by Rahul Joshi
Description: Automate your AI newsletter creation and delivery using this ready-to-deploy n8n workflow template. Powered by GPT (OpenAI/Azure) and integrated with Gmail, this workflow generates rich, structured, and engaging AI-focused newsletters and sends them out daily or weekly—completely hands-free. What It Does: 📰 Fetches the latest AI trends and updates using GPT ✍️ Automatically formats news into structured newsletter sections: headlines, tools, stats, tips, and more 📧 Sends HTML email newsletters via Gmail 🕘 Runs automatically at your chosen schedule (default: 9 AM daily) Setup Includes: Connect your OpenAI or Azure GPT API Add Gmail SMTP or OAuth credentials Customize categories, schedule, and email styling Perfect for: Tech bloggers, content marketers, AI influencers, and automation enthusiasts who want to send curated AI content to their audience without manual effort.
by Jimleuk
This n8n template offers a simple yet capable chatbot assistant who can answer course enquiries over SMS. Given the right access to data, AI Agents are capable of planning and performing relatively complex research tasks to get their answers. In this example, the agent must first understand the database schema, retrieve lists of values before generating it's own query to search over the database. Checkout the example database here - https://airtable.com/appO5xvP1aUBYKyJ7/shr8jSFDaghubDOrw How it works A Twilio trigger gives us the ability to receive SMS input into our workflow via webhook. The message is then directed to our AI agent who is instructed to assist the user and use the course database as reference. The database is an Airtable base. The agent autonomously figures out which tool it needs to use and generates it's own "filter_by_formula" query to search over the available courses. On successful search results, the Agent can then use this information to answer the user's query. The Agent's output is logged in a second sheet of the Airtable base. We can use this later for analysis and lead gen. Finally, the response is sent back to the user through SMS using Twilio. How to use Ensure your Twilio number is set to forward messages to this workflow's webhook URL. Configure and update the course database as required. If you're not interested in courses, you can swap this out for inventory, deliveries or any other data relevant to your business. Ask questions like: "Can you help me find suitable courses to fill my Wednesday mornings?" "Which courses are being instructed by profession Lee?" "I'm interested in creative arts. What courses are available which could be relevant to me?" Requirements Twilio for SMS receiving and sending OpenAI for LLM and Agent Airtable for Course Database Customising this workflow Add additional tools and expand the range of queries the agent is able to answer or assist with. Not using Airtable? This technique also works with SQL databases like PostgreSQL.
by Not Another Marketer
Instantly Find & Fix What’s Holding Your Page Back You’ve put in the work. Your content is strong. Your design is polished. But… ❌ Your page isn’t ranking where it should. ❌ Your competitors are outranking you—even with weaker content. ❌ You have no idea what’s wrong—or how to fix it. The truth? SEO isn’t just about keywords. Your technical setup, content structure, and on-page elements must work together seamlessly. And if anything is off? Google won’t rank your page. Who Is This For? SaaS Founders & Startups – Get higher rankings & organic traffic that converts. Marketing Teams & Agencies – Audit & optimize pages in seconds. E-commerce & Content Sites – Improve rankings for product pages, blogs, and landing pages. How It Works Paste your URL Get an instant audit + recommendations list Implement changes & watch your rankings jump The workflow scrapes the url you input, gets the htlm source code of the landing page, and sends it to OpenAI AI Agent. The Agent makes a deep analysis, audit the Technical + Content SEO of the page, and provides 10 Recommendations to improve your SEO. Setup Guide You will need OpenAI Credentials with an API Key to run the workflow. The workflow is using the OpenAI-o1 model to deliver the best results. It costs between $0.20/0.30 per run. You can adjust the prompt to your wish in the AI Agent parameters. Once the audit has been completed, it will send an email (don't forget to add your email address here) Below is an example of what you can expect
by Joseph LePage
This n8n workflow demonstrates multiple ways to harness DeepSeek's AI models in your automation pipeline! 🌟 Core Features Multiple Integration Methods 🔌 Local deployment using Ollama for DeepSeek-R1 Direct API integration with DeepSeek Chat V3 Conversational agent with memory buffer HTTP request implementation with both raw and JSON formats Model Options 🧠 DeepSeek Chat V3 for general conversation DeepSeek-R1 for advanced reasoning Memory-enabled agent for persistent context Quick Setup 🛠️ API Configuration Base URL: https://api.deepseek.com Get your API key from platform.deepseek.com/api_keys Local Setup 💻 Install Ollama for local deployment Set up DeepSeek-R1 via Ollama Configure local credentials in n8n Implementation Details 🔧 Conversational Agent Window Buffer Memory for context Customizable system messages Built-in error handling with retries API Endpoints 🌐 Chat completions for V3 and R1 models OpenAI API format compatibles
by Yang
Who is this for? This workflow is for digital marketers, small business owners, lead generation agencies, and VAs who need a scalable way to find and store local business leads using AI. It’s especially useful for teams that want to enrich leads with real-time news insights and save the structured data to Airtable. What problem is this workflow solving? Manually researching local businesses and staying up to date with relevant news is time-consuming and inefficient. This automation eliminates that burden by using Dumpling AI chat agents to generate leads and context, GPT-4o to summarize, and Airtable to store everything in one place. What this workflow does This AI workflow listens for a manual trigger in n8n and executes the following steps: Extracts local business leads using a Local Business Agent from Dumpling AI. Pulls current news related to the business type or location using a News Agent from Dumpling AI. Uses GPT-4o to combine both responses into a human-readable summary. Extracts structured lead data like name, category, and city. Saves the summary and lead data into Airtable for easy follow-up. Setup 1. Create AI Agents in Dumpling AI Sign in at Dumpling AI Create two separate agents: Local Business Agent: Designed to respond with structured lists of businesses by location and category. News Agent: Designed to fetch relevant recent news and summaries about a specific industry or region. After setting up each agent, copy the Agent Key from Dumpling AI. These keys will be required in the headers of your HTTP Request nodes in n8n. 2. Manual Trigger This workflow begins with a manual trigger inside n8n, Which is the When chat message is recieved. This makes it easy to test and reuse, especially during setup. 3. Get Local Business Data from Dumpling AI The first HTTP Request node sends a prompt like List 5 top real estate companies in Atlanta with full address and services. Include your Local Business Agent Key in the x-agent-key header. The response will return a structured list of business leads. 4. Get News Context from Dumpling AI The second HTTP Request node sends a prompt such as Give me the latest news related to the real estate market in Atlanta. Use your News Agent Key in the header. This fetches a brief set of recent news summaries relevant to the businesses being researched. 5. Use GPT-4o to Merge and Summarize The GPT node combines the list of businesses and news into one coherent summary. You can modify the prompt to output in paragraph format, bullet points, or structured notes. 6. Save Lead to Airtable The Airtable node sends all structured fields into your selected base and table. Be sure to connect your Airtable account and confirm the columns match exactly. How to customize this workflow Replace the prompt inside the HTTP node to focus on different types of businesses or cities. Expand the GPT output to include additional lead info like websites, phone numbers, or emails if the agent includes them. Add a webhook trigger to allow this flow to be run via a chatbot, external app, or button. Link to HubSpot or another CRM to sync the leads automatically. Duplicate the process to run for multiple industries in parallel. Final Notes You must create and configure your Dumpling AI agents first before running this workflow. The Agent Keys from Dumpling AI are required in both HTTP Request nodes. This flow is modular and flexible, ready for deeper CRM integrations. The manual trigger is great for testing, but you can add a Webhook node to automate it. This workflow helps you launch an intelligent lead gen process that combines location-targeted business discovery, AI-generated insights, and structured CRM-friendly output, all powered by Dumpling AI and OpenAI.
by Praveena
Purpose The purpose of this automation is to help context switch from office to some side projects or passion gigs so you can be free of distracting thoughts and re-set your perspective. Benefits Anyone who works full time and also does something on the side (perhaps a side gig/being a mom/just follow your passion project) What you need N8N (lol) Any LLM API Key (I used OpenAI 4.1) IPhone (automations and shortcuts) Template Setup Setup LLM API key. Import template file to new workflow. On Iphone create a new shortcut as per video. Create automation steps. Resources Youtube
by Fan Luo
Auto-Share YouTube Videos with AI-Generated Posts to Facebook, X and Notify in Discord This n8n template demonstrates how to use a LLM like DeepSeek to generate a post and share to Facebook page and X automatically whenever a new video is published to a YouTube channel. How it works We first define RSS with a polling schedule to pull YouTube videos from a specified channel Prompt AI agent to generate a post with proper url and hash tags based on the video metadata Then automatically create a new post in Facebook and X via their APIs Post a new message in Discord channel via Webhook How to use Simply setup a RSS polling trigger to automatically trigger the workflow Requirements Facebook API setup, see step by step tutorials X v2 API setup, see step by step tutorials Discord channel webhook, see step by step tutorials Need Help? Contact me via My Blog or ask in the Forum! Happy Hacking!
by Jimleuk
This n8n workflow demonstrates how to build a simple uptime monitoring service using scheduled triggers. Useful for webmasters with a handful of sites who want a cost-effective solution without the need for all the bells and whistles. How it works Scheduled trigger reads a list of website urls in a Google Sheet every 5 minutes Each website url is checked using the HTTP node which determines if the website is either in the UP or DOWN state. An email and Slack message are sent for websites which are in the DOWN state. The Google Sheet is updated with the website's state and a log created. Logs can be used to determine total % of UP and DOWN time over a period. Requirements Google Sheet for storing websites to monitor and their states Gmail for email alerts Slack for channel alerts Customising the workflow Don't use Google Sheets? This can easily be exchanged with Excel or Airtable.
by Yang
Who is this for? This workflow is built for newsletter writers, marketers, content creators, or anyone who curates and summarizes web articles. It’s especially helpful for virtual assistants and founders who need to quickly turn web content into digestible, branded newsletters using AI. What problem is this workflow solving? Manually reading, summarizing, and formatting multiple articles into a newsletter takes time and focus. This workflow automates the process using Dumpling AI for crawling, GPT-4o for summarization, and Gmail for delivery—so you can go from raw URLs to a polished email in minutes. What this workflow does Starts manually (can also be scheduled) Reads a list of article URLs from Google Sheets Sends URLs to Dumpling AI to crawl and extract content Splits each article into a single item for processing Uses a Code node to clean and structure article data Uses an Edit Fields node to merge articles into one JSON block GPT-4o summarizes and generates HTML content for the newsletter Sends the formatted newsletter via Gmail Setup Google Sheets Create a sheet with a column (A) for article URLs Update the Read URLs from Google Sheet node to use your Sheet ID and tab name Connect your Google account in the credentials Dumpling AI Sign up at https://app.dumplingai.com Create an agent for web crawling under /crawl Add your Dumpling API key in the HTTP headers of the Crawl Content with Dumpling AI node Split Node Breaks apart the array of articles from Dumpling AI so each article is processed individually Code Node Structures each article as JSON with title, url, and cleaned text content Edit Fields Node Gathers all structured articles back into a single JSON array to prepare for AI summarization OpenAI (GPT-4o) Processes the article list and returns a formatted subject line and HTML newsletter content Gmail Connect your Gmail account to send the AI-generated newsletter to your inbox or team Update the recipient field in the Send HTML Email via Gmail node How to customize this workflow to your needs Replace the manual trigger with a Schedule node to send newsletters weekly Modify the GPT-4o prompt to change tone (e.g., more professional, funny, casual) Add filtering logic to skip low-value articles Connect Slack, Airtable, or Notion for internal team usage Change Gmail to SendGrid or Outlook if preferred Final Notes This workflow uses: Dumpling AI** /crawl endpoint to extract article content Split, **Code, and Edit Fields nodes to format multi-article input GPT-4o** for summarization and HTML formatting Gmail** for delivery This setup eliminates manual steps and delivers fast, consistent newsletters powered by AI.
by Praveena
Idea The idea for app came since I wanted to build a unique gift for my niece because she gets excited for her birthday (which Im going to miss this year). The web app has a simple countdown (in html and JS) but more importantly, there is an AI agent that will answer some specific questions and know her preferences. How it works The questions from app are sent via web hook to N8N which has pulls preferences file (about her likes, dislikes, personality) from postgre and AI Agent that will answer questions/respond. The current status is stored back in postgre (especially about status of cat and universe happenings) before responding back. Features Integrated AI chatbot via N8N webhook Persistent conversation history Minimizable chat interface Fallback support for offline testing Features: -- Wheres Mittens - This is a query to track her lost cat in multiverse. -- Multiverse updates with recent update stored Pre Requisites Postgre SQL database is available. Alternatively, use any other database but change the N8N nodes. LLM Api Key. Step by Step Instructions Export this N8N Workflow. Modify LLM API Key, I used openAI, 4.1 For web app scofflding,you will need Node, HTML and Javascript. I've created a mini version using Node and JS with web app and N8N connection settings here: <https://github.com/productiser/FiBirthdayAgent> PostgreSQL Database Script (1 table for memory and context storage): CREATE TABLE fifi_world_context ( id TEXT PRIMARY KEY, -- e.g., 'agent_fifi' cat_location TEXT, -- e.g., "Bubble Nebula" cat_activity TEXT, -- e.g., "Playing laser tag with moon mice" fifi_preferences JSONB, -- e.g., likes/dislikes/foods/shows world_history TEXT, -- Summary of narrative events last_updated TIMESTAMP DEFAULT CURRENT_TIMESTAMP ); 5.Modify system prompt as per your needs. Built With N8N Self hosted Self hosted web app Hosted on Vercel Total spend = <£1 (AI costs only) Total Time = <1 day Support Watch this video for web app overview and how it looks. <https://youtu.be/e7PlrTdvwoM> Contact me on info@pankstr.com/ superllmuser@gmail.com for any queries Hope you enjoy!!
by Yang
Who is this for? This workflow is perfect for customer support teams, sales departments, or solopreneurs who receive frequent email enquiries and want to automate the initial response process using AI. If you spend too much time answering similar questions, this system helps respond faster and more intelligently—without writing a single line of code. What problem is this workflow solving? Manually responding to repeated customer enquiries slows productivity and increases delay. This workflow classifies if an incoming email is a real enquiry, analyzes the content with a LangChain-powered agent, fetches helpful context using Dumpling AI, and sends a personalized reply using Gmail—all within minutes. What this workflow does Listens for new incoming Gmail messages using the Gmail Trigger node. Classifies whether the email is an enquiry using a GPT-4o classification prompt. Uses a Filter node to continue only if the email was classified as an enquiry. Passes the email content to a LangChain Agent, enhanced with memory, AI tools, and Dumpling AI to search for relevant information. The agent constructs a smart, relevant response, then sends it to the original sender via Gmail. Setup Connect Gmail Use the Gmail Trigger node to connect to the Gmail account that receives enquiries. Make sure Gmail OAuth2 credentials are authenticated. Configure Dumpling AI Agent Sign up at Dumpling AI. Create an agent trained to search your help docs, site content, or FAQs. Copy your Dumpling agent ID and API key. Paste it in the Dumpling AI Agent – Search for Relevant Info HTTP Request node. Set Up LangChain Agent No extra setup needed beyond connecting OpenAI credentials. GPT-4o is used for classification and reply generation. Enable Gmail Reply Node The final Send Email Response via Gmail node will send the AI-generated reply back to the same thread. How to customize this workflow to your needs Change the classification prompt to include other email types like “support”, “complaint”, or “sales”. Add additional logic if you want to CC someone or forward certain types of enquiries. Add a Notion or Google Sheets node to log the conversation for analytics. Replace Gmail with Outlook or another email provider by switching the nodes. Improve context by adding more AI tools like database queries or preloaded FAQs.
by Yulia
This n8n workflow demonstrates how to create an agent using LangChain and SQLite. The agent can understand natural language queries and interact with a SQLite database to provide accurate answers. 💪 🚀 Setup Run the top part of the workflow once. It downloads the example SQLite database, extracts from a ZIP file and saves locally (chinook.db). 🗣️ Chatting with Your Data Send a message in a chat window. Locally saved SQLite database loads automatically. User's chat input is combined with the binary data. The LangChain Agend node gets both data and begins to work. The AI Agent will process the user's message, perform necessary SQL queries, and generate a response based on the database information. 🗄️ 🌟 Example Queries Try these sample queries to see the AI Agent in action: "Please describe the database" - Get a high-level overview of the database structure, only one or two queries are needed. "What are the revenues by genre?" - Retrieve revenue information grouped by genre, LangChain agent iterates several time before producing the answer. The AI Agent will store the final answer in its memory, allowing for context-aware conversations. 💬 Read the full article: 👉 https://blog.n8n.io/ai-agents/