to send messages to n8n. Test the Flow: Send yourself a DM on Instagram to confirm the workflow triggers and GPT responds correctly. Instructions and links: Notion instruction Register in ManyChat
By Alex Hi no codeDiscord AI-powered bot
This workflow is a template example for making Discord GPT-powered bots. Incoming user requests are analysed and categorised via OpenAI node with the help of a hand-crafted prompt. The response message is then routed to a different Discord channel.
By EduardERP AI chatbot for Odoo sales module with OpenAI
Who is this for? This workflow is for everyone who wants to have easier access to their Odoo sales data without complex queries. Use Case To have a clear overview of your sales data in Odoo you typically needs to extract data from it manually to analyse it. This workflow uses OpenAI's language models to create an intelligent chatbot that provides conversational access to your Odoo sales opportunity data. How it works Creates a summary of all Odoo sales opportunities using OpenAI Uses that summary as context for the OpenAI chat model Keeps the summary up to date using a schedule trigger Set up steps: Configure the Odoo credentials Configure OpenAI credentials Toggle "Make Chat Publicly Available" from the Chat Trigger node.
By Mihai FarcasGoogle Maps business scraper with contact extraction via Apify and Firecrawl
Who is this for? Marketing agencies, sales teams, lead generation specialists, and business development professionals who need to build comprehensive business databases with contact information for outreach campaigns across any industry. What problem is this workflow solving? Finding businesses and their contact details manually is time-consuming and inefficient. This workflow automates the entire process of discovering businesses through Google Maps and extracting their digital contact information from websites, saving hours of manual research. What this workflow does This automated workflow runs every 30 minutes to: Scrape business data from Google Maps using Apify's Google Places crawler Save basic business information (name, address, phone, website) to Google Sheets Filter businesses that have websites Scrape each business's website content using Firecrawl Extract contact information including emails, LinkedIn, Facebook, Instagram, and Twitter profiles Store all extracted data in organized Google Sheets for easy access and follow-up Setup Required Services: Google Sheets account with OAuth2 setup Apify account with API access for Google Places scraping Firecrawl account with API access for website scraping Pre-setup: Copy this Google Sheet Configure your Apify and Firecrawl API credentials in n8n Set up Google Sheets OAuth2 connection Update the Google Sheet ID in all Google Sheets nodes Quick Start: The workflow includes detailed sticky notes explaining each phase. Simply configure your API credentials and Google Sheet, then activate the workflow. How to customize this workflow to your needs Change search criteria: Modify the Apify scraping parameters to target different business types (restaurants, gyms, salons, etc.) or locations Adjust schedule: Change the trigger interval from 30 minutes to your preferred frequency Add more contact fields: Extend the extraction code to find additional contact information like WhatsApp or Telegram Filter criteria: Modify the filter conditions to target businesses with specific characteristics Batch size: Adjust the batch processing to handle more or fewer websites simultaneously Perfect for lead generation, competitor research, and building targeted marketing lists across any industry or business type.
By Naveen ChoudharyGenerate AI-Powered LinkedIn Posts with Google Gemini and Gen-Imager
๐ AI-Powered LinkedIn Post Automation --- ๐งฉ How It Works This workflow automatically generates LinkedIn posts based on a user-submitted topic, including both content creation and image generation, then publishes the post to LinkedIn. Ideal for marketers, content creators, or businesses looking to streamline their social media activity, without the need for manual post creation. High-Level Workflow: Trigger: The workflow is triggered when a user submits a form with a topic for the LinkedIn post. Data Mapping: The topic is mapped and prepared for the AI model. AI Content Generation: Calls the Google Gemini AI model to generate engaging post content and a visual image prompt. Image Creation: Sends the image prompt to the external API, gen-imager, to generate a professional image matching the topic. Post Creation: Publishes the text and image to LinkedIn, automatically updating the user's feed. --- โ๏ธ Set Up Steps (Quick Overview) ๐ Estimated Setup Time: ~10โ20 minutes Connect Google Gemini: Set up your Google Gemini API credentials to interact with the AI model for content creation. Set Up External Image API: Configure the external image generation API (gen-imager API) for visual creation based on the post prompt. Connect LinkedIn: Set up OAuth2 credentials to authenticate your LinkedIn account and allow publishing posts. Form Submission Setup: Create a simple web form for users to submit the topic for LinkedIn posts. Activate the Workflow: Once everything is connected, activate the workflow. It will trigger automatically upon receiving form submissions. ๐ก Important Notes: The flow uses Google Gemini (PaLM) for generating content based on the user's topic. Text to Image: The image generation process involves creating a professional, LinkedIn-appropriate image based on the postโs topic using the gen-imager API. You can customize the visual elements of the posts and adjust the tone of the generated content based on preferences. --- ๐ Detailed Node Breakdown: On Form Submission Trigger: Captures the user-submitted topic and initializes the workflow. Action: Start the process by gathering the topic information. Mapper (Field Mapping) Action: Maps the captured topic to a variable that is passed along for content generation. AI Agent (Content Generation) Action: Calls Google Gemini to generate professional LinkedIn post content and an image prompt based on the submitted topic. Key: Outputs content in a structured form โ post text and image prompt. Google Gemini Chat Model Action: AI model that generates actionable insights, engaging copy, and an image prompt for LinkedIn post. Normalizer (Data Cleanup) Action: Cleans the output from the AI model to ensure the content and image prompt are correctly formatted for use in the next steps. Text to Image (Image Generation) Action: Sends the image prompt to the gen-imager API, which returns a custom image based on the post's topic. Decoder (Base64 Decoding) Action: Decodes the image from base64 format for easier uploading to LinkedIn. LinkedIn (Post Creation) Action: Publishes the generated text and image to LinkedIn, automatically creating a polished post for the userโs feed. --- โฑ Execution Time Breakdown: Total Estimated Execution Time: ~15โ40 seconds per workflow run. On Form Submission: Instant (Trigger) Mapper (Field Mapping): ~1โ2 seconds AI Content Generation: ~5โ10 seconds (depending on server load) Text to Image: ~5โ15 seconds (depends on external API) LinkedIn Post Creation: ~2โ5 seconds --- ๐ Ready to Get Started? Letโs get you started with automating your LinkedIn posts! Create your free n8n account and set up the workflow using this link. --- ๐ Notes & Customizations Form Fields: Customize the form to gather more specific information for the LinkedIn posts (like audience targeting, post category, etc.). Image API Customization: Adjust the image generation prompt to fit your brandโs style, or change the color palette as needed. Content Tone: The tone can be adjusted by modifying the system message sent to Google Gemini for content generation. ---
By Evoort SolutionsAI Timesheet Generator with Gmail, Calendar & GitHub to Google Sheets
AI-Powered Automatic Timesheet Generator for Google Sheets Stop wasting billable hours on manual time-tracking. AutoTimesheet Pro uses AI to collect emails, meetings, and GitHub work, then writes a clean timesheet straight into Google Sheets. Perfect for developers, consultants, agencies, and remote teams. Get Started with n8n now! --- ๐ Key Features Automated Google Sheets time-tracking โ zero spreadsheet prep. AI-generated activity summaries (โค 120 chars) via OpenAI GPT-4o-mini. Gmail integration โ logs only important emails, skipping newsletters & no-replies. Google Calendar time logger โ captures confirmed events, duration, and attendees. GitHub commit & PR tracker โ records your commits plus opened/closed PRs. Daily 7 PM cron trigger (easily adjustable). Month-based sheet creation โ new tab spins up on the first run each month. No-code n8n template โ just connect credentials and tweak one Set Variables node. ๐ Easily extensible โ drag-and-drop extra n8n nodes to add Slack, Jira, Notion, Asana, Trello, Toggl, or any other data source you need. --- ๐ How It Works Collect โ n8n pulls data from Gmail, Google Calendar, and chosen GitHub repos. Clean โ filters remove noise (newsletters, irrelevant commits, etc.). Condense โ OpenAI rewrites each item into a concise, SEO-friendly description. Write โ workflow appends Date, Type, and Description to your Timesheet Google Sheet. Extend โ simply insert new n8n nodes (e.g., Slack, Notion, Jira) and merge them into the same pipeline. --- ๐ Benefits for SEO-Minded Professionals Keyword-rich activity log improves internal search and reporting. Structured data in Sheets simplifies export to accounting or PM tools. Consistent naming (CALENDAR_EVENT, EMAIL, COMMIT, PR) makes analytics easy. --- โ Why Choose AutoTimesheet Pro? Zero manual entry โ just open the sheet and bill clients. Immediate visibility into where your hours went. Works with any GitHub repo list and any inbox you own. 100 % no-code setup โ activate in minutes. Built on n8n, so you can customize and scale without limits. --- ๐ฅ Get Started Ready to replace manual time-tracking with smart automation? https://n8n.partnerlinks.io/ds9podzjls6d Join N8N now, connect your Google & GitHub accounts, and let AI handle your daily log. ---
By Luka Zivkovicโก๐ฝ๏ธ Ultimate AI-powered chatbot for YouTube summarization & analysis
๐ฅ YouTube Video AI Agent Workflow This n8n workflow template allows you to interact with an AI agent that extracts details and the transcript of a YouTube video using a provided video ID. Once the details and transcript are retrieved, you can chat with the AI agent to explore or analyze the video's content in a conversational and insightful manner. ๐ How the Workflow Works ๐ Input Video ID: The user provides a YouTube video ID as input to the workflow. ๐ Data Retrieval: The workflow fetches essential details about the video (e.g., title, description, upload date) and retrieves its transcript using YouTube's Data API and additional tools for transcript extraction. ๐ค AI Agent Interaction: The extracted details and transcript are processed by an AI-powered agent. Users can then ask questions or engage in a conversation with the agent about the video's content, such as: Summarizing the transcript. Analyzing key points. Clarifying specific sections. ๐ฌ Dynamic Responses: The AI agent uses natural language processing (NLP) to generate contextual and accurate responses based on the video data, ensuring a smooth and intuitive interaction. --- ๐ Use Cases ๐ Content Analysis: Quickly analyze long YouTube videos by querying specific sections or extracting summaries. ๐ Research and Learning: Gain insights from educational videos or tutorials without watching them entirely. โ๏ธ Content Creation: Repurpose transcripts into blogs, social media posts, or other formats efficiently. โฟ Accessibility: Provide an alternative, text-based way to interact with video content for users who prefer reading over watching. --- ๐ ๏ธ Resources for Getting Started Google Cloud Console (for API setup): Visit Google Cloud's Get Started Guide to configure your API access. YouTube Data API Key Setup: Follow this guide to create and manage your YouTube Data API key. Install n8n Locally: Refer to this installation guide for setting up n8n on your local machine. --- โจ Sample Prompts "Tell me about this YouTube video with id: JWfNLF_g_V0" "Can you provide a list of key takeaways from this video with id: [youtube-video-id]?"
By Joseph LePage