Workflow Templates

What this workflow does Front-door chat orchestrator that delegates calendar requests to a separate Sub-Agent workflow which holds Google Calendar tools (Get, Create, Delete). Keeps the agent persona and memory in the Parent for clean separation of concerns. Pipeline: Chat Trigger → Parent Agent ("Albert") → sub_agent_cal (Execute Workflow Tool) → Child Sub-Agent → Google Calendar Category: Productivity / Calendar / Agentic\ Time to set up: ~10--15 minutes\ Difficulty: Intermediate\ Cost: Mostly free (n8n CE; OpenAI + Google Calendar usage as configured) * What you'll need n8n with chat trigger enabled. OpenAI credentials. The companion template: Agentic Google Calendar Assistant --- Sub-Agent (Calendar Tools). After importing both, open this Parent and re-select the Sub-Agent in the toolWorkflow node. * Set up steps Import this Parent workflow. Import the Sub-Agent workflow (Template B). In the Parent, open sub_agent_cal (Tool → Workflow) and select the imported Sub-Agent workflow. Ensure the input mapping passes: chatInput → text sessionId → sessionid Add your OpenAI credential to the OpenAI Chat Model node. Activate the Parent workflow. * Testing "Create a meeting tomorrow 3--4pm called 'Product Sync'" → Sub-Agent should create the event and the agent should confirm. "What's on my calendar this week?" → Lists events. "Delete my 'Dentist' appointment on Thursday" → Finds and deletes the event.

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. Who’s it for Community managers, content marketers, and builders who want a daily, skimmable update from a subreddit—automatically summarized, formatted, and cross-posted to DEV Community. Here is a Link to video hackathon detailing this build. What it does Collects fresh posts from a subreddit (seeded via RSS). Uses the Bright Data node to batch-scrape each post for richer fields (upvotes, comment count, comments). Flattens comments/replies with JMESPath and trims payload size. Summarizes into a Morning Brew–style brief (Top Stories, Quick Hits, Community Q\&A, Comment Spotlight). Converts to clean Markdown and publishes to DEV with HTTP Request. Optional: emails the same digest via Gmail. How to set up Trigger: Start with Manual Trigger; swap to Cron (daily) when ready. RSS → URLs: Set the subreddit RSS of your choice, just add .rss to the end of the subreddit URL. Update AI Prompt to fit your needs Requirements DEV Community API key. Bright Data account + the Bright Data api key Found Here. Optional: LLM provider credentials (OpenAI, Gemini). How to customize Swap DEV publishing for email/Slack; or post both. Add more subreddits and dedupe by URL. Best practices No hardcoded API keys**—use credentials. Pin long-running outputs while building to save credits. Only collect publicly available data with Bright Data.

Done-For-You Social Media Trend Tracker for Content Creators | Instant AI Video Ideas 💥 What It Does This pre-built n8n workflow is your ultimate shortcut to viral content. It automatically scouts the web for trending social media topics and generates hyper-relevant video ideas, complete with engaging hooks and calls to action, directly from the latest trends. No more endless scrolling or brainstorming sessions – just plug in and receive daily, actionable content inspiration delivered straight to your Discord channel. Stop missing out on viral trends and start creating content that captivates your audience from day one, effortlessly. This fully installed automation transforms your content strategy, giving you an unfair advantage in the crowded digital landscape. ⚙️ Key Features ⚡ Instant deployment: Pre-configured n8n workflow, ready to run in minutes. 🧠 AI-powered content engine: Generates viral video ideas with hooks & CTAs (powered by OpenAI). 📈 Automated trend discovery: Daily insights from top social platforms without manual research. 💬 Discord integration: Delivers actionable ideas directly to your team or private channel. 🚀 Zero-setup solution: No coding, no complex API configurations required. 😩 Pain Points Solved Sick of endless trend research and content ideation headaches? Tired of missing out on viral opportunities and falling behind competitors? Frustrated with complex API setups and coding your own automations? Struggling to consistently produce fresh, engaging content that performs? Wasting valuable time on manual content planning and brainstorming? 📦 What’s Included Fully configured n8n workflow file (.json) Step-by-step installation & connection guide Pre-written AI prompt for optimal video idea generation Dedicated support to ensure seamless launch 🚀 Call to Action Get your viral content ideas delivered daily. No setup. No stress. 🏷️ Optimized Tags done for you system, ai automation, n8n workflow, social media trends, content ideas, viral video, tiktok content, youtube shorts, instagram reels, discord bot, pre built workflow, instant download, marketing automation

n8n Workflow: WhatsApp Lead Nurturing (MQL) 🔄 Purpose This workflow fetches unqualified leads from Postgres at defined retry intervals, sends personalized WhatsApp template messages via Gallabox API, and logs message activity while updating lead status in the database. 🧩 Workflow Structure Schedule Trigger Type: n8n-nodes-base.scheduleTrigger Runs the workflow automatically at set intervals (seconds-based). Entry point of the workflow. Execute a SQL query Type: n8n-nodes-base.postgres Fetches leads from mql_contacts that: Have count = 0, 1, 2, or 3. Respect time delays: count=1 → after 3 minutes count=2 → after 5 minutes count=3 → after 8 minutes Must have disposition = unqualified. Loop Over Items4 Type: n8n-nodes-base.splitInBatches Iterates over each lead individually. Ensures one-by-one processing. Code1 Type: n8n-nodes-base.code Selects message content based on: Lead’s model (nexus, magnus, reo, general). Current count (0–3). Ensures personalized, varied message text. new_lead_4 Type: n8n-nodes-base.httpRequest Sends WhatsApp template message through Gallabox API. Dynamic fields: Lead’s name and phone. Message details selected from Code1. Quick reply buttons: Show Brochure, Get Showroom Location, Not Interested. Insert rows in a table4 Type: n8n-nodes-base.postgres Inserts a record into mql_logs. Captures: Phone, name, disposition. Message count, message_id, timestamps. Gallabox API response (status, code). Update rows in a table4 Type: n8n-nodes-base.postgres Updates mql_contacts: Increments count by 1. Updates last_message_sent timestamp. Matches using phone number. Sticky Notes Provide inline documentation: SQL query purpose. Message matrix explanation. Gallabox API role. Postgres update/logging details. ⚙️ Data Flow Summary Trigger** → Runs every X seconds SQL Query** → Fetches eligible leads (unqualified, retry intervals) Loop** → Processes each lead sequentially Code1** → Chooses personalized message based on model & count HTTP Request** → Sends WhatsApp template via Gallabox Insert Log** → Stores activity in mql_logs Update Contact** → Updates count & last sent in mql_contacts Cycle repeats** until all leads are processed 📊 Use Case Automates WhatsApp drip campaigns for unqualified leads. Respects retry intervals to avoid spamming. Uses personalized message variations based on product model & retry count. Provides full traceability with logs and lead updates.

Automatically Send Monthly Sales Reports from Square via Outlook What It Does This workflow automatically connects to the Square API and generates a monthly sales summary report for all your Square locations. The report matches the figures displayed in Square Dashboard > Reports > Sales Summary. It's designed to run monthly and pull the previous month’s sales into a CSV file, which is then sent to a manager/finance team for analysis. This workflow builds on my previous template, which allows users to automatically pull data from the Square API into n8n for processing. (See here: https://n8n.io/workflows/6358) Prerequisites To use this workflow, you'll need: A Square API credential (configured as a Header Auth credential) A Microsoft Outlook credential How to Set Up Square Credentials: Go to Credentials > Create New Choose Header Auth Set the Name to Authorization Set the Value to your Square Access Token (e.g., Bearer <your-api-key>) How It Works Trigger: The workflow runs on the 1st of every month at 8:00 AM Fetch Locations: An HTTP request retrieves all Square locations linked to your account Fetch Orders: For each location, an HTTP request pulls completed orders for the previous calendar month Filter Empty Locations: Locations with no sales are ignored Aggregate Sales Data: A Code node processes the order data and produces a summary identical to Square’s built-in Sales Summary report Create CSV File: A CSV file is created containing the relevant data Send Email: An email is sent using Microsoft Outlook to the chosen third party Example Use Cases Automatically send monthly Square sales data to management for forecasting and planning Automatically send data to an external third party, such as a landlord or agent, who is paid via commission Automatically send data to a bookkeeper for entry into QuickBooks How to Use Configure both HTTP Request nodes to use your Square API credential Set the workflow to Active so it runs automatically Enter the email address of the person you want to send the report to and update the message body If you want to remove the n8n attribution, you can do so in the last node Customization Options Add pagination to handle locations with more than 1,000 orders per month Adjust the date filters in the HTTP node to cover the full calendar month (e.g., use Luxon or JavaScript to calculate start_date and end_date) Why It's Useful This workflow saves time, reduces manual report pulling from Square, and enables smarter automation around sales data — whether for operations, finance, or performance monitoring.

What It Does This workflow lets users create Google Calendar events through natural chat messages — no forms, no clicking around, just type like you're talking to a friend. For example, you can say: “Lunch with John tomorrow at 12:30” and it’ll auto-create a calendar event with the correct title, time, and duration. How It Works Trigger: Chat Message Received The flow starts with a chat interface node (When chat message received) that listens for incoming user messages like: “Book dentist next Wed 10am” “Schedule Zoom call with Jane Friday 3–4pm” AI Agent with Scheduling Instructions The message is handed off to a Langchain-powered AI Agent that: Parses the message Resolves relative time (like "next Tuesday") into actual ISO timestamps Generates a title (summary) if not provided by the user Ensures all required fields are correctly filled Handles vague messages by asking a single clarifying question LLM (OpenAI) The agent is powered by gpt-4o-mini (or your preferred OpenAI model). You can customize this or swap it out. Google Calendar Integration Once the AI agent has structured the event details, it uses the Google Calendar Tool Node to create the event via your connected Google account. (Optional) A response node (Respond to Chat) is included (but currently disabled) — you can enable it to send a confirmation message back to the user like: “📅 Booked: Lunch with John on Aug 30 at 12:30 PM Asia/Manila.” Requirements To make this workflow functional, you need to connect: 🔐 Google Calendar OAuth2 credentials Add your Google account under Credentials > Google Calendar OAuth2 API. 🧠 OpenAI credentials Provide your OpenAI API key (used for message interpretation and slot filling). Customization Ideas Add email collection to invite attendees Expand to support recurring events Add error handling or fallback if date parsing fails Connect to Slack or Telegram for real-time event booking Important Note on Credentials This template does not include any personal API keys or credential tokens. You’ll need to connect your own Google and OpenAI credentials after import.

Replace YOUR_API_KEY with your actual SerpApi key. 2️⃣ Set Up OpenAI Connection Go to OpenAI Platform Navigate to Billing and ensure your account has credits/funding Copy your API Key into the OpenAI credentials in n8n 🧠 Workflow Breakdown Chat Trigger → User enters a financial question (e.g., “What’s the current price of Tesla?”). HTTP Request (SerpApi Finance Search) → Fetches the latest market data for the requested ticker or index. OpenAI Node → Takes both the raw financial data and the user’s query, then formulates a natural language response. Output → Returns a clear, conversational answer that can be displayed in chat, Slack, or another integration. 🎛️ Customization Guidance Multiple Tickers**: Update the workflow to query multiple tickers (e.g., TSLA, AAPL, AMZN) and return a combined report. Scheduling: Add a **Schedule Trigger to run this workflow every morning and send a market recap. Delivery Channels**: Use Slack, Email, or Google Sheets nodes to distribute reports automatically. Extended Data**: Adjust the SerpApi query to include more than prices — e.g., company info, market news, or related tickers. Custom Prompts**: Change the OpenAI system prompt to make the chatbot more formal (for reporting) or casual (for quick insights). 💬 Example Questions & Responses Question: “What’s the current price of the S&P 500?” Expected Response: “The S&P 500 (^GSPC) is currently trading at 4,725.13, down 0.8% today.” Question: “Summarize the performance of Tesla and Apple today.” Expected Response: Tesla (TSLA): $238.45, up 1.5% Apple (AAPL): $192.11, down 0.3% Question: “Give me a quick market recap.” Expected Response: “Markets are mixed today — the S&P 500 is slightly down, while tech stocks like Tesla are showing gains. Apple dipped slightly after earnings news.” 📬 Contact Need help customizing this workflow (e.g., multiple tickers, daily summaries, or integrating into dashboards)? 📧 robert@ynteractive.com 🔗 Robert Breen 🌐 ynteractive.com

This workflow solves a critical problem in AI chat implementations: handling multiple rapid messages naturally without creating processing bottlenecks. Unlike traditional approaches where every user waits in the same queue, our solution implements intelligent conditional buffering that allows each conversation to flow independently. Key Features: Aggregates rapid user messages (like when someone types multiple lines quickly) into single context Only the first message in a burst waits - subsequent messages skip the queue entirely Each user session operates independently with isolated Redis queues Reduces LLM API calls by 45% through intelligent message batching Maintains conversation memory for contextual responses Perfect for: Customer service bots, AI assistants, support systems, and any chat application where users naturally send multiple messages in quick succession. The workflow scales linearly with users, handling hundreds of concurrent conversations without performance degradation. Some Use Cases: Customer support systems handling multiple concurrent conversations AI assistants that need to understand complete user thoughts before responding Educational chatbots where students ask multi-part questions Sales bots that need to capture complete customer inquiries Internal company AI agents processing complex employee requests Any scenario where users naturally communicate in message bursts Why This Template? Most chat buffer implementations force all users to wait in a single queue, creating exponential delays as usage scales. This template revolutionizes the approach by making only the first message wait while subsequent messages flow through immediately. The result? Natural conversations that scale effortlessly from one to hundreds of users without compromising response quality or speed. Prerequisites n8n instance (v1.0.0 or higher) Redis database connection OpenAI API key (or alternative LLM provider) Basic understanding of webhook configuration Tags ai-chat, redis, buffer, scalable, conversation, langchain, openai, message-aggregation, customer-service, chatbot

📄 Description This workflow automates the extraction of structured invoice data from PDF files sent via Telegram and stores it in Airtable. It leverages GPT-4o for intelligent parsing and includes conversational memory for a seamless user experience. Designed for businesses and freelancers who receive invoices digitally and want to streamline their record-keeping. ⚙️ How It Works Telegram Trigger – Listens for incoming messages and PDF attachments. Switch Node – Filters messages to ensure only PDFs are processed. Extract from File – Parses the PDF content for text extraction. Edit Fields – Prepares the extracted data for AI processing. AI Agent (GPT-4o) – Orchestrates the workflow, prompts the user for missing info, and extracts structured data. Simple Memory – Maintains conversational context across sessions. Create Invoice (Airtable Tool) – Creates a new invoice record in Airtable. Create Line Item (Airtable Tool) – Adds individual line items linked to the invoice. Telegram Response – Sends confirmation back to the user. 🔐 Required Credentials To run this workflow successfully, you’ll need: Telegram Bot Token** (via @BotFather) OpenAI API Key** (with GPT-4o access) Airtable API Key** and access to: Base: Invoice Tracker Proper Tables: Invoices and Line Items 🧰 Airtable Structure Invoices Table Fields: Invoice Number Date Supplier Supplier Address Tax ID PO Number Due Date Receiver Name Receiver Address Delivery Date Total Tax Total Amount Line Items Table Fields: Product Code Description Unit Price Quantity Unit Type Sub Total Invoice (linked) 🧠 Features AI-powered invoice parsing PDF text extraction Airtable record creation with relational linking Telegram-based user interaction Conversational memory Error handling and data validation

What It Does This workflow automatically connects to the Square API and generates a daily sales summary report for all your Square locations. The report matches the figures displayed in Square Dashboard > Reports > Sales Summary. It's designed to run daily and pull the previous day's sales into a Google Sheet for easy analysis and reporting. This workflow builds on my previous template, which allows users to automatically pull data from the Square API into N8N for processing. (See here: https://n8n.io/workflows/6358) Prerequisites To use this workflow, you'll need: A Square API credential (configured as a Header Auth credential) A Google Sheets credential How to Set Up Square Credentials: Go to Credentials > Create New Choose Header Auth Set the Name to "Authorization" Set the Value to your Square Access Token (e.g., Bearer <your-api-key>) How It Works Trigger – The workflow runs daily at 4:00 AM Fetch Locations – An HTTP request retrieves all Square locations linked to your account Fetch Orders – For each location, an HTTP request pulls completed orders for the specified report_date Filter Empty Locations – Locations with no sales are ignored Aggregate Sales Data – A Code node processes the order data and produces a summary identical to Square’s Sales Summary report Append to Google Sheets – The data will automatically be appended to an existing Google sheet Example Use Cases Automatically store daily sales data in Google Sheets for analysis and historical tracking Automatically create charts or visualizations from the imported data Build weekly/monthly reports after running for multiple days Quickly calculate commissions or rent payments based on sales volume How to Use Configure both HTTP Request nodes to use your Square API credential Set the workflow to Active so it runs automatically Select the Google Sheet you want to import data into, and map the data to your columns Customization Options Add pagination to handle locations with more than 1,000 orders per day Expand the workflow to save or send the report output via other integrations (email, database, webhook, etc.) Why It's Useful This workflow saves time, reduces manual report pulling from Square, and enables smarter automation around sales data—whether for operations, finance, or performance monitoring.

Sales Tax Calculator API Integration: Automate Tax Calculation with Google Sheets & RapidAPI Effortlessly calculate and store sales tax rates based on user address data using the Sales Tax Calculator API on RapidAPI. Automate the process, format the data, and store results in Google Sheets for easy access.** Workflow Overview: This automation workflow integrates the Sales Tax Calculator API from RapidAPI to calculate and store sales tax rates based on user-provided address information. The workflow is designed to automate tax calculation, streamline data processing, and save results in a Google Sheets document for future reference. Node-by-Node Explanation: 1. On Form Submission: Trigger: This node listens for form submissions, capturing the user’s address data (street, city, state, zip). 2. Calculate Sales Tax: Action: Sends a POST request to the Sales Tax Calculator API (via RapidAPI) to fetch tax rates based on the submitted address data. 3. Reformat API Response: Processing: Processes and reformats the data received from the API, structuring the tax agencies, rates, and total tax calculations into rows. 4. Append to Google Sheets: Store: Appends the reformatted tax information into a Google Sheets document for easy storage and future analysis. Use Case: This workflow is ideal for businesses or individuals who need to automatically calculate sales tax based on customer-provided address information. It can be used in any e-commerce platform, accounting system, or sales management tool. Benefits: Automation: Streamline the tax calculation process by automatically calculating and storing tax rates based on user inputs. Real-Time Data: Ensure up-to-date tax rates are used for every transaction or form submission. Easy Data Access: Tax rates and details are stored in Google Sheets, providing easy access and better organization for future reference. Efficient Workflow: Saves time and reduces the possibility of human error by automating the entire process from data collection to storage. Integration with RapidAPI: This workflow is powered by the Sales Tax Calculator API from RapidAPI, which ensures accurate and real-time tax calculations based on user addresses. Key Features of the Sales Tax Calculator API: Fetch tax rates based on various address details (street, city, state, zip). Reliable and fast service via RapidAPI, ensuring smooth API integrations. Provides tax rate data for multiple jurisdictions (states, cities, etc.). Start using the Sales Tax Calculator API on RapidAPI today and streamline your sales tax process. 🔑 How to Get API Key from RapidAPI Sales Tax Calculator Follow these steps to get your API key and start using it in your workflow: Visit the API Page 👉 Click here to open Sales Tax Calculator on RapidAPI Log in or Sign Up Use your Google, GitHub, or email account to sign in. If you're new, complete a quick sign-up. Subscribe to a Pricing Plan Go to the Pricing tab on the API page. Select a plan (free or paid, depending on your needs). Click Subscribe. Access Your API Key Navigate to the Endpoints tab. Look for the X-RapidAPI-Key under Request Headers. Copy the value shown — this is your API key. Use the Key in Your Workflow In your n8n workflow (HTTP Request node), replace: "x-rapidapi-key": "your key" with: "x-rapidapi-key": "YOUR_ACTUAL_API_KEY" Keywords: Sales Tax Calculator, Sales Tax API, RapidAPI, Tax Calculation, Google Sheets Integration, Automation, API Integration

Amazon Price Tracker & Competitor Monitoring Workflow (Apify + Google Sheets) This n8n workflow automates Amazon price tracking and competitor monitoring by scraping product pricing via Apify and updating your Google Sheet every day. It removes manual price checks, keeps your pricing data always fresh, and helps Amazon sellers stay ahead in competitive pricing, Buy Box preparation, and daily audits. 💡 Use Cases Automatically track prices of your Amazon products Monitor competitor seller prices across multiple URLs Maintain a daily pricing database for reporting and insights Catch sudden competitor undercutting or pricing changes Support Buy Box analysis by comparing seller prices Scale from 10 to 1000+ product URLs without manual effort 🧠 How It Works Scheduled Trigger** runs the workflow every morning Google Sheets node** loads all product rows with seller URLs Loop node** processes each item one-by-one Apify Actor node** triggers the Amazon scraper HTTP Request node** fetches the scraped result from Apify JavaScript node** extracts, cleans, and formats price data Update Sheet node** writes the fresh prices back to the right row Supports additional price columns for more sellers or metrics ➕ Adding New Competitor Columns (Step-by-Step) 1. Add a new column in Google Sheets Add two new columns: competitor_url_3 price_comp_3 2. Update the Apify Actor (inside n8n) In the Apify Actor node, pass the new competitor URL: "competitor_url_3": {{$json.competitor_url_3}} This ensures Apify scrapes the additional competitor product page. 3. Update your Code (JavaScript) node Inside the Code node, extract the new competitor’s price from the Apify JSON and attach it to the output: const price_comp_3 = item?.offers?.[2]?.price || null; item.price_comp_3 = price_comp_3; return item; (Adjust the index [2] based on the Apify output structure.) Update the Google Sheet “Update Row” node To save the new values into your Sheet: Open your Google Sheets Update Row node Scroll to Field Mapping Map Columns with New Data Hit the "Save & Execute" Button.🚀 ⚡ Requirements Apify account (free tier is enough) Apify "Amazon Product Scraper" API (Costs $40/month - 14-day free trial) Google Sheet containing product URLs Basic credentials setup inside n8n 🙌 Want me to set it up for you? I’ll configure the full automation — Apify scraper, n8n workflow, Sheets mapping, and error handling. Email me at: imarunavadas@gmail.com Automate the boring work and focus on smarter selling. 🚀