AI Automation
923 results — all source-linked n8n references
Extract & Summarize Indeed Company Info with Bright Data and Google Gemini
Who this is for? Extract & Summarize Indeed Company Info is an automated workflow that extracts the Indeed company profile information using Bright Data Web Unlocker, transform it using Google Gemini’s LLM, and forward the transformed response with the summary to a specified webhook for downstream use. This workflow is tailored for: Recruiters and HR teams looking to assess companies quickly during talent sourcing. Job seekers researching potential employers and needing summarized company insights. Market researchers and analysts monitoring competitor or industry players. What problem is this workflow solving? Searching and evaluating company profiles on Indeed manually can be time-consuming and inefficient, especially when dealing with large volumes of companies. Manually browsing, copying, and summarizing company descriptions, reviews, and ratings from Indeed hinders productivity and limits real-time insights. This workflow solves this by: Automating the extraction of company details from Indeed using Bright Data Web Unlocker. Summarizing the raw data using Google Gemini's language model for a quick, human-readable overview. Sending the transformed response with the summary to a
WAutomated Generation of AI Advertising Photos for Product Marketing
How it works This workflow automates the transformation of standard product images into professional product photography featuring human models It uses AI to analyze product images, create tailored photography prompts, and generate high-quality enhanced versions Set up steps You'll need an OpenAI API key and access to gpt-image-1 (verify your organization) Set up a Google Sheets spreadsheet with columns: Image-URL, Prompt, Output Create a Google Drive folder to store the generated images Requirements: OpenAI API access (for image generation and analysis) Google Sheets and Google Drive accounts Basic product images (URLs) as input The spreadsheet must contain a column named "Image-URL" with links to the product images This workflow automatically: Reads product image URLs from your Google Sheet Downloads the images for processing Analyzes each image to understand what product it contains Creates specialized photography prompts ensuring each product is shown with a human model Generates professional product photography using OpenAI's image generation capabilities Uploads results to Google Drive and updates your spreadsheet with links Extra: You can also use the included simple image g
Daily Personalized Air & Pollen Health Alerts with Ambee API and AI via Email
This workflow fetches real-time air quality and pollen data using Ambee’s APIs and sends a friendly, personalized daily summary by email. It uses a scheduler to automate data collection, AI-generated health tips, and clear, actionable messages—perfect for sensitive users (e.g. kids with asthma, allergy sufferers). Use Case: Ideal for individuals with respiratory conditions, allergies, or those who want to stay informed about environmental conditions affecting their health. Set up steps Estimated time: 10–15 minutes You'll need: Ambee API key (free registration) OpenAI API key Email credentials (Gmail) User Profile 💡 Keep in mind: You’ll need to input your location coordinates (we’ve pre-filled Braunschweig as an example). The AI Agent node uses a ready-made prompt that’s tailored for email—but feel free to adapt it to other messaging platforms.
Multi-Agent AI Clinic Management with WhatsApp, Telegram, and Google Calendar
Healthcare Clinic Assistant with WhatsApp and Telegram Integration Version: 1.1.0 n8n Version: 1.88.0+ License: MIT 📋 Description A comprehensive and modular automation workflow designed for healthcare clinics. It manages patient communication, appointment scheduling, confirmations, rescheduling, internal tasks, and media processing by integrating WhatsApp, Telegram, Google Calendar, and Google Tasks, combined with AI-powered agents for maximum efficiency. This system guarantees proactive communication with patients, streamlined internal clinic management, and consistent data synchronization across platforms. 🌟 Key Features 🤖 AI-Powered Specialized Agents: Distinct agents handle WhatsApp patient support, appointment confirmations, and internal rescheduling tasks. 📱 Omnichannel Communication: Handles patient interactions via WhatsApp and staff commands via Telegram. 📅 Google Calendar Appointment Management: Full synchronization for creating, updating, canceling, and confirming appointments. 📋 Task Management with Google Tasks: Manages shopping lists and administrative tasks efficiently through staff Telegram requests. 🔔 Automated Appointment Reminders: Daily-triggered system
AI-Powered Gmail Email Organization with Auto-Archiving and Priority Labels
Who is this for? This workflow is perfect for busy professionals, students, or anyone who struggles to keep their Gmail inbox organized and clutter-free. What problem is this workflow solving? It helps you avoid email overload by automating the process of organizing your Gmail inbox. Unnecessary emails are archived, while important emails are categorized into "MustRead" or "NotNeed" for better prioritization. What this workflow does Connects to your Gmail inbox. Automatically archives emails that are unnecessary or irrelevant. Sorts remaining emails into two categories: MustRead: Emails that require immediate attention. NotNeed: Less critical emails for review later. Setup Connect your Gmail account to the workflow. Define the criteria for "MustRead" and "NotNeed" emails by updating the filter rules in the nodes. Activate the workflow to start organizing your inbox. How to customize this workflow to your needs Adjust the filters for archiving emails based on your specific preferences. Modify the sorting rules for "MustRead" and "NotNeed" categories to match your workflow. Add additional actions, such as sending notifications for "MustRead" emails.
🗞️ AI-powered sustainability newsletter for marketing with Gmail, GPT-4o
Tags: Sustainability, Web Scraping, OpenAI, Google Sheets, Newsletter, Marketing Context Hey! I’m Samir, a Supply Chain Engineer and Data Scientist from Paris, and the founder of LogiGreen Consulting. We use AI, automation, and data to support sustainable business practices for small, medium and large companies. I use this workflow to bring awareness about sustainability and promote my business by delivering automated daily news digests. > Promote your business with a fully automated newsletter powered by AI! This n8n workflow scrapes articles from the official EU news website and sends a daily curated digest, highlighting only the most relevant sustainability news. 📬 For business inquiries, feel free to connect with me on LinkedIn Who is this template for? This workflow is useful for: Business owners** who want to promote their service or products with a fully automated newsletter Sustainability professionals** staying informed on EU climate news Consultants and analysts** working on CSRD, Green Deal, or ESG initiatives Corporate communications teams** tracking relevant EU activity Media curators** building newsletters What does it do? This n8n workflow: ⏰ Triggers automatical
Extract Amazon Best Seller Electronic Info with Bright Data and Google Gemini
Who this is for? Extract Amazon Best Seller Electronic Info is an automated workflow that extracts best seller data from Amazon's Electronics section using Bright Data Web Unlocker, transform it into structured JSON using Google Gemini's LLM, and forwards a fully structured JSON response to a specified webhook for downstream use. This workflow is tailored for: eCommerce Analysts** Who need to monitor Amazon best-seller trends in the Electronics category and track changes in real-time or on a schedule. Product Intelligence Teams** Who want structured insights on competitor offerings, including rankings, prices, ratings, and promotions. AI-powered Chatbot Developers** Who are building assistants capable of answering product-related queries with fresh, structured data from Amazon. Growth Hackers & Marketers** Looking to automate competitive research and surface trending product data to inform pricing strategies. Data Aggregators and Price Trackers** Who need reliable and smart scraping of Amazon data enriched with AI-driven parsing. What problem is this workflow solving? Keeping up with Amazon's best sellers in Electronics is a time-consuming, error-prone task when done manually.This
MCP Supabase Server for AI Agent with RAG & Multi-Tenant CRUD
Supabase AI Agent with RAG & Multi-Tenant CRUD Version: 1.0.0 n8n Version: 1.88.0+ Author: Koresolucoes License: MIT Description A stateful AI agent workflow powered by Supabase and Retrieval-Augmented Generation (RAG). Enables persistent memory, dynamic CRUD operations, and multi-tenant data isolation for AI-driven applications like customer support, task orchestration, and knowledge management. Key Features: 🧠 RAG Integration: Leverages OpenAI embeddings and Supabase vector search for context-aware responses. 🗃️ Full CRUD: Manage agent_messages, agent_tasks, agent_status, and agent_knowledge in real time. 📤 Multi-Tenant Ready: Supports per-user/organization data isolation via dynamic table names and webhooks. 🔒 Secure: Role-based access control via Supabase Row Level Security (RLS). Use Cases Customer Support Chatbots: Persist conversation history and resolve queries using institutional knowledge. Automated Task Management: Track and update task statuses dynamically. Knowledge Repositories: Store and retrieve domain-specific information for AI agents. Instructions 1. Import Template Go to n8n > Templates > Import from File and upload this workflow. 2. Configure Credenti
Business Model Canvas AI-Powered Generator (LLM Flexible)
👥 Who is this for? Startup founders validating or pitching new ideas Business consultants running strategy sessions Product teams defining business logic visually Agencies offering planning frameworks to clients ❓ What problem does this workflow solve? Creating a Business Model Canvas manually is time-consuming and often scattered across tools. This workflow solves that by allowing users to generate a fully populated, formatted, and printable Business Model Canvas in seconds using the power of AI, all structured in a professional A4 landscape layout. ⚙️ What this workflow does Starts with a chat input asking for your business idea Sends it to 9 separate AI agents, each focused on one section: Key Partners Key Activities Value Proposition Customer Relationships Customer Segments Key Resources Channels Cost Structure Revenue Streams Uses your preferred LLM (see below) to generate meaningful bullet points Converts output into a specific format Merges all sections into a clean, A4-styled HTML canvas Exports the result as a downloadable .html file 🛠️ Setup Import the workflow into your n8n instance Start the flow from the “When chat message received” node Describe your business idea w
Build a Chatbot, Voice and Phone Agent with Voiceflow, Google Calendar and RAG
Voiceflow is a no-code platform that allows you to design, prototype, and deploy conversational assistants across multiple channels—such as chat, voice, and phone—with advanced logic and natural language understanding. It supports integration with APIs, webhooks, and even tools like Twilio for phone agents. It's perfect for building customer support agents, voice bots, or intelligent assistants. This workflow connects n8n and Voiceflow with tools like Google Calendar, Qdrant (vector database), OpenAI, and an order tracking API to power a smart, multi-channel conversational agent. There are 3 main webhook endpoints in n8n that Voiceflow interacts with: n8n_order – receives user input related to order tracking, queries an API, and responds with tracking status. n8n_appointment – processes appointment booking, reformats date input using OpenAI, and creates a Google Calendar event. n8n_rag – handles general product/service questions using a RAG (Retrieval-Augmented Generation) system backed by: Google Drive document ingestion, Qdrant vector store for search, and OpenAI models for context-based answers. Each webhook is connected to a corresponding "Capture" block inside Voiceflow, which
AI-Powered Telegram Task Manager with MCP Server
Detailed Description The ToDo App workflow is designed to streamline task management through Telegram and Google Tasks integration. This workflow allows users to create, update, and manage tasks via Telegram messages, leveraging AI capabilities to enhance user interaction. The expected outcome is a seamless experience where users can manage their tasks efficiently without needing to switch between applications. Who is this for? This workflow is intended for: Individuals** looking for an efficient way to manage their tasks directly from Telegram. Teams** that require a collaborative task management solution integrated with Google Tasks. Developers** interested in automating task management processes using n8n and Telegram. What problem does this workflow solve? Managing tasks can often be cumbersome, especially when switching between different applications. This workflow addresses the following problems: Fragmented Task Management**: Users can manage tasks directly from Telegram, reducing the need to switch to Google Tasks. Inefficient Communication**: By integrating AI, users can interact with the task management system in a conversational manner, making it more intuitive. Task Upd
WAuto-create and publish AI social videos with Telegram, GPT-4 and Blotato
Auto-create and publish AI social videos with Telegram, GPT-4 and Blotato > ⚠️ Disclaimer: This workflow uses Community Nodes and must be run on a self-hosted instance of n8n. Who is this for? This template is perfect for social media managers, content creators, AI enthusiasts, and automation pros who want to generate short-form videos (Reels) from a simple Telegram message, then publish them across multiple platforms—all without video editing or manual uploads. What problem is this workflow solving? Creating content is only half the job. The real bottleneck comes in: Rendering the video, Adding voice or music, Writing captions and titles, Publishing to multiple platforms. This workflow automates all of that using AI. It saves hours every week and guarantees consistent output. What this workflow does This end-to-end automation handles everything from AI video generation to social publishing: Starts with a Telegram message (text or image prompt) Generates video using Kling or Blotato, based on the input Creates music with Piapi and merges it with the video Generates text overlays and captions with GPT-4 Builds a stylized video using JSON2Video Logs results to Google Sheets Sends
📥 Transform Google Drive Documents into Vector Embeddings
Automatically convert documents from Google Drive into vector embeddings using OpenAI, LangChain, and PGVector — fully automated through n8n. ⚙️ What It Does This workflow monitors a Google Drive folder for new files, supports multiple file types (PDF, TXT, JSON), and processes them into vector embeddings using OpenAI’s text-embedding-3-small model. These embeddings are stored in a Postgres database using the PGVector extension, making them query-ready for semantic search or RAG-based AI agents. After successful processing, files are moved to a separate “vectorized” folder to avoid duplication. 💡 Use Cases Powering Retrieval-Augmented Generation (RAG) AI agents Semantic search across private documents AI assistant knowledge ingestion Automated document pipelines for indexing or classification 🧠 Workflow Highlights Trigger Options:** Manual or Scheduled (3 AM daily by default) Supported File Types:** PDF, TXT, JSON Embedding Stack:** LangChain Text Splitter, OpenAI Embeddings, PGVector Deduplication:** Files are moved after processing License:** CC BY-SA 4.0 Author:** AlexK1919 🛠 What You’ll Need Google Drive OAuth2** credentials (connected to Search Folder, Download File, and Mo
W🌳 EU green legislation tracker with GPT-4o, Google Sheets and Tasks
Tags: EU Legislation, Sustainability, Automation, Web Scraping, OpenAI, Google Sheets, Policy Monitoring, Climate Context Hey! I’m Samir, a Supply Chain Engineer and Data Scientist from Paris, and the founder of LogiGreen Consulting. We use AI, automation, and data to support sustainable business practices for small, medium and large companies. This workflow is part of our broader initiative to monitor and act on sustainability legislation in Europe. > How do you know if new EU laws will impact your business's sustainability goals? This n8n workflow automatically scrapes the EU Parliament’s legislative portal to find and flag procedures related to environmental sustainability. 📬 For business inquiries, feel free to connect with me on LinkedIn Who is this template for? This workflow is useful for: Sustainability consultants** monitoring legal frameworks NGOs and researchers** tracking environmental regulations Companies* aligning with *CSRD* or *EU Green Deal** objectives Policy analysts** looking for automation tools What does it do? This n8n workflow: 🌐 Scrapes the EU Parliament legislative portal for yesterday’s entries 🧠 Uses OpenAI to classify if each procedure is related
W🧑🦯Improve your website accessibility with GPT-4o and Google Sheet
Tags: Accessibility, SEO, Blogging, Marketing, Automation, AI, Web Auditing Context Hey! I’m Samir, a Supply Chain Engineer and Data Scientist from Paris, and the founder of LogiGreen Consulting. In my personal blog, I share insights on how to use AI, automation, and data analytics to improve logistics, operations, and digital sustainability practices. > Have you heard about accessibility? In this workflow, I use n8n to improve the quality of alternative texts for images on my personal website. 📬 For business inquiries, you can connect with me on LinkedIn Who is this template for? This workflow is for: Bloggers* and *website owners* who want to *improve accessibility** SEO professionals** looking to boost page performance Web developers* and *product teams** automating web audits What does it do? This n8n workflow: 🔍 Downloads the HTML of a blog or web page 🖼️ Extracts all ` tags and their alt` attributes 📉 Detects missing or too-short alt texts 🤖 Sends those images to GPT-4o (with vision) to generate new alt descriptions 📄 Saves the results into a Google Sheet, updating the alt text when needed How it works Set a page URL using the Set node Download HTML content Extract i
WBuild your own CUSTOM API MCP server
This n8n demonstrates how any organisation can quickly and easily build and offer MCP servers to their customers or internal staff to improve productivity. This MCP example uses PayCaptain.com as an example and shows how to create an MCP server which can search for and update employee data. How it works A MCP server trigger is used and connected to 3 custom workflow tools: Search Employee, Get Employee by ID and Update Employee. Each tool makes calls to the PayCaptain API to perform their respective tasks. Extra care is performed to strip out sensitive data and ensure we're not sharing too much. The Update Employee too also guards against updating fields which would preferably remain readonly. When you control the MCP server, you can determine behaviour of the tool. Finally, a Google Sheet node is used to log all operations for later audit. This will add a tiny bit of latency but recommended if sensitive data is being accessed. How to use This MCP server allows any compatible MCP client to manage their PayCaptain employee database. You will need to have a PayCaptain account and developer key to use it. Connect your MCP client by following the n8n guidelines here - https://docs.n8n.
WBuild your own Youtube MCP server
This n8n demonstrates how to build a simple Youtube MCP server to look up videos on Youtube and download their transcripts for research purposes. Youtube videos are a great source of new and updated information on a variety of cutting edge developments but they''re are not always simple to understand and lengthy videos may take too much time. Using this MCP server, you extract and feed their transcripts for your AI agents which then allows it to breakdown the content into manageble learnings and insights. How it works A MCP server trigger is used and connected to 3 custom workflow tools: Youtube Search, Youtube Transcripts and Usage Reports. Both Youtube tools use an external scraping service called APIFY.com. This is my preference as it's a much simpler interface and there are no rate limits. The Youtube Search fetches 10 results based on the user's query. The Youtube Transcripts downloads the subtitles from one or more given URL. The usage reports pulls in your monthly APIFY.com monthly spending and limits as a way to check your account. How to use This Apify Youtube MCP server allows any compatible MCP client to research YouTube videos for any desired topic. An Apify account is
CDBuild 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 ser
WBuild your own Github MCP server
This n8n demonstrates how to build your own Github MCP server to personalise it to your organisation's repositories, issues and pull requests. This n8n implementation, though not as fully featured as the official MCP server offered by Github, allows you to control precisely what access and/or functionality is granted to users which can make MCP use simpler and in some cases, more secure. The use-case in this template is to simply view and comment on issues within a specific repository but can be extended to meet the needs of your team. This MCP example is based off an official MCP reference implementation which can be found here https://github.com/modelcontextprotocol/servers/tree/main/src/github How it works A MCP server trigger is used and connected to 3 custom workflow tools. We're using custom workflow tools as there is quite a few nodes required for each task. Behind these tools are regular Github nodes although preconfigured with credentials and targeted repository. The "Get Issue Comments" and "Create Issue Comment" tools depend on obtaining an Issue Number first. The agent should call the "Get Latest Issues" tool for this. How to use This Github MCP server allows any compat
Build your own Google Drive MCP server
This n8n demonstrates how to build a simple Google Drive MCP server to search and get contents of files from Google Drive. This MCP example is based off an official MCP reference implementation which can be found here -https://github.com/modelcontextprotocol/servers/tree/main/src/gdrive How it works A MCP server trigger is used and connected to 1x Google Drive tool and 1x Custom Workflow tool. The Google Drive tool is set to perform a search on files within our Google Drive folder. The Custom Workflow tool downloads target files found in our drive and converts the binaries to their text representation. Eg. PDFs have only their text contents extracted and returned to the MCP client. How to use This Google Drive MCP server allows any compatible MCP client to manage a person or shared Google Drive. Simple select a drive or for better control, specify a folder within the drive to scope the operations to. 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: "Please help me search for last month's expense reports." "Wh
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Build your own SQLite MCP server
This template is for Self-Hosted N8N Instances only. This n8n demonstrates how to build a simple SQLite MCP server to perform local database operations as well as use it for Business Intelligence. This MCP example is based off an official MCP reference implementation which can be found here -https://github.com/modelcontextprotocol/servers/tree/main/src/sqlite How it works A MCP server trigger is used and connected to 5 tools: 2 Code Node and 3 Custom Workflow. The 2 Code Node tools use the SQLLite3 library and are simple read-only queries and as such, the Code Node tool can be simply used. The 3 custom workflow tools are used for select, insert and update queries as these are operations which require a bit more discretion. Whilst it may be easier to allow the agent to use raw SQL queries, we may find it a little safer to just allow for the parameters instead. The custom workflow tool allows us to define this restricted schema for tool input which we'll use to construct the SQL statement ourselves. All 3 custom workflow tools trigger the same "Execute workflow" trigger in this very template which has a switch to route the operation to the correct handler. Finally, we use our Code no
Build your own PostgreSQL MCP server
This n8n demonstrates how to build a simple PostgreSQL MCP server to manage your PostgreSQL database such as HR, Payroll, Sale, Inventory and More! This MCP example is based off an official MCP reference implementation which can be found here -https://github.com/modelcontextprotocol/servers/tree/main/src/postgres How it works A MCP server trigger is used and connected to 5 tools: 2 postgreSQL and 3 custom workflow. The 2 postgreSQL tools are simple read-only queries and as such, the postgreSQL tool can be simply used. The 3 custom workflow tools are used for select, insert and update queries as these are operations which require a bit more discretion. Whilst it may be easier to allow the agent to use raw SQL queries, we may find it a little safer to just allow for the parameters instead. The custom workflow tool allows us to define this restricted schema for tool input which we'll use to construct the SQL statement ourselves. All 3 custom workflow tools trigger the same "Execute workflow" trigger in this very template which has a switch to route the operation to the correct handler. Finally, we use our standard PostgreSQL node to handle select, insert and update operations. The res
Build your own FileSystem MCP server
This template is for self-hosted n8n instances only. This n8n demonstrates how to build a simple FileSystem MCP server. Connecting to this server allows MCP clients and agents to list, read and create directories and files on the local machine or remote server. This MCP example is based off an official MCP reference implementation which can be found here -https://github.com/modelcontextprotocol/servers/tree/main/src/filesystem How it works A MCP server trigger is used and connected to 5 tools: 3 Execute Command tools and 2 custom workflow tools. The 3 Execute Command tools allow for listing, searching and creating directories. The 2 custom workflow tools are for reading and writing files to disk. Special care has been to not allow the MCP agent to execute arbitrary linux commands on the target server. This is achieved by only allowing the agent to provide parameters such as filenames and paths rather than raw commands. How to use This Filesystem MCP server will write to the server which hosts the n8n instance - this can be your local machine or a remove server. If your target filesystem is on neither, then modify the commands to connect to the desired server. Connect your MCP clien
WScrape Competitor Reviews & Generate Ad Creatives with Bright Data & OpenAI
Scrape Competitor Reviews & Generate Ad Creatives with Bright data and OpenAI How the Flow Runs Fill the Form Enter the Amazon product URL to analyze competitor reviews. Trigger Bright Data Scraper Bright Data scrapes Amazon reviews based on the provided URL. Wait for Snapshot Completion Periodically checks Bright Data until the scraping is complete. Retrieve JSON Data Collects the scraped review data in JSON format. Save Reviews to Google Sheets Automatically appends the scraped reviews to your Google Sheets. Aggregate Reviews Consolidates all reviews into a single summary for simpler analysis. Analyze Reviews with OpenAI LLM Sends the aggregated reviews to OpenAI (GPT-4o mini) to summarize competitors’ main weaknesses clearly. Generate Creative Ad Image OpenAI generates a visually appealing 1080x1080 ad image addressing these identified pain points. Send Ad Creative via Gmail Automatically emails the creative and review summary to your media buying team for immediate use in Meta ads. What You Need Google Sheets:** Template Bright Data:** Dataset and API key: www.brightdata.com OpenAI API Key:** For GPT-4o mini or your preferred LLM Automation Tool:** Ensure it supports HTTP Reque