Workflow Templates

Use Case It is very convenient to add expenses via simple chat message. This workflow attempts to do exactly this using AI-powered n8n magic! Send message to a chat, something like "car wash; 59.3 usd; 25 jan 2024" And get a response: Your expense saved, here is the output of save sub-workflow:{"cost":59.3,"descr":"car wash","date":"2024-01-25","msg":"car wash; 59.3 usd; 25 jan 2024"} LLM will smartly parse your message to structured JSON and save the expense as a new row into Google Sheet! Installation 1. Set up Google Sheets: Clone this Sheet: https://docs.google.com/spreadsheets/d/1D0r3tun7LF7Ypb21CmbTKEtn76WE-kaHvBCM5NdgiPU/edit?gid=0#gid=0 (File -> Make a copy) Choose this sheet into "Save expense into Google Sheets" node. 2. Fix sub-workflow dropdown: open "Parse msg and save to Sheets" node (which is an n8n sub-workflow executor tool) and make sure the SAME workflow is chosen in the dropdown. it will allow n8n to locate and call "Workflow Input Trigger" properly when needed. 3. Activate the workflow to make chat work properly. Sent message to chat, something like "car wash; 59.3 usd; 25 jan 2024" you should get a response: Your expense saved, here is the output of save sub-workflow:{"cost":59.3,"descr":"car wash","date":"2024-01-25","msg":"car wash; 59.3 usd; 25 jan 2024"} and new row in Google sheets should be inserted!

This n8n workflow template uses community nodes and is only compatible with the self-hosted version of n8n. 📈 StockPulse: AI-Picked Daily News for Your Portfolio Stay ahead of the market with this automated, AI-powered stock market news briefing delivered straight to your inbox — no code required. Watch Step-by-step Video Tutorial Here: https://www.youtube.com/watch?v=iZvPej9eLYE&t=201s ⚙️ What it does: This workflow runs every morning and: Triggers a scheduled prompt to a Langchain AI Agent (OpenAI) Uses the Tavily Web Search API to fetch fresh financial news relevant to your watchlist or portfolio Summarizes the top stories, highlighting: 🔍 Key headlines 💡 Investment opportunities ⚠️ Risks and macro trends 📊 Suggested trades Sends a clean, readable email via Gmail to your preferred address 🔧 Built with: 🧠 Langchain AI Agent (OpenAI GPT-4o) 🔍 Tavily Search Tool 📬 Gmail Node for Email Delivery ⏰ Daily Cron Trigger (customizable) 💼 Who it’s for: Investors and traders who want to save time on news gathering Financial creators looking for curated, actionable insights Non-technical users interested in automating stock news monitoring Anyone who wants to combine AI + automation + market data 🟢 Customize easily: Edit your stock list or news focus inside the Agent prompt 📨 Email ready: Just plug in your Gmail credentials and you’re good to go ⏱️ 10-minute setup — no coding required!

This n8n template helps you automatically discover, analyze, and track trending topics and videos on YouTube using an AI-powered agent. Use cases are many: This workflow is perfect for YouTube creators needing fresh video ideas, digital marketers scouting new campaign topics, social media managers who want to catch trends early, and researchers who want to analyze what’s viral. How It Works The workflow starts whenever a chat message is received (e.g., a trend question, a topic prompt, or a request for insights). Incoming chat is routed to the AI Agent – Trend Explorer node: First, the agent triggers the Workflow – YouTube Search tool to gather the latest trending topics and keywords from YouTube. Next, the agent supplies this real-time YouTube data to the OpenAI Chat Model for deep analysis, trend interpretation, and unique insights. To provide context-aware answers and track ongoing interests, the agent also references a Simple Memory module, recalling past queries, and user instructions. Finally, the result is a fast, data-driven, and smart trend report delivered instantly to your chat. How To Set Up Download the workflow package (including 2 .json files) and import it into your n8n interface. Set up necessary access in the following components of the AI Agent - Trend Explorer node: OpenAI Chat Model: allows API connection for trend insights. Workflow – YouTube Search: searches for trending videos based on the query. Simple Memory (optional): enhances experience for ongoing sessions. Start by sending a chat message on n8n. Check the response from the AI agent in the same chat box. Ask follow-ups, explore deeper, or trigger new searches - all in one chat thread. Requirements n8n instance (self-hosted or cloud). Set up API access to OpenAI Chat Model for chat-based AI. How To Customize Connect to your favorite chat platforms**: Easily integrate with additional chat triggers such as Telegram, Slack, or your preferred messaging app. Choose your preferred AI model**: If you want a different viewpoint, simply swap OpenAI Chat Model for Google Gemini, Claude, or any compatible LLM model in your workflow. Upgrade memory for smarter conversations: For long-term recall or more advanced, context-aware chats, replace **Simple Memory with a vector database like Pinecone or Redis. Need Help? If you’d like this workflow customized to fit your tools and platforms availability, or if you’re looking to build a tailored AI Agent for your own business - please feel free to reach out to Agent Circle. We’re always here to support and help you to bring automation ideas to life. Join our community on different platforms for support, inspiration and tips from others. Website: https://www.agentcircle.ai/ Etsy: https://www.etsy.com/shop/AgentCircle Gumroad: http://agentcircle.gumroad.com/ Discord Global: https://discord.gg/d8SkCzKwnP FB Page Global: https://www.facebook.com/agentcircle/ FB Group Global: https://www.facebook.com/groups/aiagentcircle/ X: https://x.com/agent_circle YouTube: https://www.youtube.com/@agentcircle LinkedIn: https://www.linkedin.com/company/agentcircle

This workflow is designed for content creators or AI artists who want to automate posting unique AI-generated images to their Facebook Page multiple times a day. It uses Google Gemini via LangChain to generate imaginative image prompts, and Pollinations AI to generate the images. Posts are published with hashtags and a clean caption. Who Is It For AI artists Facebook page managers Digital marketers looking for automated creative content What It Does Triggers 3x daily at 7:00, 11:00, and 17:00 (local time) Generates random AI image prompts in a retro-futuristic, cinematic, or surreal style using Google Gemini Fetches images from Pollinations AI using custom prompts Posts images automatically to your Facebook Page with hashtags Requirements n8n self-hosted or desktop (workflow uses schedule trigger) Pollinations API (no auth needed) Facebook Page with Facebook Graph API token: Required scopes: pages_manage_posts, pages_read_engagement, pages_show_list Google Gemini API Key (used via LangChain node) How to Customize Change the prompt style in the Basic LLM Chain node (promptType: define) to suit your theme. Adjust Set The Generator Image node if you want: Different image sizes (width / height) Different seed randomness Other Pollinations models (&model=kontext) Add Telegram/Twitter nodes if you want cross-posting Use Set node to allow easy user-level configuration of models, hashtags, times, etc.

n8n Template: Store Chat Data in Supabase PostgreSQL for WhatsApp/Slack Integration This n8n template captures chat data (like user ID, name, or address) and saves it to a Supabase PostgreSQL database. It’s built for testing now but designed to work with WhatsApp, Slack, or similar platforms later, where chat inputs aren’t predefined. Guide with images can be found on: https://github.com/JimPresting/Supabase-n8n-Self-Hosted-Integration/ Step 1: Configure Firewall Rules in Your VPC Network To let your n8n instance talk to Supabase, add a firewall rule in your VPC network settings (e.g., Google Cloud, AWS, etc.). Go to VPC Network settings. Add a new firewall rule: Name: allow-postgres-outbound Direction: Egress (outbound traffic) Destination Filter: IPv4 ranges Destination IPv4 Ranges: 0.0.0.0/0 (allows all; restrict to Supabase IPs for security) Source Filter: Pick IPv4 ranges and add the n8n VM’s IP range, or Pick None if any VM can connect Protocols and Ports: Protocol: TCP Port: 5432 (default PostgreSQL port) Save the rule. Step 2: Get the Supabase Connection String Log into your Supabase Dashboard. Go to your project, click the Connect button in the header. Copy the PostgreSQL connection string: postgresql://postgres.fheraruzdahjd:[YOUR-PASSWORD]@aws-0-eu-central-1.pooler.supabase.com:6543/postgres Replace [YOUR-PASSWORD] with your Supabase account password (no brackets) and replace the string before that with your actual unique identifier. Note the port (6543 or 5432)—use what’s in the string. Step 3: Set Up the n8n Workflow This workflow takes chat data, maps it to variables, and stores it in Supabase. It’s built to handle messy chat inputs from platforms like WhatsApp or Slack in production. Workflow Steps Trigger Node: "When clicking 'Test workflow'" (manual trigger). For now, it’s manual. In production, this will be a WhatsApp or Slack message trigger, which won’t have a fixed input format. Set Node: "Set sample input variables (manual)". This node sets variables like id, name, address to mimic chat data. Why? Chat platforms send unstructured data (e.g., a message with a user’s name or address). We map it to variables so we can store it properly. The id will be something unique like a phone number, account ID, or account number. Sample Agent Node: Uses a model (e.g., GeminiFlash2.0 but doesn't matter). This is a placeholder to process data (e.g., clean or validate it) before saving. You can skip or customize it. Supabase PostgreSQL Node: "Supabase PostgreSQL Database". Connects to Supabase using the connection string from Step 2. Saves the variables (id, name, address) to a table. Why store extra fields? The id (like a phone number or account ID) is the key. Extra fields like name or address let us keep all user info in one place for later use (e.g., analytics or replies). Output Node: "Update additional values e.g., name, address". Confirms the data is saved. In production, this could send a reply to the chat platform. Why This Design? Handles Unstructured Chat Data**: WhatsApp or Slack messages don’t have a fixed format. The "Set" node lets us map any incoming data (e.g., id, name) to our database fields. Scales for Production**: Using id as a key (phone number, account ID, etc.) with extra fields like name makes this workflow flexible for many use cases, like user profiles or support logs. Future-Ready**: It’s built to swap the manual trigger for a real chat platform trigger without breaking. Step 4: Configure the Supabase PostgreSQL Node In the n8n workflow, set up the Supabase PostgreSQL node: Host: aws-0-eu-central-1.pooler.supabase.com (from the connection string) Port: 6543 (or what’s in the connection string) Database: postgres User: postgres.fhspudlibstmpgwqmumo (from the connection string) Password: Your Supabase password SSL: Enable (Supabase usually requires it) Set the node to Insert or Update: Map id to a unique column in your Supabase table (e.g., phone number, account ID). Map fields like name, address to their columns. Test the workflow to confirm data saves correctly. Security Tips Limit Firewall Rules**: Don’t use 0.0.0.0/0. Find Supabase’s IP ranges in their docs and use those. Hide Passwords**: Store your Supabase password in n8n’s environment variables. Use SSL**: Enable SSL in the n8n node for secure data transfer.

When you fill out the form with business challenges and requirements GPT-4 analyzes the input and generates a customized proposal using your template System automatically creates a Google Slides presentation with personalized content Professional proposal email is sent directly to the prospect with the presentation link Set up steps Estimated time: 15-20 minutes Connect your OpenAI API key for GPT-4 access Link your Google account for Slides and Gmail integration Create your proposal template in Google Slides with placeholder variables Customize the AI prompt and email template with your branding Test with sample data and activate the workflow

This workflow allows you to collect tweets, store them in MongoDB, analyse their sentiment, insert them into a Postgres database, and post positive tweets in a Slack channel. Cron node: Schedule the workflow to run every day Twitter node: Collect tweets MongoDB node: Insert the collected tweets in MongoDB Google Cloud Natural Language node: Analyse the sentiment of the collected tweets Set node: Extract the sentiment score and magnitude Postgres node: Insert the tweets and their sentiment score and magnitude in a Posgres database IF node: Filter tweets with positive and negative sentiment scores Slack node: Post tweets with a positive sentiment score in a Slack channel NoOp node: Ignore tweets with a negative sentiment score

🧠 ICP Scoring Agent (n8n + Explorium + LLM) This workflow automates Ideal Customer Profile (ICP) scoring for any company using a combination of Explorium data and an LLM-driven evaluation framework. 🔧 How It Works Input: Company name is submitted via form. Data Enrichment: Explorium's MCP Server is used to fetch firmographic, hiring, and tech data about the company. Scoring Logic: An AI agent (LLM) applies a 3-pillar framework to assess and score the company. Output: A structured JSON or Google Doc summary is generated using the AgentGeeks formatter. 📊 Scoring System (100 points total) | Pillar | Max Points | |------------------------------|------------| | Strategic Fit | 40 | | AI / Tech Readiness | 40 | | Engagement & Reachability | 20 | 🧠 Scoring Criteria Strategic Fit**: Industry, size, use case, buyer roles Tech Readiness**: AI maturity, hiring trends, stack visibility Reachability**: Geography, contactability, data quality 🎯 Verdict Scale 🟩 90–100: Ideal ICP ✅ 70–89: Good Fit 🟨 40–69: Medium Fit ❌ < 40: Poor Fit 📦 Workflow Components Trigger**: Form submission via webhook MCP Client**: Pulls enriched company data via Explorium's MCP API AI Agent**: Uses Anthropic Claude (or other LLM) to calculate scores Output**: Results are posted to a structured endpoint (e.g. Google Doc or JSON API) 🧰 Dependencies n8n (self-hosted or cloud) Explorium MCP credentials and access LLM API (e.g., Anthropic Claude, OpenAI, etc.) Optional: AgentGeeks formatter or similar doc generator 💼 Use Case This ICP scoring system is designed for GTM and sales teams to: Automate lead prioritization Qualify accounts before outbounding Sync ICP data into CRMs, routing systems, or reporting layers 📈 Example Output in Google Doc { "company": "Acme Inc.", "score": 87, "verdict": "Good Fit", "pillars": { "strategic_fit": 35, "tech_readiness": 37, "reachability": 15 }, "summary": "Acme Inc. is a mid-sized SaaS company with strong AI hiring activity and a buyer profile aligned to enterprise IT. Moderate reachability via firmographic signals." }

This workflow is designed for dynamic and intelligent conversational capabilities. It incorporates OpenAI's GPT-4o model for natural language understanding and generation. Additional tools include SerpAPI and Wikipedia for enriched, data-driven responses. The workflow is triggered manually, and utilizes a 'Window Buffer Memory' to maintain the context of the last 20 interactions for better conversational continuity. All these components are orchestrated through n8n nodes, ensuring seamless interconnectivity. To use this template, you need to be on n8n version 1.50.0 or later.

Tags: Productivity, Education, Learning, Language Context I’m a Supply Chain Data Scientist from Paris who lived six years in China — and yes, learning Mandarin while working full-time was tough. Learning Mandarin as an adult can be very difficult, especially if you have a full-time job. With AI, you can now have a Chinese tutor available 24/7 on your phone — no excuses left! It is with this spirit that I designed this workflow to support fellow Mandarin learners with a Chinese Teacher powered by GPT-4o. >Boost your language skills with AI using N8N! 📬 For business inquiries, you can add me on LinkedIn Who is this template for? This workflow template is designed for language learners and educators who need support to learn a vocabulary list in Mandarin (or any other language) using Open AI GPT-4o, an AI agent and a Telegram Bot to interact with users. For the vocabulary list, you can use another template shared in my profile 🉑 Generate Anki Flash Cards for Language Learning with Google Translate and GPT-4o to generate the Google Sheet needed in this workflow. How does it work? The workflow loads a vocabulary list stored in your Google Sheet. The bot will: 📥 Load your vocabulary list from Google Sheets 🧠 Generate multiple-choice questions with GPT-4o ✅ Evaluate your answer and give instant feedback 🔁 Loop to the next word until you're fluent These fields will be automatically added to a Google Sheet, ready to be loaded in Anki to create flash cards. What do I need to start? This workflow does not require any advanced programming skills. Prerequisite A Google Drive Account with a folder including a Google Sheet filled with the vocabulary list you want to learn. API Credentials: Open AI API for the chat model, Google Drive API and Google Sheets API activated with OAuth2 credentials A Telegram Bot with its token recorded in the Telegram Node Credentials A Google Sheet** with two columns (initialText: words in your own language, translatedText: words in the target language) Next Steps Follow the sticky notes to set up the parameters inside each node and get ready to pump your learning skills. 🎥 Watch My Tutorial 🚀 Curious how N8N can supercharge learning or supply chain? 📬 Let’s connect on LinkedIn Notes This workflow can be used for any language. In the AI Agent prompt, you just need to replace Chinese with your language. This workflow has been created with N8N 1.82.1 Submitted: March 23th, 2025

Capture URL Screenshots Automatically from Google Sheets & Drive with ScreenshotOne & Gmail Alerts Summary This automation template streamlines the process of capturing screenshots for multiple URLs. Instead of manually visiting each URL, taking a screenshot, and organizing the results, this workflow automates everything. When a spreadsheet is added to a designated Google Drive folder, the template extracts URLs from the column named "Url." These URLs are then processed through ScreenshotOne to capture screenshots, which are saved back to the same folder. Finally, an email notification is sent via Gmail with a link to the folder containing the screenshots. Problem Solved This template addresses the challenge of manual screenshot capture for multiple URLs. Without this automation, a user would need to: Open each URL from a spreadsheet. Take a screenshot manually. Save each screenshot with an appropriate name. Organize the screenshots in a folder. Notify stakeholders when the process is complete. These steps are not only time-consuming but also repetitive, especially when handling a large number of URLs. Who Can Benefit: Digital Marketers:** Monitor website appearances for competitive analysis or to track campaign landing pages. Web Developers/Designers:** Capture screenshots of multiple websites for inspiration or reference. QA Teams:** Document the visual state of web pages during various stages of development. SEO Specialists:** Track visual changes to websites they are optimizing. Content Managers:** Monitor how content appears across various web properties. Prerequisites Google Drive Node:** Must have appropriate permissions to create and access folders. Connected Google Sheets Node:** To extract URLs from the spreadsheet. Authenticated Gmail Node:** For sending notifications. ScreenshotOne Account:* Either a free or paid plan depending on volume needs, along with an *Access key**. Ensure you replace the placeholder --YOUR ACCESS KEY-- with your generated access key in the "Get Screenshots" node. Workflow Details Step 1: Google Drive Integration Trigger Node:** Monitors a specific folder in Google Drive. When a spreadsheet is added, the workflow is initiated. Step 2: Google Sheets Processing Google Sheets Node:** Extracts URLs from the column named "Url." Step 3: Screenshot Capture Get Screenshots Node:** Sends each extracted URL to ScreenshotOne to capture screenshots. Step 4: Saving Screenshots and Notifications Google Drive Node:** Saves the captured screenshots back into the same folder. Gmail Node:** Sends an email notification with a link to the folder, alerting stakeholders that the screenshots are ready. Customization Guidance Folder Monitoring: The workflow is set to monitor a specific Google Drive folder. It can be customized by selecting a different folder in the node settings. Spreadsheet Structure: While the template expects a spreadsheet with a column named "Url." for extracting URLs, users can add additional columns (e.g., titles, categories, or tags) and modify the workflow to utilize them as needed. Email Settings: Customize the recipient, subject, and body of the notification email to suit your needs. If required, enable optional notifications for different stakeholders. ScreenshotOne Access Key & Configurations: A valid ScreenshotOne Access key is required to capture screenshots. Users can further refine screenshot settings (e.g., viewport size, device emulation, or delay timing) by exploring the available options in the ScreenshotOne API documentation.

This automation fetches the latest article from a WordPress blog, summarizes it using OpenAI, and sends the summary to a list of subscribers via email. Ideal for content creators and bloggers who want to distribute digestible content without manual effort. Use Case Perfect for: • Newsletter creators • Content marketers • Bloggers • Knowledge managers Nodes Used • Schedule Trigger • HTTP Request • Set • OpenAI • Google Sheets • Email (Gmail/SMTP) • IF • SplitInBatches Workflow Steps Trigger: Starts on a schedule (e.g., daily at 9:00 AM). Fetch Blog Post: Retrieves the most recent post from a WordPress blog via HTTP Request. Extract Fields: A Set node extracts the title, link, and content. Summarize Article: OpenAI processes the article and returns a 3-point summary. Fetch Subscribers: Google Sheets reads email addresses from a subscriber list. Loop Emails: SplitInBatches and Send Email nodes loop through subscribers. Conditional Logic: IF node skips articles shorter than 300 words. Credentials Required • OpenAI API Key (for content summarization) • Google Sheets OAuth2 (to read subscriber emails) • Gmail or SMTP (for sending emails) Test Instructions Replace blog URL in HTTP Request node. Connect OpenAI API key. Link your Google Sheet with a column named Email. Set up Gmail or SMTP credentials. Run manually for testing, then activate schedule.