Workflow Templates

This n8n workflow automatically sends a Telegram message whenever a new event is added to Google Calendar. It extracts key event details such as event name, description, event creator, start date, end date, and location and forwards them to a specified Telegram chat. This ensures you stay updated on all newly scheduled events directly from Telegram. Prerequisites Before setting up the workflow, ensure the following: Google Account with Google Calendar Access: The Google Calendar API must be enabled. Telegram Bot: Create a bot using BotFather on Telegram. Telegram Chat ID: Retrieve the Chat ID (personal chat or group). Use OAuth2 for Google Calendar and a Bot Token for Telegram. Steps Step 1: Google Calendar Trigger Node (Event Created Event) Click "Add Node" and search for Google Calendar. Select "Google Calendar Trigger" and add it to the workflow. Authenticate with your Google Account. Select "Event Created" as the trigger type. Choose the specific calendar to monitor. Click "Execute Node" to test the connection. Click "Save". Step 2: Telegram Node (Send Message Action) Click "Add Node" and search for Telegram. Select "Send Message" as the action. Authenticate using your Telegram Bot Token. Set the Chat ID (personal or group chat). Format the message using details from Google Calendar Trigger and set the message in text. Click "Execute Node" to test. Click "Save". Step 3: Connect & Test the Workflow Link Google Calendar Trigger → Telegram Send Message. Execute the workflow manually. Create a test event in Google Calendar. Check Telegram to see if the event details appear. n8n Workflow Created by WeblineIndia This workflow is built by the AI development team at WeblineIndia. We help businesses automate processes, reduce repetitive work, and scale faster. Need something custom? You can hire AI developers to build workflows tailored to your needs.

🐾 Who’s it for Animal advocates & campaigners who want a weekly briefing on animal-related bills with clear, actionable steps—no manual research needed. ⏱ What it does Every Monday at 8 AM, this workflow: Fetches all House bills scheduled for the week. Cleans and downloads bill PDFs. Analyzes each bill with Gemini (relevance, urgency, stance, key action points). Filters irrelevant bills using built-in thresholds. Runs a research subworkflow for lobbying, sponsor, and coalition intel. Generates a ready-to-send HTML action email with scripts, contacts, and deadlines. ⚙️ How to set up Import this workflow into n8n. Download & import the Research Subworkflow and select it in the “Research” node. Add email credentials (SMTP, Gmail, etc.) in the Email node. (Optional) Adjust Gemini prompt or thresholds for your priorities. 🔑 Requirements Gemini API key** (via Google AI Studio or Vertex AI). Email provider credentials**. Research subworkflow** (linked above). 🎛 How to customize Edit the Gemini prompt** to focus on specific issues (e.g., wildlife, farmed animals). Change relevance/urgency thresholds** to include more or fewer bills. Tweak the HTML email design** or call-to-action style.

The workflow starts by listening for messages from Telegram users. The message is then processed, and based on its content, different actions are taken. If it's a regular chat message, the workflow generates a response using the OpenAI API and sends it back to the user. If it's a command to create an image, the workflow generates an image using the OpenAI API and sends the image to the user. If the command is unsupported, an error message is sent. Throughout the workflow, there are additional nodes for displaying notes and simulating typing actions.

This n8n workflow leverages the power of AI and automation to streamline Pipedrive's CRM operations using natural language commands. It allows you to interact with your Deals, Leads, Persons, and Organizations simply by sending a message. How it Works The workflow initiates the process by sending the incoming message to an AI Agent. The AI Agent is powered by Google Gemini Chat Model and utilizing n8n's Simple Memory to maintain context, interprets the natural language command. Based on the interpreted command, the AI Agent instructs the MCP Client node to perform specific actions. The MCP Client then interacts with various nodes from Pipedrive designed to manage Deals, Leads, Persons, and Organizations within your CRM. These nodes can perform actions like creating, getting, updating, or searching for data in each category. Finally, a Gmail node sends a summary compiling the actions executed. Set Up Steps Set up your MCP Client:** Paste the MCP URL from your MCP Trigger node into the MCP Client node. Configure the AI Agent:** Connect your Google Gemini Chat Model credentials or your desired LLM. Configure Pipedrive:** The individual nodes for Deals, Leads, Persons, and Organizations will need to be connected to your specific CRM. Add your Oath credentials for Pipedrive by creating a private app. Configuring each specific node** (Create Deal, Get Lead, Update Person, Search Organization, etc.) to perform the desired action. Configure Send Summary:** Set up the Gmail node to send the summary email. Benefits Significant Time Saving:** Automates data entry, retrieval, and updates in your CRM, freeing up valuable time for sales teams and managers. Increased Efficiency:** Perform multiple CRM actions with a single natural language command. Simplified CRM Interaction:** Interact with your CRM using natural language instead of navigating complex interfaces. Reduced Errors:** Automation minimizes manual data entry errors. Suggested Enhancements Integrate More CRM Operations:** Add nodes for additional CRM functionalities like logging activities, managing tasks, or working with other modules and tools. Connect to Other Tools:** Integrate with other sales or marketing tools to create a more comprehensive workflow. Advanced AI Capabilities:** Explore fine-tuning the AI model for better understanding of specific industry jargon or complex requests. Should you add more nodes and tools, you might want to insert a specific prompt to the AI agent to give more context about the tools and actions to perform. User Management and Permissions:** Customize the private app's permissions on your Pipedrive account to limit access. Error Handling and Notifications:** Add more robust error handling and notification systems to be alerted if a workflow run fails. Need help? Feel free to contact us at 1 Node. Get instant access to a library of free resources we created.

This workflow automatically transforms your messy inbox into a neatly organized space while ensuring you never miss a critical message. It connects to your Gmail account and triggers for every new email. Using a powerful AI agent, the workflow first analyzes the email's content, sender, and metadata to classify it and apply the appropriate Gmail label (e.g., "Finance," "Marketing," "Dev Tools"). In parallel, a second AI agent determines if the email is urgent (like a security alert, OTP, or payment reminder) and generates a concise summary. If an email is marked as urgent, the workflow instantly sends a notification with the summary to your Telegram and WhatsApp, allowing you to take immediate action. This workflow is perfect for anyone looking to automate their email management, reduce inbox clutter, and stay on top of important, time-sensitive communications. Step-by-Step Explanation This workflow is designed to intelligently categorize incoming emails and notify you of urgent messages. Here is a breakdown of how it operates: Trigger: New Email Received Node: Gmail Trigger Action: The workflow initiates whenever a new email arrives in your connected Gmail inbox. Fetch Full Email Content Node: Get a message Action: It takes the ID of the new email from the trigger and fetches the complete message body, subject, sender, and headers. AI-Powered Categorization Node: AI Agent2 Action: This AI agent analyzes the full email content. Based on a detailed prompt that includes classification rules (e.g., if the sender is GitHub, classify as "Dev Tools"), it determines the most appropriate category and outputs the corresponding Label ID. Label Management and Application Node: Loop Over Items -> Create Label if Doesn't exist -> Get Existing Labels -> Filter -> Add label to thread Action: This sequence ensures the email gets the correct label. It first attempts to create the Gmail label suggested by the AI. The node is set to continue even if the label already exists. It then fetches a list of all your current Gmail labels. A Filter node finds the exact ID of the label that matches the AI's suggestion. Finally, it applies this label to the email thread, neatly organizing it in your inbox. Urgency Analysis and Summarization Node: AI Agent Action: Concurrently, a second AI agent analyzes the email to determine its urgency (classifying it as "urgent" or "normal") and generates a two-sentence summary. Parse AI Output Node: Code Action: A simple code node cleans up the JSON output from the urgency analysis to ensure it's correctly formatted for the next step. Conditional Notification Logic Node: If Action: This node checks the output from the previous step. It proceeds only if the email's urgency is marked as "urgent." Send Instant Alerts Nodes: Send a text message (Telegram) & Send message (WhatsApp) Action: If an email is deemed urgent, the workflow immediately sends an alert containing the email summary to your specified Telegram chat and WhatsApp number.

This n8n template automatically creates and publishes high-quality LinkedIn posts using your brand brief, AI-generated ideas, and structured feedback loops — all powered by OpenAI. Perfect for solo creators, marketers, and startup teams building a consistent presence on LinkedIn. Who's it for Creators and freelancers building a personal brand Social media managers at startups or agencies Marketing teams that want to scale LinkedIn content Anyone tired of manually ideating, writing, and posting daily What it does Triggers daily at a chosen time (default: 9 PM) Fetches new content ideas from your idea-generation workflow Loads your brand brief and previous post feedback Uses OpenAI to craft a branded, engaging LinkedIn post Publishes directly to LinkedIn — no manual copy-paste needed How the AI logic works The AI agent follows a consistent, looped prompt strategy to ensure brand alignment: ++Prompt++ You are a helpful content creator for Nabin Bhandari's personal brand. Use the below steps to create content: Always start by getting the brand brief using the Get_Brand_Brief tool. Create a post on the requested topic that aligns with the brand brief. Get feedback and a score on the post using the Get_Content_Feedback tool. If the score is below 0.8, use the feedback to refine the post and repeat. The final output should be the approved post. Bonus: You can fine-tune OpenAI on your own brand tone and style by uploading at least 50 examples of approved posts. This will help ensure even more accurate, on-brand outputs. Requirements OpenAI API Key LinkedIn API credentials set in the LinkedIn node A Notion page (or any storage) with your Brand Brief clearly described Optional: Fine-tuned OpenAI model for higher fidelity How to customize Adjust the AI prompt for different tones (e.g., witty, professional) Swap the idea source (Airtable, Notion, Webhook, etc.) Add manual approval steps before publishing Replace the LinkedIn node with other social media APIs (Twitter/X, Threads) Tips Store a clear and specific brand brief in your Notion page — it directly shapes the AI's tone Add a database of previously approved posts for fine-tuning OpenAI Use additional feedback metrics (likes, engagement) for future iterations

🤖💬 Conversational AI Chatbot with Google Gemini for Text & Image | Telegram Overview 📋 Flexible and scalable chatbot template, designed mainly for Spanish conversations but capable of handling English and other languages. Integrates Google Gemini API for text and image generation, and Telegram for messaging. Supports multiple output types with potential for video, audio, and more. How It Works Modular Architecture & Extensibility ⚙️ Separate modules for data extraction, intent analysis, and adaptive response generation. Easily extendable with additional tools, databases, or APIs. Context & Memory Handling 🧠 Session-based volatile memory maintains conversation coherence. Allows updates or modifications to previous images based on new requests (e.g., add a hat to a dog 🐶). Intent Detection & Classification 🔍 Google Gemini accurately classifies user intent. Two-step validation ensures context-aware, precise replies. Content Generation & Output ✍️🖼️ Generates text and images based on intent and context. Designed for Telegram but adaptable to other platforms and media types (audio, video). Key Benefits ✅ Scalable, customizable, and production-ready architecture. Supports multiple content formats: text, images, audio, and video. Dynamic context and memory management for smooth, coherent conversations. Native integration with Google Gemini and Telegram ensures reliable and seamless operation. Suitable for diverse use cases and easy to extend with new tools or platforms. Use Cases 💼 Customer support virtual assistants. On-demand multimedia content creation. Marketing and user engagement bots. AI conversational prototypes and pilots. Requirements 👨‍💻 n8n instance (self-hosted or cloud) Google Gemini API credentials Telegram bot setup (optional but recommended) Active member of the Polytechnic Artificial Intelligence Club (CIAP) at ESPOL.

Automatically scrape LinkedIn posts with Apify, transform them into optimized tweets and threads using Claude AI, store them in Airtable for approval, and publish to X on a daily schedule. Who is this for This workflow is designed for content creators, social media managers, and personal brand builders who want to maximize their content reach by repurposing LinkedIn posts for X (Twitter) without manual rewriting. What it does This workflow automates the entire LinkedIn-to-X content repurposing pipeline: Weekly scraping: Uses Apify to scrape your recent LinkedIn posts based on configurable parameters stored in Airtable Carousel extraction: If a post contains a carousel/PDF, OpenAI extracts the slide content via OCR AI transformation: Claude (via OpenRouter) converts each LinkedIn post into two X-optimized variations: a standalone tweet and a thread (3-7 tweets) Content storage: Saves both the original posts and generated tweets to Airtable with a "Pending" status for review Scheduled publishing: Daily at 12:30, searches for ‘Approved’ tweets whose publication date has passed and posts them to X Thread handling: Properly chains thread tweets as replies to maintain the conversation structure Requirements Apify account (LinkedIn Profile Posts Scraper actor) Airtable account with configured base OpenAI API access (for carousel OCR) OpenRouter API access (for Claude) X/Twitter API access How to set up Create an Airtable base with three tables: Config, LK Posts, and X Tweets (see table configurations below) Configure the Config table with your LinkedIn profile URL, scraping limits, and tweet scheduling delay Configure the ‘TWEET NOW’ button in Airtable with the following URL formula: Connect your credentials: Apify, Airtable, OpenAI, OpenRouter, and X/Twitter Set the weekly and daily schedule triggers according to your timezone Activate the workflow Config Table | Field Name | Type | Description | |------------|------|-------------| | Name | String | Configuration parameter name | | Type | Single Select | Data type indicator: String, Integer | | String Value | String | Value when Type is "String" | | Integer Value | Number | Value when Type is "Integer" | Configuration parameters to create: profile_url — LinkedIn profile URL to scrape posted_limit — Time range for scraping (possible values: "any", "1h", "24h", "week", "3months", "6months", "year") max_posts — Maximum number of posts to scrape schedule_tweets_days_after_lk — Number of days after LinkedIn post date to schedule the tweet LK Posts Table | Field Name | Type | Description | |------------|------|-------------| | LK Post ID | String | LinkedIn post unique identifier | | Status | Single Select | Post processing status: Scrapped, Converted, Tweeted | | Date | DateTime | Original LinkedIn post publication date | | Content | Long Text | LinkedIn post text content | | Post URL | URL | Link to the original LinkedIn post | | Post Img URL | URL | URL of post image (if any) | | Post Doc URL | URL | URL of carousel/PDF document (if any) | | Carousel Content | Long Text | Extracted text content from carousel slides | X Tweets Table | Field Name | Type | Description | |------------|------|-------------| | Unique ID | Formula | Auto-generated unique identifier | | LK Post ID | String | Reference to the source LinkedIn post | | Status | Single Select | Tweet status: Pending, Approved, Rejected, Tweeted | | Variation | Single Select | Tweet format: Standalone, Thread | | Tweet Nb | Number | Tweet position in thread (0 for standalone, 1-7 for thread tweets) | | Content | Long Text | The tweet text content | | Publication Date | DateTime | Scheduled date/time to publish the tweet | | Post Now | Button | Triggers webhook to post immediately | How to customize AI prompt: Edit the "ConvertPostIntoTweets" node to adjust tone and style LLM model: Replace the OpenRouter node with OpenAI or any other LLM node in "ConvertPostIntoTweets" if you prefer a different model Posting delay: Change schedule_tweets_days_after_lk in the Config table Schedule: Modify "Weekly_OnSunday" and "Daily_AtNoon" triggers Scraping: Adjust max_posts and posted_limit in Config table

How It Works This workflow automates programme performance monitoring and governance oversight through intelligent AI-driven analysis and multi-tool orchestration. Designed for programme managers, portfolio management offices, and executive leadership teams, it solves the critical challenge of tracking programme health while coordinating interventions across escalation, exception handling, and briefing preparation workflows. The system operates on scheduled intervals, fetching programme data and processing it through dual AI agents for performance monitoring and governance assessment. It orchestrates parallel specialized tools for exception escalation, briefing preparation, and governance reporting, each with dedicated AI models and output parsers. The workflow intelligently routes findings based on severity classification, delivering critical alerts through multiple channels including email and Slack while generating formatted standard reports. By maintaining comprehensive documentation and coordinating multi-faceted governance responses, it ensures programme stakeholders receive timely, actionable intelligence while creating complete audit trails for portfolio reviews. Setup Steps Configure Schedule Trigger with programme review frequency Connect Workflow Configuration node with programme parameters Set up Fetch Programme Data node with project management API credentials Configure Programme Monitoring Agent with OpenAI API credentials Set up monitoring processing Connect Governance Agent with OpenAI API credentials for orchestration Configure parallel specialized tools with respective OpenAI models Set up tool-specific parsers Prerequisites OpenAI API credentials for multiple AI agents and specialized tools Use Cases PMOs monitoring multi-project portfolios, consulting firms tracking client engagement health Customization Adjust monitoring frequency for programme urgency levels Benefits Reduces programme review overhead by 75%, eliminates manual status compilation

Build your own Shopify Store Agent with Shopify MCP and C1 by Thesys This n8n template can setup a embeddable web chat widget for your Shopify store. Check out a working demo of this template here. What this workflow does A user sends a message in the n8n Chat UI (public chat trigger). The AI Agent interprets the request. The agent calls CoinGecko Free MCP to fetch market data (prices, coins, trending, etc.). The model responds through C1 by Thesys with a streaming, UI answer. Example prompts you can try right away Copy/paste any of these into the chat: “What are the products in the catalog?” "Purchase white shirt" "Checkout my cart" How it works User sends a prompt C1 model based on prompt will use Shopify MCP to fetch live catalog 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. Shopify MCP URL You’ll need the URL of your Shopify Storefront MCP to access the catalog. For more information, please refer to the Shopify MCP Docs. What is C1 by Thesys? C1 by Thesys is an API middleware that augments LLMs to respond with interactive UI (charts, buttons, forms) in real time instead of text. Facing setup issues? If you get stuck or have questions: :speech_bubble: Join the Thesys Community :e-mail: Email support: support@thesys.dev

Description This workflow helps developers and automation teams route measurement data from a webhook to multiple destinations using n8n. It is designed for measurement engines, 3D scanning systems, QA tools, and API-based platforms that send structured JSON data and need a fast, flexible way to store, display, or process it without building a custom backend. The workflow starts with a Webhook Trigger that receives incoming measurement data and validates the payload. A processing step normalizes the fields into a clean, consistent format so the data can be reused across different outputs. A routing node then allows users to choose how they want to handle the data. You can append measurements to Google Sheets for reporting, display them as a formatted HTML page for quick viewing, export them as a CSV and send them by email, or run custom JavaScript logic to forward the data to APIs, cloud storage, or other n8n workflows. Clear sticky notes inside the workflow guide users through setup, credential configuration, and customization, making this template beginner-friendly and production-ready. How it works A Webhook Trigger receives measurement data as a JSON payload. The workflow validates and normalizes the data structure. A Switch node routes the data to the selected output path. The data is sent to Google Sheets, an HTML response, a CSV email, or a custom JavaScript step. How to set up Import and activate the workflow in n8n. Copy the Webhook URL from the Webhook Trigger node. Open the 3D Measure Up Web Application: https://3dmeasureup.ai/ Log in and navigate to Settings → Webhooks. Paste the webhook URL into the Webhook URL field and click Save. Connect Google Sheets and email credentials if needed. Use the configuration fields and sticky notes inside the workflow to select and customize your output path. Setup usually takes 5–10 minutes. Requirements n8n (cloud or self-hosted) A webhook URL generated by this workflow 3D Measure Up** can send measurement data as JSON to the webhook URL Google account (optional, for Google Sheets output) Email credentials (optional, for CSV email delivery) How to update the Webhook URL in 3D Measure Up Open the 3D Measure Up Web Application: https://3dmeasureup.ai/ Log in to your account. Navigate to Settings → Webhooks. Copy the Webhook Trigger URL from this n8n workflow. Paste the URL into the Webhook URL field in 3D Measure Up. Click Save to apply the configuration. Once saved, the webhook becomes active immediately. From now on, whenever new measurements are generated, the data will be sent automatically to your n8n workflow. How to customize the workflow Adjust the processing node to match your measurement schema. Enable or disable outputs using the Switch node. Edit the HTML template for branding or layout. Add API calls or storage logic inside the JavaScript node.

This template deploys a multi-agent system that fully automates advanced stock analysis. It uses a central AI orchestrator to call specialized sub-workflows, synthesizing technical, fundamental, and news sentiment data into a single, actionable report delivered to your inbox. All API Keys can be acquired for free! How it Works Orchestration:** An AI Agent acts as the central "brain," managing the analysis pipeline. It's triggered either on a schedule for a list of stocks or manually for a single ticker. Specialist Agents (Tools):** The orchestrator invokes three sub-workflows as tools to gather intelligence: Technical Analysis: Fetches TA data (RSI, MACD, Bollinger Bands) and uses a vision-AI to analyze the stock's chart, identifying trends and patterns. Fundamental Analysis: Retrieves financial statements (Income, Balance Sheet) to generate a summary of the company's financial health and valuation. News Sentiment Analysis: Aggregates and analyzes market news to determine overall sentiment and identify key discussion topics. Synthesis & Delivery:** The main agent synthesizes all findings to formulate a final recommendation (Buy, Hold, Sell), generates a professional HTML report, and delivers it via email. Setup (Est. 10-15 mins) This is an advanced, multi-workflow template. Please follow the steps precisely. Split Modules: Separate the 5 color-coded modules on this canvas into 5 new, individual workflows. Acquire APIs: Acquire the 7 APIs needed for this workflow. These need Credentials: Gemini,, OpenRouter, SMTP, Alpaca. These just need to be pasted in: AlphaVantage, TwelveData, Chart-Img. Configure & Link: Insert your API keys and email, then re-link the Execute Workflow and Tool nodes to connect your new workflows. Activate: Toggle all 5 workflows to "Active." ➡️ For the complete, detailed guide, visit: https://docs.google.com/document/d/1Ri_GfuIlc0QVm1aDrWJjRCg_2vWRCrw_SjRV9cBoKmw/edit?usp=sharing