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Load and summarize Google Drive files with AI

This workflow includes advanced features like text summarization and tokenization, it's ideal for automating document processing tasks that require parsing and summarizing text data from Google Drive. To use this template, you need to be on n8n version 1.19.4 or later.

n8n TeamBy n8n Team
33617

Update HubSpot when a new invoice is registered in Stripe

This workflow automatically posts a message in Slack when a new invoice is uploaded in Stripe, and it updates the fields in the HubSpot CRM. Prerequisites A Slack account and credentials A HubSpot account and credentials A Stripe account and credentials Nodes Stripe Trigger node triggers the workflow when a new invoice is uploaded. IF nodes filter the invoices that don't have a PO number and if there is no deal for the PO. HubSpot nodes retrieve deals with the specific PO number and update the deal status to 'paid'. Slack nodes post messages about the deals in a Slack channel.

JonathanBy Jonathan
6276

🤖🧑‍💻 AI agent for top n8n creators leaderboard reporting

This n8n workflow is designed to automate the aggregation, processing, and reporting of community statistics related to n8n creators and workflows. Its primary purpose is to generate insightful reports that highlight top contributors, popular workflows, and key trends within the n8n ecosystem. Here's how it works and why it's important: How It Works Data Retrieval: The workflow fetches JSON data files from a GitHub repository containing statistics about creators and workflows. It uses HTTP requests to access these files dynamically based on pre-defined global variables. Data Processing: The data is parsed into separate streams for creators and workflows. It processes the data to identify key metrics such as unique weekly and monthly inserters/visitors. Ranking and Filtering: The workflow sorts creators by their weekly inserts and workflows by their popularity. It selects the top 10 creators and top 50 workflows for detailed analysis. Report Generation: Using AI tools like GPT-4 or Google Gemini, the workflow generates a Markdown report summarizing trends, contributors, and workflow statistics. The report includes tables with detailed metrics (e.g., unique visitors, inserters) and insights into why certain workflows are popular. Distribution: The report is saved locally or uploaded to Google Drive. It can also be shared via email or Telegram for broader accessibility. Automation: A schedule trigger ensures the workflow runs daily or as needed, keeping the reports up-to-date. Why It's Important Community Insights: This workflow provides actionable insights into the n8n community by identifying impactful contributors and popular workflows. This fosters collaboration and innovation within the ecosystem. Time Efficiency: By automating data collection, processing, and reporting, it saves significant time and effort for community managers or administrators. Recognition of Contributors: Highlighting top creators encourages engagement and recognizes individuals driving value in the community. Trend Analysis: The workflow helps uncover patterns in usage, enabling better decision-making for platform improvements or feature prioritization. Scalability: With its modular design, this workflow can be easily adapted to include additional metrics or integrate with other tools.

Joseph LePageBy Joseph LePage
4776

Viral ASMR video factory: Automatically generate viral videos on autopilot.

🚀 Overview This automation is a complete content creation engine for your social media. It endlessly designs, generates, and organizes unique and oddly satisfying ASMR videos, ensuring you always have fresh, viral-style content ready to post on platforms like TikTok, YouTube Shorts, and Instagram Reels. Video Examples 😩 The Problem Consistently creating viral content is exhausting. You're constantly battling creative burnout, trying to come up with new ideas that are fresh and engaging. For every video, you have to brainstorm an idea, write a detailed prompt for an AI generator, wait for the video, and then manually track what you've already posted. This manual process is slow, repetitive, and a major roadblock to scaling your content output. ✨ The Solution This workflow acts as your personal, automated content creation employee. When you trigger it, the automation first checks a Google Sheet to see what videos it has already made. Then, a built-in "Idea Agent" cleverly brainstorms a brand new, unused concept (like a "glass banana" or "glass pomegranate"). Next, it passes this idea to a "Prompt Agent," which writes a perfectly detailed, sensory-rich script designed to produce a stunning, hyper-realistic video. The script is sent to an AI video generator, and the workflow waits patiently for it to finish. Once the video is ready, the automation saves the final video link neatly into your Google Sheet and cleans up the oldest entry, creating a self-sustaining content machine. ⚙️ Simple Setup This workflow is a pre-built blueprint, designed to be up and running in minutes! Upload: Simply upload the provided JSON file into your n8n instance. Connect: Connect your app credentials (e.g., your Google, OpenAI, and Fal accounts). The workflow will show you exactly where. Activate: Turn the workflow on, and it's ready to go! Let your new automated employee get to work. --- 🌐 Explore more workflows ❤️ Buy more workflows at: adamcrafts 🦾 Custom workflows at: adamcrafts@cloudysoftwares.com adamaicrafts@gmail.com > Build once, customize endlessly, and scale your video content like never before.

Abdellah HomraniBy Abdellah Homrani
3341

Generate complete business plans with customizable AI models and specialized agents

👔 Who is this for? Entrepreneurs and startup founders preparing for investors Business consultants drafting complete client plans Strategy teams building long-term business models Accelerators, incubators, or pitch trainers ❓ What problem does this workflow solve? Writing a full business plan takes days of work, multiple tools, and often gets stuck in messy docs or slides. This template automates every major section, generating a clean, detailed, and professional business plan with AI in just minutes. ⚙️ What this workflow does Starts with a chat message asking for your business idea or startup concept Passes the idea through 83 intelligent agents, each handling a full business plan chapter: Executive Summary Problem & Solution Product Description Market Research Competitor Analysis Business Model Marketing Strategy (includes guerrilla ideas) Operational Plan Financial Plan Team & Advisors Roadmap Conclusion & Next Steps Each section uses tailored prompts and business logic Combines all outputs into a structured, professional Markdown file Final result: a ready-to-export business plan in seconds 🛠️ Setup Import this template into your n8n instance Replace the “LLM Chat Model” node with your preferred model (Ollama, GPT-4, etc.) Start from the chat input node — describe your startup or idea Wait for all agents to finish Download the final Business plan file 🤖 LLM Flexibility (Choose Your Model) Supports: OpenAI (GPT-4 / GPT-3.5) Ollama (LLaMA 3.1, Mistral, DeepSeek, etc.) Any compatible N8N chat model To change the model, just replace the “Language Model” node — no other updates required 📌 Notes All nodes are clearly named by function (e.g., “Market Research Generator”) Sticky notes included for clarity Generates high-quality plans suitable for VCs or accelerators Modular: you can turn off or reorder any chapter 📩 Need help? Email: sinamirshafiee@gmail.com Happy to support setup, LLM switching, or custom section development.

SinaBy Sina
3069

Build your own Qdrant vector store MCP server

This n8n demonstrates how to build your own Qdrant MCP server to extend its functionality beyond that of the official implementation. This n8n implementation exposes other cool API features from Qdrant such as facet search, grouped search and recommendations APIs. With this, we can build an easily customisable and maintainable Qdrant MCP server for business intelligence. This MCP example is based off an official MCP reference implementation which can be found here - https://github.com/qdrant/mcp-server-qdrant How it works A MCP server trigger is used and connected to 5 custom workflow tools. We're using custom workflow tools as there is quite a few nodes required for each task. We use a mix of n8n supported Qdrant nodes for simple operations such as insert documents and similarity search, and HTTP node to hit the Qdrant API directly for Facet search, group search and recommendations. We use "Edit Field" and "Aggregate" nodes to return suitable responses to the MCP client. How to use This Qdrant MCP server allows any compatible MCP client to manage a Qdrant Collection by supporting select and create operations. You will need to have a collection available before you can use this server. Use the Prerequisite manual steps to get started! Connect your MCP client by following the n8n guidelines here - https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-langchain.mcptrigger/integrating-with-claude-desktop Try the following queries in your MCP client: "Can you help me list the available companies in the collection?" "What do customers say about product deliveries from company X?" "What do customers of company X and company Y say about product ease of use?" Requirements Qdrant for vector store. This can be an a cloud-hosted instance or one you can self-host internally. MCP Client or Agent for usage such as Claude Desktop - https://claude.ai/download Customising this workflow Depending on what queries you'll receive, adjust the tool inputs to make it easier for the agent to set the right parameters. Not interested in Reviews? The techniques shared in this template can be used for other types of collections. Remember to set the MCP server to require credentials before going to production and sharing this MCP server with others!

JimleukBy Jimleuk
2941

Categorize and label existing Gmail emails automatically with GPT-4o mini

📨 Categorize and Label Existing Gmail Emails Automatically with GPT-4o mini 👥 Who's it for This workflow is perfect for individuals or teams who want to sort and label existing emails in their Gmail inbox 🗃️ using AI. Ideal for cleaning up unlabeled emails in bulk — no coding required! For sorting incoming emails messages in your gmail inbox, please use this free workflow: Categorize and Label Incoming Gmail Emails Automatically with GPT-4o mini 🤖 What it does It manually processes a selected number of existing Gmail emails, skips those that already have labels, sends the content to an AI Agent powered by GPT-4o mini 🧠, and applies a relevant Gmail label based on the email content. All labels must already exist in Gmail. ⚙️ How it works ▶️ Manual Trigger – The workflow starts manually when you click "Execute Workflow". 📥 Gmail Get Many Messages – Pulls a batch of existing inbox emails (default: 50). 🚫 Filter – Skips emails that already have one or more labels. 🧠 AI Agent (GPT-4o mini) – Analyzes the content and assigns a category. 🧾 Structured Output Parser – Converts the AI output into structured JSON. 🔀 Switch Node – Routes each email to the right label based on the AI result. 🏷️ Gmail Nodes – Apply the correct Gmail label to the email. 📋 Requirements Gmail account connected to n8n Gmail labels must be manually created in your inbox beforehand Labels must exactly match the category names defined in the AI prompt OpenAI credentials with GPT-4o mini access n8n's AI Agent & Structured Output Parser nodes 🛠️ How to set up In your Gmail account, create all the labels you want to use for categorizing emails Open the workflow and adjust the email fetch limit in the Gmail node (e.g., 50, 100) Confirm that the Filter skips emails that already have labels Define your categories in the AI Agent prompt — these must match the Gmail labels exactly In the Switch Node, create a condition for each label/category Ensure each Gmail Label Node applies the correct existing label Save the workflow and run it manually whenever you want to organize your inbox ✅ 🎨 How to customize the workflow Add or remove categories in the AI prompt & Switch Node Adjust the batch size of emails to process more or fewer per run Fine-tune the AI prompt to suit your inbox type (e.g., work, personal, client support)

Arlin PerezBy Arlin Perez
2599

Data analytics department with AI team: CDO & specialists using OpenAI O3

CDO Agent with Data Analytics Team Description Complete AI-powered data analytics department with a Chief Data Officer (CDO) agent orchestrating specialized data team members for comprehensive data science, business intelligence, and analytics operations. Overview This n8n workflow creates a comprehensive data analytics department using AI agents. The CDO agent analyzes data requests and delegates tasks to specialized agents for data science, business intelligence, data engineering, machine learning, data visualization, and data governance. Features Strategic CDO agent using OpenAI O3 for complex data strategy and decision-making Six specialized data analytics agents powered by GPT-4.1-mini for efficient execution Complete data analytics lifecycle coverage from collection to insights Automated data pipeline management and ETL processes Advanced machine learning model development and deployment Interactive data visualization and business intelligence reporting Comprehensive data governance and compliance frameworks Team Structure CDO Agent: Data strategy leadership and team delegation (O3 model) Data Scientist Agent: Statistical analysis, predictive modeling, machine learning algorithms Business Intelligence Analyst Agent: Business metrics, KPI tracking, performance dashboards Data Engineer Agent: Data pipelines, ETL processes, data warehousing, infrastructure Machine Learning Engineer Agent: ML model deployment, MLOps, model monitoring Data Visualization Specialist Agent: Interactive dashboards, data storytelling, visual analytics Data Governance Specialist Agent: Data quality, compliance, privacy, governance policies How to Use Import the workflow into your n8n instance Configure OpenAI API credentials for all chat models Deploy the webhook for chat interactions Send data analytics requests via chat (e.g., "Analyze customer churn patterns and create predictive models") The CDO will analyze and delegate to appropriate specialists Receive comprehensive data insights and deliverables Use Cases Predictive Analytics: Customer behavior analysis, sales forecasting, risk assessment Business Intelligence: KPI tracking, performance analysis, strategic business insights Data Engineering: Pipeline automation, data warehousing, real-time data processing Machine Learning: Model development, deployment, monitoring, and optimization Data Visualization: Interactive dashboards, executive reporting, data storytelling Data Governance: Quality assurance, compliance frameworks, data privacy protection Requirements n8n instance with LangChain nodes OpenAI API access (O3 for CDO, GPT-4.1-mini for specialists) Webhook capability for chat interactions Optional: Integration with data platforms and analytics tools Cost Optimization O3 model used only for strategic CDO decisions and complex data strategy GPT-4.1-mini provides 90% cost reduction for specialist data tasks Parallel processing enables simultaneous agent execution Template libraries reduce redundant analytics development work Integration Options Connect to data platforms (Snowflake, BigQuery, Redshift, Databricks) Integrate with BI tools (Tableau, Power BI, Looker, Grafana) Link to ML platforms (AWS SageMaker, Azure ML, Google AI Platform) Export to business applications and reporting systems --- Disclaimer: This workflow is provided as a building block for your automation needs. Please review and customize the agents, prompts, and connections according to your specific data analytics requirements and organizational structure. Contact & Resources Website: nofluff.online YouTube: @YaronBeen LinkedIn: Yaron Been Tags DataAnalytics DataScience BusinessIntelligence MachineLearning DataEngineering DataVisualization DataGovernance PredictiveAnalytics BigData DataDriven DataStrategy AnalyticsAutomation DataPipelines MLOps DataQuality BusinessMetrics KPITracking DataInsights AdvancedAnalytics n8n OpenAI MultiAgentSystem DataTeam AnalyticsWorkflow DataOperations

Yaron BeenBy Yaron Been
1334

Generate AI promo videos for products with GPT-4o, Fal.ai & human supervision

Generate AI video clips to promote products, services or events on social media. Use gotoHuman as an interface to control and supervise each step of the workflow to create content that's actually worth posting. How it works gotoHuman will show the workflow steps that need approval or input in its' inbox and notify you via email or Slack. We choose from different topics for our post suggested by AI We select the image style, a product to show, and review an AI-generated tag line We use Fal.ai to generate an image that serves as a reference image for our video clip. And we use Cloudinary to add an overlay for the tag line. We review the image in gotoHuman and can iterate on it by retrying or even changing the prompt. We review the video clip that's generated with Fal.ai based on the approved image and can, again, retry or reprompt. How to set up Most importantly, install the gotoHuman node before importing this template! (Just add the node to a blank canvas before importing) Follow the instructions shown along the workflow and in the incl. video guide. You mainly need to set up your credentials for gotoHuman, OpenAI, Fal.ai and Cloudinary in gotoHuman, select and create the pre-built review template "Promo video agent" or import these IDs: Z7V1jyImY1pho9eY039R,0GBaOCWd27tqV562kkCL,E2wlCVPWmk2UnLHVt4uu,DitPdbIapS4rBxBTIYGt,Z2T7nFwkXVFQlD6z50eV select these templates in the gotoHuman nodes do a quick setup for Cloudinary Requirements You need accounts for gotoHuman (human supervision) OpenAI (ideation) Fal.ai (image/video generation) Cloudinary (text overlay) How to customize Adjust/Replace the workflow triggers as needed Change the prompt in the topics generation node Replace the product image URLs used in the "gotoHuman - Content" node Adjust the available styles for image generation in the gotoHuman review template and the prompts they link to in the "Set Initial Image Prompt" node Adjust the prompt used for video generation in the "Set Initial Video Prompt" node If you want to use a different service/model for image and video generation, replace the nodes related to Fal.ai. Also, if you do not need a text overlay, remove the Cloudinary nodes.

gotoHumanBy gotoHuman
1316

📍 Daily nearby garage sales alerts via Telegram

Get a personalized list of garage sales happening today, based on your current location, directly in Telegram each morning! This n8n workflow integrates Home Assistant and Brocabrac.frto: Automatically detect your location every day Scrape and parse garage sale listings from Brocabrac Filter for high-quality and nearby events Send a neatly formatted message to your Telegram account Perfect for treasure hunters and second-hand enthusiasts who want to stay in the loop with zero effort!

ThibaudBy Thibaud
1043

Automated invoice management with Nextcloud, email and Telegram notifications

This workflow automatically fetches PDF invoices from a Nextcloud folder (/Invoice/Incoming), sends them via email to a fixed recipient (invoice@example.com), sends a Telegram notification, and archives the file to /Invoice/2025/archive. Key Steps: Triggered daily at 8 AM Lists files in /Invoice/Incoming Filters for existing entries Downloads the file Sends the invoice via email Sends a Telegram message with filename Moves the file to archive 📦 Technologies used: Nextcloud SMTP Email Telegram Bot ⚙️ Use case: Perfect for freelancers or small businesses to automate recurring invoice sending with minimal effort.

Joachim HummelBy Joachim Hummel
1004

Create a new user in Intercom

No description available.

tanaypantBy tanaypant
807