Workflow Templates

This workflow fetches live financial data from SerpApi and generates a daily market recap using OpenAI. ⚙️ Setup Instructions 1️⃣ Set Up SerpApi Connection Create a free account at SerpApi Copy your API Key from the SerpApi dashboard In n8n → Credentials → New → SerpApi Paste your API Key → Save In the workflow, select your SerpApi credential in the Finance Search node. 2️⃣ Set Up OpenAI Connection Go to OpenAI Platform Navigate to OpenAI Billing Add funds to your billing account Copy your API key into the OpenAI credentials in n8n 🧠 How it works SerpApi Finance Search** → pulls market data (example: S&P 500, ticker ^GSPC) OpenAI Model** → summarizes into a daily report with a paragraph + key bullet points 📬 Contact Need help customizing (e.g., pulling multiple tickers, exporting to Google Sheets, or sending Slack/Email updates)? 📧 robert@ynteractive.com 🔗 Robert Breen 🌐 ynteractive.com

This workflow implements a lightweight authentication system for n8n web portals using Google Sheets as a simple user and session store. It supports email-based registration, username and password login, one-click magic link authentication, and cookie-based session management. How it works Users register with an email address through a form. The workflow generates a password and a one-time authentication token. User credentials and token are stored in Google Sheets. An email is sent with login credentials and a magic link. Users can log in with username and password or click the magic link. The /auth endpoint validates the token, creates a session id (sid), sets it as an HttpOnly cookie, and invalidates the token. The /profile endpoint reads the sid cookie, verifies the session in Google Sheets, and displays a protected profile page. Set up steps Create a Google Sheet with columns: username, password, role, token, sid. Replace YOUR_SPREADSHEET_ID with your Google Sheet ID in all Google Sheets nodes. Replace YOUR_DOMAIN with your n8n instance domain in redirect URLs and email links. Configure Gmail or SMTP credentials in the email node. Ensure your n8n instance is served over HTTPS so Secure cookies function correctly. This template is suitable for small internal portals, admin dashboards, or proof-of-concept authentication systems built entirely within n8n.

How it works This workflow automatically discovers and analyzes backlinks for any website, providing comprehensive SEO insights and competitive intelligence using AI-powered analysis. Key Steps Website Input - Accepts target URLs via webhook or manual input for backlink analysis. Backlink Discovery - Scrapes and crawls the web to find all backlinks pointing to the target website. AI-Powered Analysis - Uses GPT-4 to analyze backlink quality, relevance, and SEO impact. Data Processing & Categorization - Cleans, validates, and automatically categorizes backlinks by type, authority, and relevance. Database Storage - Saves processed backlink data to PostgreSQL database for ongoing analysis and reporting. API Response - Returns structured summary with backlink counts, domain authority scores, and SEO insights. Set up steps Setup time: 8-12 minutes Configure OpenAI credentials - Add your OpenAI API key for AI-powered backlink analysis. Set up PostgreSQL database - Connect your PostgreSQL database and create the required table structure. Configure webhook endpoint - The workflow provides a /analyze-backlinks endpoint for URL submissions. Customize analysis parameters - Modify the AI prompt to include your preferred SEO metrics and analysis criteria. Test the workflow - Submit a sample website URL to verify the backlink discovery and analysis process. Set up database table - Ensure your PostgreSQL database has a backlinks table with appropriate columns. Features Comprehensive backlink discovery**: Finds all backlinks pointing to target websites AI-powered analysis**: GPT-4 analyzes backlink quality, relevance, and SEO impact Automatic categorization**: Backlinks categorized by type (dofollow/nofollow), authority level, and relevance Data validation**: Cleans and validates backlink data with error handling Database storage**: PostgreSQL integration for data persistence and historical tracking API responses**: Clean JSON responses with backlink summaries and SEO insights Competitive intelligence**: Analyzes competitor backlink profiles and identifies link building opportunities Authority scoring**: Calculates domain authority and page authority metrics for each backlink

Workflow Description: Turn a simple text idea into production-ready icons in seconds. With this workflow, you input a subject (e.g., “Copy”, “Banana”, “Slack Mute”), select a style (Flat, 3D, Cartoon, etc.), and off it goes. Here’s what happens: A form trigger collects your icon subject, style and optional background. The workflow uses an LLM to construct an optimised prompt. An image-generation model (OpenAI image API) renders a transparent-background, 400×400 px PNG icon. The icon is automatically uploaded to Google Drive, and both a download link and thumbnail are generated. A styled completion card displays the result and gives you a “One More Time” option. Perfect for designers, developers, no-code creators, UI builders and even home-automation geeks (yes, you can integrate it with Home Assistant or Stream Deck!). It saves you the manual icon-hunt grind and gives consistent visual output across style variants. 🔧 Setup Requirements: n8n instance (self-hosted or cloud) OpenAI API access (image generation enabled) Google Drive credentials (write access to a folder) (Optional) Modify to integrate Slack, Teams or other file-storage destinations ✅ Highlights & Benefits: Fully automated prompt creation → consistent icon quality Transparent background PNGs size-ready for UI use Saves icons to Drive + gives immediate link/thumbnail Minimal setup, high value for creative/automation workflows Easily extendable (add extra sizes, style presets, share via chat/bot) ⚠️ Notes & Best-Practices: Check your OpenAI image quota and costs - image generation may incur usage. Confirm Google Drive folder permissions to avoid upload failures. If you wish a different resolution or format (e.g., SVG), clone the image node and adjust parameters.

Text-to-Image Generator with OpenAI What It Is This is an automated text-to-image generation system that converts simple subject descriptions into AI-generated photos using OpenAI's image generation technology. Setup The system works through a streamlined workflow: You input a subject or brief description into a designated note field The system automatically expands your simple subject into a detailed, comprehensive prompt This enhanced prompt is sent to OpenAI's image generator Once the image is created, it is automatically saved to your Google Drive for easy access and storage You receive a notification in Slack to view it

Personal AI Assistant on Telegram Who It’s For: This workflow is designed for developers, founders, community managers, and automation enthusiasts who want to bring a personal AI assistant directly into their Telegram chat. It lets users interact naturally—either through text or voice messages—and get instant, AI-powered replies without switching apps or opening dashboards. ⚡ What It Does / How It Works 📥 Message Trigger: A Telegram Trigger node listens for incoming messages. 🧭 Smart Routing: A Switch node decides if the user sent a text or voice message. 🗣️ Voice to Text: If it’s voice, the workflow uses OpenAI Whisper Transcription to convert it into text. 🧠 AI Processing: The text is passed to an AI Agent powered by GPT-4.1-mini to understand intent and craft a response. 💬 Reply: The bot sends a clean, structured, and polite answer back to the user on Telegram. 🧠 Memory: A buffer memory node keeps short-term conversation history for a more contextual, human-like experience. 🧰 How to Set It Up: Telegram Integration Create a bot via @BotFather on Telegram. https://telegram.me/BotFather Add your Telegram API Key to n8n credentials. Connect the Telegram Trigger and Send a Message nodes. OpenAI Setup Get your API key from platform.openai.com. https://platform.openai.com/api-keys Configure the OpenAI Chat Model and Transcribe a Recording nodes with GPT-4.1-mini. Workflow Logic Use the Switch node to detect message type (text or voice). Route voice messages through transcription before sending them to the AI agent. Add Simple Memory to maintain short conversational context. Go Live Activate the workflow. Send a message or voice note to your bot. Get instant replies from your personal AI assistant. 🚀 🛡️ Requirements: n8n (self-hosted or cloud) Telegram Bot API key OpenAI API key (for GPT-4.1-mini) Basic understanding of n8n nodes and connections 🌟 Why Use This Workflow: ✅ Hands-free experience: Just talk or type. 🧠 AI-powered responses: Natural language understanding with GPT. ⚡ Real-time interaction: Fast replies via Telegram. 🔁 Memory-aware conversations: Feels more human. 🧩 Modular design: Easily extend to other AI tools or platforms.

Conversational analytics with Google Sheet and C1 by Thesys Turn any Google Sheet into a chat-powered dashboard. Ask questions in plain English and get interactive charts, tables, and UI (not just text) powered by C1 by Thesys. Outcome: faster insights from spreadsheet data. No filters, pivot tables, or manual chart building. Check out a working demo of this template here. Example Use Cases You can use this setup for many real-world scenarios, such as: Lead Tracking Upload your leads data to Google Sheets Ask questions like: “How many new leads came from LinkedIn?” “Which region generated the most leads?” Marketing Campaign Analysis Store campaign performance data in a sheet Ask: “Which campaign had the highest conversion rate?” “Compare email vs paid ads performance” How it works User sends a prompt C1 model based on prompt will use CoinGecko MCP to fetch live data C1 Model generates a UI Schema Response Schema is rendered as UI using Thesys GenUI SDK on the frontend Setup Make sure you have the following: 1. Thesys API Key You’ll need an API key to authenticate and use Thesys services. 👉 Get your key here 2. Google Sheet as a Data Source Prepare a Google Sheet that contains your data: Column headers in the first row Clean, structured data (no merged cells) Example columns: date campaign_name leads cost Facing setup issues? If you get stuck or have questions: 💬 Join the Thesys Community 📧 Email support: support@thesys.dev

This n8n workflow automates outbound phone calls to new leads using VAPI, with built-in timezone detection to ensure you're only calling during business hours. Use cases include appointment setting, lead qualification, follow-up surveys, payment reminders, and sales outreach—anywhere you need to scale phone conversations without scaling headcount. Good to know You'll need a VAPI phone number and configured voice agent before using this workflow. VAPI offers $10 free credit when you sign up (~70 minutes of calls). Create your account here. The timezone logic covers common country codes (UK, US, EU, Australia, India, UAE, Singapore, Japan). You can extend this in the Code node. How it works A new row in Google Sheets triggers the workflow (you can swap this for a webhook, form, or CRM trigger). The phone number is sanitised—stripping spaces, dashes, and brackets so it's in the correct format for dialling. The lead's timezone is determined from their country code, and the workflow checks whether it's between 8am-5pm local time. If not, it waits and retries. VAPI places the outbound call using your configured voice agent. The workflow polls VAPI's API until the call ends, then retrieves the transcript. The Google Sheet is updated to mark the lead as "Called", as well as entering the call summary, transcript, call sentiment, and other useful details from Vapi's call logs. Requirements VAPI account with a phone number and voice agent Google Sheets with columns: Phone Number, Name, Status Customising this workflow Change the trigger**: Replace Google Sheets with a webhook, n8n form, or CRM trigger (HubSpot, Pipedrive, etc.) Adjust calling hours**: Modify the IF node to change the 8am-5pm window Expand timezone coverage**: Add more country codes to the mapping in the "Get lead's timezone" Code node Add your own AI analysis**: We currently use VAPI's default call summary - but you could add an agent that extracts different insights (e.g., buying signals, objections) Route the output elsewhere**: Send results to Slack, a CRM, email, or Airtable instead of updating Google Sheets Built by Marcus Taylor (@intellagents / voiceai.guide)

Create a Fall 2025 course schedule for each student based on what they’ve already completed, catalog prerequisites, and term availability (Fall/Both). Reads students from Google Sheets → asks an AI agent to select exactly 5 courses (target 15–17 credits, no duplicates, prereqs enforced) → appends each student’s schedule to a schedule tab. 🧠 Summary Trigger:* Manual — *“When clicking ‘Execute workflow’” I/O:** Google Sheets in → OpenAI decisioning → Google Sheets out Ideal for:** Registrars, advisors, degree-planning prototypes ✅ What this template does Reads: StudentID, Name, Program, Year, CompletedCourses (pipe-separated CourseIDs) from **Sheet1 Decides: AI **Scheduling Agent chooses 5 courses per student following catalog rules and prerequisites Writes: Appends StudentID + Schedule strings to **schedule worksheet Credits target**: 15–17 total per term Catalog rules** (enforced in the agent prompt): Use Fall or Both courses for Fall 2025 Enforce AND prereqs (e.g., CS-102|CS-103 means both) Priority: Major Core → Major Elective → Gen Ed (include Gen Ed if needed) No duplicates or already-completed courses Prefer 200-level progression when prereqs allow ⚙️ Setup (only 2 steps) 1) Connect Google Sheets (OAuth2) In n8n → Credentials → New → Google Sheets (OAuth2), sign in and grant access In the Google Sheets nodes, select your spreadsheet and these tabs: Sheet1 (input students) schedule (output) > Example spreadsheet (replace with your own): > - Input: .../edit#gid=0 > - Output: .../edit#gid=572766543 2) Connect OpenAI (API Key) In n8n → Credentials → New → OpenAI API, paste your key In the OpenAI Chat Model node, select that credential and a chat model (e.g., gpt-4o) 📥 Required input (Sheet1) Columns**: StudentID, Name, Program, Year, CompletedCourses CompletedCourses**: pipe-separated IDs (e.g., GEN-101|GEN-103|CS-101) Program* names should match those referenced in the embedded catalog (e.g., *Computer Science BS, Business Administration BBA, etc.) 📤 Output (schedule tab) Columns**: StudentID Schedule → a selected course string (written one row per course after splitting) 🧩 Nodes in this template Manual Trigger* → *Get Student Data (Google Sheets)* → *Scheduling Agent (OpenAI)** → Split Schedule → Set Fields → Clear sheet → Append Schedule (Google Sheets) 🛠 Configuration tips If you rename tabs, update both Get Student Data and Append Schedule nodes Keep CompletedCourses consistent (use | as the delimiter) To store rationale as well, add a column to the output and map it from the agent’s JSON 🧪 Test quickly 1) Add 2–3 sample student rows with realistic CompletedCourses 2) Run the workflow and verify: 5 course rows per student in schedule Course IDs respect prereqs & Fall/Both availability Credits sum ~15–17 🧯 Troubleshooting Sheets OAuth error:** Reconnect “Google Sheets (OAuth2)” and re-select the spreadsheet & tabs Empty schedules:** Ensure CompletedCourses uses | and that programs/courses align with the provided catalog names Prereq violations:** Check that students actually have all AND-prereqs in CompletedCourses OpenAI errors (401/429):** Verify API key, billing, and rate-limit → retry with lower concurrency 🔒 Privacy & data handling Student rows are sent to OpenAI for decisioning. Remove or mask any fields you don’t want shared. Google Sheets retains input/output. Use spreadsheet sharing controls to limit access. 💸 Cost & performance OpenAI**: Billed per token; cost scales with student count and prompt size Google Sheets**: Free within normal usage limits Runtime**: Typically seconds to a minute depending on rows and rate limits 🧱 Limitations & assumptions Works for Fall 2025 only (as written). For Spring, update availability rules in the agent prompt Assumes catalog in the agent system message is your source of truth Assumes Program names match catalog variants (case/spacing matter for clarity) 🧩 Customization ideas Add a Max Credits column to cap term credits per student Include Rationale in the sheet for advisor review Add a “Gen Ed needed?” flag per student to force at least one Gen Ed selection Export to PDF or email the schedules to advisors/students 🧾 Version & maintenance n8n version:** Tested on recent n8n Cloud builds (2025) Community nodes:** Not required Maintenance:** Update the embedded catalog and offerings each term; keep prerequisites accurate 🗂 Tags & category Category:** Education / Student Information Systems Tags:** scheduling, registrar, google-sheets, openai, prerequisites, degree-planning, catalog, fall-term 🗒 Changelog v1.0.0** — Initial release: Sheets in/out, Fall 2025 catalog rules, prereq enforcement, 5-course selection, credits target 📬 Contact Need help customizing this (e.g., cohort logic, program-specific rules, adding rationale to the sheet, or emailing PDFs)? 📧 rbreen@ynteractive.com 🔗 Robert Breen — https://www.linkedin.com/in/robert-breen-29429625/ 🌐 ynteractive.com — https://ynteractive.com

Replace BillyBot: Free Slack Employee Birthday & Anniversary Automation Who's it for HR teams, team leaders, and operations managers looking to automate employee celebrations without expensive third-party tools like BillyBot. Perfect for startups to enterprise teams wanting to save $600-2,400+ annually while maintaining personalized, engaging employee recognition. What it does This workflow automatically monitors your employee database daily and posts AI-generated, unique celebration messages to Slack for birthdays and work anniversaries. Unlike generic bots, it creates personalized messages that never repeat, rotating through 12 different styles and tones to keep celebrations fresh and authentic. How it works Daily Check: Runs every morning at 9 AM to scan your employee Google Sheet Smart Filtering: Matches today's date against employee birthdays and joining dates Data Aggregation: Collects all celebrating employees into a single payload AI Generation: Google Gemini creates unique, heartfelt messages with proper Slack formatting Auto-Post: Sends personalized celebrations directly to your chosen Slack channel The AI ensures no two messages feel templated, calculating years of service for anniversaries and adapting tone based on tenure length. Requirements Google Sheets** with employee data (columns: NO, Name, Email, Date of Birth, Joining Date in YYYY-MM-DD format) Slack workspace** with bot permissions to post messages Google Gemini API key** (free tier included) n8n Cloud** ($20/month) or self-hosted n8n (free) Cost comparison: Save $600-2,400+ per year BillyBot pricing: $1 per employee/month 50 employees = $600/year 100 employees = $1,200/year 200 employees = $2,400/year This solution: $0-20/month (unlimited employees) Google Gemini API: FREE Google Sheets API: FREE Slack API: FREE n8n: $20/month (Cloud) or $0 (self-hosted) Your savings: 95-100% cost reduction regardless of team size. Setup instructions Create Google Sheet: Add columns: NO, Name, Email, Date of Birth, Joining Date (ensure dates are YYYY-MM-DD format) Connect Google Sheets: Authenticate your Google account in the "Get row(s) in sheet" node Set up Slack: Create a Slack bot with chat:write permission and add to your celebration channel Configure Gemini: Add your Google Gemini API key to the "Google Gemini Chat Model" node Adjust Schedule: Change trigger time in "Schedule Trigger" node (default: 9 AM daily) Select Channel: Update Slack channel in "Send a message" node to your desired celebration channel Test: Run workflow manually to verify messages post correctly Customization options Change celebration time**: Modify the Schedule Trigger to any hour (e.g., 8 AM for morning celebrations) Adjust message tone**: Edit the AI Agent system prompt to match your company culture (formal, casual, playful) Multi-channel posting**: Duplicate the Slack node to post to multiple channels (e.g., company-wide + team-specific) Add upcoming reminders**: Modify the IF node to check for celebrations within 7 days Include photos**: Extend the workflow to pull employee photos from your HR system Custom emoji styles**: Update the AI prompt to use your organization's custom Slack emojis Key features 12 rotating message styles prevent repetition Automatic tenure calculation for work anniversaries Culturally inclusive and professional tone Mobile-optimized message length (1-3 lines) Slack markdown formatting for visual appeal Scales infinitely without additional cost Note: Ensure your Google Sheet date formats are consistent (YYYY-MM-DD) for accurate date matching. The workflow processes dates in MM-DD format to match across years automatically.

Who is this workflow for? This workflow is designed for technical teams, automation owners, process auditors, and anyone who needs to document n8n workflows in a consistent, fast, and professional way—without manual work. What problem does it solve? / Use case Documenting n8n workflows is often slow and error-prone: you need to review nodes, configurations, connections, internal logic, and embedded code. This workflow automates that process by generating a complete technical report, structured and ready to share, ensuring documentation is: consistent easy to update easy to review accessible in Google Drive What this workflow does Lets you select an n8n workflow to document Extracts its structure, nodes, connections, and settings Normalizes the JSON to remove noise and keep what matters Generates a HTML technical report using an LLM (OpenAI GPT-4.1) Detects whether Code nodes exist If Code nodes exist, analyzes their logic and adds an extra technical section Creates a final Google Docs document inside a Google Drive folder High-level flow Manual workflow start Target workflow selection Workflow normalization (cleanup + structure) Main report generation with OpenAI Code node extraction Condition: Code nodes exist or not (Optional) technical analysis of Code nodes with OpenAI Merge main report + code analysis Create the final document in Google Docs Setup OpenAI Configure OpenAI credentials (API Key). The workflow uses OpenAI nodes to: generate the main report analyze Code nodes (if any) Google Drive Configure Google Drive OAuth2 credentials with write permissions Define a destination folder using a folder ID (e.g., YOUR_FOLDER_ID) The workflow uploads the final HTML as a Google Docs document n8n (access to the target workflow) If your instance requires it, configure access to read internal workflows. The workflow fetches the selected workflow using an n8n Get Workflow node. How to customize this workflow Report format:** adjust the prompt in the Generate Report node to change sections, style, or level of detail Output folder:** replace YOUR_FOLDER_ID with the real Drive folder ID Documentation strategy:** generate shorter reports for small workflows split large reports if the workflow is very big Automated triggering:** replace the manual start with a webhook trigger if you want to use an external application Final outcome A system that automatically generates a professional technical Google Docs document containing: workflow description global configuration node-by-node breakdown routing logic (conditions and branches) required credentials operational requirements risks and observations additional Code node analysis (if applicable) Do you want this workflow in Spanish? 📧 jrvillaverde@virodria.es 🔗 https://www.linkedin.com/in/ramonvillaverde

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. 🤖 AI-Powered Twitter Content Generator Transform topic ideas into ready to post Twitter drafts (text + image) using fresh web data and AI agents 🎯 What does this workflow do? This end to end automation creates complete Twitter posts by: Taking your topic input (e.g., "Agentic AI") via chat interface Generating fresh, research-backed content using AI agents: First agent uses GPT-4.1-MINI + Tavily to bypass LLM knowledge limits with real-time web data Second agent creates optimized prompt for image generation Producing custom visuals through OpenAI's gpt-image-1 Delivering polished drafts (text + image) via Gmail for review ⚙️ How it works User input: You provide a topic through chat node Content research: Agent 1 (GPT-4.1-mini + Tavily) researches current web data Generates factually fresh tweet content Visual creation: Agent 2 optimizes prompt for image generation HTTP request node calls OpenAI's gpt-image-1 model to generate the image Convert to file node converst the base64 string to a file so we can send it as an attachment Delivery: Gmail node sends compiled draft with text body + image attachment 🔑 Required setup Have a verified organization: OpenAI Org Settings OpenAI API Key: Create a Key Here Tavily API Key: Get it Here Gmail credentials: Google Cloud Console