Workflow Templates

Daily Economic News Brief for Israel (Hebrew, RTL, GPT-4o) Overview Stay ahead of the curve with this AI-powered workflow that delivers a daily economic summary tailored for professionals tracking the Israeli economy. At 8:00 PM Israel Time, this workflow: Retrieves the latest articles from Calcalist and Mako via RSS Filters duplicates and irrelevant stories Uses OpenAI’s GPT-4o to identify the 5 most important stories of the day Summarizes each article in concise, readable Hebrew Generates a fully styled, responsive HTML email (with proper RTL layout) Sends it to your inbox using your preferred SMTP email provider Perfect for economists, analysts, investors, or policymakers who want an actionable and personalized news digest -- no distractions, no fluff. Setup Instructions Estimated setup time: 10 minutes Required credentials: OpenAI API Key SMTP credentials (for email delivery) Steps: Import this template into your n8n instance. Add your OpenAI API Key under credentials. Configure the SMTP Email node with: Host (e.g. smtp.gmail.com) Port (465 or 587) Username (your email) Password (app-specific password or login) Set your target email address in the last node. (Optional) Customize the GPT prompt to adjust tone or audience (e.g. general public, policy makers). Activate the workflow and receive daily updates straight to your inbox. Customization Tips Change the RSS sources to pull from other Hebrew or international news websites Modify the summarization prompt to fit different sectors (e.g. tech, health, politics) Add integrations like Notion, Airtable, or Telegram for logging or distribution Apply your branding to the HTML output (logos, footer, colors) Why Use This? This is more than a news digest. It’s an intelligent economic assistant that filters noise, highlights what matters, and keeps you informed-automatically. You can set it up in 10 minutes and benefit every single day.

Automatically deploy n8n workflows by simply dropping JSON files into a Google Drive folder—this template watches for new exports, cleans and imports them into your n8n instance, applies a tag, and then archives the processed files. Who is this template for? This workflow template is designed for n8n power users, and automation specialists who need a simple, reliable way to bulk‑deploy or version‑control n8n workflows via Google Drive. It’s perfect if you: Manage multiple n8n instances (staging, production, etc.) Want an easy “drop‑in” approach to publish new or updated workflows Prefer storing/exporting JSON in Drive rather than editing in the UI Use case Manually importing .json exports into n8n is slow and error‑prone. With this template you can: Keep your workflows in a shared Drive folder (version control friendly) Automatically sanitize each file so only supported settings go through Tag deployed workflows consistently for easy filtering Move processed files to a “Deployed” folder for clear change tracking How it works Watch “ToDeploy” folder in Google Drive for new .json files Download & parse each file into a JSON object Clean payload: strip out everything except the allowed executionOrder (and timezone if you choose) POST the cleaned workflow to your n8n instance via /api/v1/workflows PUT a predefined tag onto the newly created workflow Move file to your “Deployed” folder when import succeeds, or capture the workflow name & error if it fails Setup instructions 1. In Google Drive create a ToDeploy folder and a Deployed folder Update "Google Drive Trigger -ToDeploy folder" to your ToDeploy folder Update "Move JSON file to Deployed folder" to you Deployed folder 2. Create a n8n API key: +Go to Settings > n8n API +Select Create an API key +Copy API Key 3. In "Get Existing Workflow Tags" node: Create n8n API Authentication Authentication: Predefined Credential Type Credential Type: n8n API Create new credential: +Paste in API key +Baseurl: https://SUBDOMAIN.YOURDOMAINNAME.com/api/v1/ 4. Add n8n API authentication to: "Create n8n Workflow" node "Set Workflow Tag" node 5. Add your N8N instance URL to the N8N_Instance_URL variable in "Set n8n URL variable" node. 6. Run "1. Get Workflow Tags" flow and copy the ID of your chosen tag. 7. In "Set n8n API URL & Tag ID variables" node: Add the Workflow Tag ID to the N8N_Instance_Tag variable Add your N8N instance URL to the N8N_Instance_URL variable 8. Set workflow to Active How to adjust it to your needs Use different tags: run Get Existing Workflow Tags on start‑up to refresh available tags, or hard‑code multiple tags in the Set Workflow Tag node. Add notifications**: connect the error branch to Slack or Email nodes so you get alerted if an import fails. Swap Drive for another storage**: replace Google Drive nodes with Dropbox, S3, or GitHub triggers if you prefer a different source for your JSON files.

Who is this for? This workflow is ideal for individuals focused on nutrition tracking, meal planning, or diet optimization—whether you’re a health-conscious individual, fitness coach, or developer working on a healthtech app. It also fits well for anyone who wants to capture their meal data via voice or text, without manually entering everything into a spreadsheet. What problem is this workflow solving? Manually logging meals and breaking down their nutritional content is time-consuming and often skipped. This workflow automates that process using Telegram for input, OpenAI for natural language understanding, and Google Sheets for structured tracking. It enables users to record meals by typing or sending voice messages, which are transcribed, analyzed for nutrients, and automatically stored for tracking and review. What this workflow does This n8n automation lets users send either a text or voice message to a Telegram bot describing their meal. The workflow then: Receives the Telegram message Checks if it’s a voice message • If yes: Downloads the audio file and transcribes it using OpenAI • If no: Uses the text input directly Sends the meal description to OpenAI to extract a structured list of ingredients and nutritional details Parses and stores the results in Google Sheets Responds via Telegram with a personalized confirmation message A testing interface also allows you to simulate prompts and view structured outputs for development or debugging. Setup Create a Telegram bot via BotFather and note the API token. Create an empty Google Sheet and store the sheet ID in the environment. Set up your OpenAI credentials in the n8n credential manager. Customize the “List of Ingredients and Nutrients” node with your prompt if needed. (Optional) Use the “Testing” section to simulate messages and refine outputs before going live. How to customize this workflow to your needs • Enhance prompts in the OpenAI node to improve the structure and accuracy of responses. • Add new fields in the Google Sheet and corresponding logic in the parser if you want more detail. • Adjust the Telegram response to provide motivational feedback, dietary tips, or summaries. • Upgrade to the “Pro” version mentioned in the contact section for USDA database integration and complete nutrient breakdowns. This is a lightweight, AI-powered meal logging automation that transforms voice or text into actionable nutrition data—perfect for making healthy eating easier and more data-driven. See my other workflows here

🔍 Competitor Review Scraper & Ad Copy Generator (Trustpilot + Bright Data + GPT-4o-mini) 📌 Who It's For Marketers, business owners, and agencies looking to: Analyze competitor pain points Generate high-impact Facebook ad copy Automate manual data processing 🧩 How It Works This n8n-based workflow combines Bright Data, Google Sheets, and OpenAI to scrape, process, and transform Trustpilot reviews into ready-to-use ad copy. 🔹 Step-by-Step Breakdown Trigger (Manual Form Submission) Input required: Competitor’s Trustpilot URL Review timeframe (30d, 3m, 6m, 12m) Fetch Reviews Calls Bright Data’s Dataset API with URL & timeframe Polls until snapshot is ready Retrieve & Store Extracts all reviews Saves them into a structured Google Sheet Filter & Aggregate Filters to only 1–2 star reviews Summarizes common negative feedback Generate Ad Copy Sends the summary to OpenAI GPT-4o-mini Produces 3 variations of ad copy targeting pain points Distribute Insights Sends ad copy + summary via email to the marketing team ✅ Requirements -LLM Account -Google Sheets - Copy this sheet: https://docs.google.com/spreadsheets/d/1Zi758ds2_aWzvbDYqwuGiQNaurLgs-leS9wjLWWlbUU/edit?gid=0#gid=0 -Bright Data account ⚙️ Setup Instructions **Step 1: Google Sheets ** Copy this Google Sheets template Do not change column headers **Step 2: n8n Credential Setup ** Google Sheets: OAuth2 Bright Data: Authorization Header OpenAI: API Key for GPT-4o-mini **Step 3: Import Workflow ** Import the .json file into n8n Configure your sheet + dataset ID Adjust GPT prompts as needed **Step 4: Run the Workflow ** Trigger via form Receive ad copy + review insights via email 🧠 Tips & Best Practices Bright Data snapshots may take time — polling is handled Focusing on 1–2 star reviews yields the most actionable pain points You can customize GPT-4o-mini prompts for tone or vertical 💬 Support & Feedback Need help or customization? 📧 Email: Yaron@nofluff.online 📺 YouTube: @YaronBeen 🔗 LinkedIn: linkedin.com/in/yaronbeen 📚 Bright Data Docs: docs.brightdata.com/introduction

Detailed Description The ToDo App workflow is designed to streamline task management through Telegram and Google Tasks integration. This workflow allows users to create, update, and manage tasks via Telegram messages, leveraging AI capabilities to enhance user interaction. The expected outcome is a seamless experience where users can manage their tasks efficiently without needing to switch between applications. Who is this for? This workflow is intended for: Individuals** looking for an efficient way to manage their tasks directly from Telegram. Teams** that require a collaborative task management solution integrated with Google Tasks. Developers** interested in automating task management processes using n8n and Telegram. What problem does this workflow solve? Managing tasks can often be cumbersome, especially when switching between different applications. This workflow addresses the following problems: Fragmented Task Management**: Users can manage tasks directly from Telegram, reducing the need to switch to Google Tasks. Inefficient Communication**: By integrating AI, users can interact with the task management system in a conversational manner, making it more intuitive. Task Updates**: Users can easily update task statuses and details through simple messages, enhancing productivity. What this workflow does The ToDo App workflow performs the following functions: Incoming Message Handling: Listens for messages sent to a Telegram bot. Task Creation: Allows users to create new tasks based on their messages. Task Updates: Users can update existing tasks by sending specific commands. Task Retrieval: Retrieves today's and upcoming tasks from Google Tasks. Voice Note Transcription: Supports voice messages, converting them into text for task management. AI Assistance: Utilizes an AI agent to assist users in managing their tasks effectively. Setup Prerequisites Before setting up the workflow, ensure you have the following: n8n Account**: Sign up for an n8n account if you don't have one. Telegram Bot**: Create a Telegram bot and obtain the API token. Google Tasks API**: Set up Google Tasks API and obtain OAuth2 credentials. OpenAI API Key**: Sign up for OpenAI and obtain an API key for AI functionalities. Setup Process Upload the JSON for this workflow and setup the authentication for the different tools. How to customize this workflow To adapt the ToDo App workflow to different needs, consider the following customizations: Change Task Management Platform**: If you prefer a different task management tool, replace the Google Tasks nodes with your preferred service's API. Modify AI Responses**: Adjust the AI agent's system message to change how it interacts with users. Add Additional Commands**: Expand the workflow by adding more commands for different task management functionalities (e.g., deleting tasks). Integrate Other Messaging Platforms**: If you want to use a different messaging service, replace the Telegram nodes with the appropriate nodes for that service. Conclusion The ToDo App workflow provides a powerful solution for managing tasks through Telegram, enhancing productivity and user experience. By following the setup instructions and customization options, users can tailor the workflow to meet their specific needs, making task management more efficient and accessible.

This n8n demonstrates how to build your own Qdrant MCP server to extend its functionality beyond that of the official implementation. This n8n implementation exposes other cool API features from Qdrant such as facet search, grouped search and recommendations APIs. With this, we can build an easily customisable and maintainable Qdrant MCP server for business intelligence. This MCP example is based off an official MCP reference implementation which can be found here - https://github.com/qdrant/mcp-server-qdrant How it works A MCP server trigger is used and connected to 5 custom workflow tools. We're using custom workflow tools as there is quite a few nodes required for each task. We use a mix of n8n supported Qdrant nodes for simple operations such as insert documents and similarity search, and HTTP node to hit the Qdrant API directly for Facet search, group search and recommendations. We use "Edit Field" and "Aggregate" nodes to return suitable responses to the MCP client. How to use This Qdrant MCP server allows any compatible MCP client to manage a Qdrant Collection by supporting select and create operations. You will need to have a collection available before you can use this server. Use the Prerequisite manual steps to get started! Connect your MCP client by following the n8n guidelines here - https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-langchain.mcptrigger/#integrating-with-claude-desktop Try the following queries in your MCP client: "Can you help me list the available companies in the collection?" "What do customers say about product deliveries from company X?" "What do customers of company X and company Y say about product ease of use?" Requirements Qdrant for vector store. This can be an a cloud-hosted instance or one you can self-host internally. MCP Client or Agent for usage such as Claude Desktop - https://claude.ai/download Customising this workflow Depending on what queries you'll receive, adjust the tool inputs to make it easier for the agent to set the right parameters. Not interested in Reviews? The techniques shared in this template can be used for other types of collections. Remember to set the MCP server to require credentials before going to production and sharing this MCP server with others!

This workflow sends a message to a Discord channel when a new row is added or a row is updated in a Google Sheet. The message will send all data rows in the Google Sheet. Prerequisites Discord account and Discord credentials. Google account and Google credentials. How it works Using a code node, we can use the obtained Google Sheet data to create a custom message that will be sent to Discord. The message will be sent to the Discord channel specified in the Discord node. Setup This workflow requires that you set up a Discord webhook and have an existing Google Sheet with data. See how to set up a Discord webhook here.

Tags: EU Legislation, Sustainability, Automation, Web Scraping, OpenAI, Google Sheets, Policy Monitoring, Climate Context Hey! I’m Samir, a Supply Chain Engineer and Data Scientist from Paris, and the founder of LogiGreen Consulting. We use AI, automation, and data to support sustainable business practices for small, medium and large companies. This workflow is part of our broader initiative to monitor and act on sustainability legislation in Europe. > How do you know if new EU laws will impact your business's sustainability goals? This n8n workflow automatically scrapes the EU Parliament’s legislative portal to find and flag procedures related to environmental sustainability. 📬 For business inquiries, feel free to connect with me on LinkedIn Who is this template for? This workflow is useful for: Sustainability consultants** monitoring legal frameworks NGOs and researchers** tracking environmental regulations Companies* aligning with *CSRD* or *EU Green Deal** objectives Policy analysts** looking for automation tools What does it do? This n8n workflow: 🌐 Scrapes the EU Parliament legislative portal for yesterday’s entries 🧠 Uses OpenAI to classify if each procedure is related to sustainability 🗂️ Filters out irrelevant items 📊 Saves the results in a Google Sheet ✅ Creates a Google Task for each relevant file to review the legislation How it works Trigger manually or on schedule Scrape HTML blocks for scheduled debates Parse each procedure to extract Title, Committee, Rapporteur, PDF link Call GPT-4-turbo to check if the topic matches sustainability criteria Filter responses based on “yes” or “no” Store valid items into Google Sheets Generate tasks in Google Tasks The AI only flags procedures that directly impact the environment, circular economy, or pollution control. What do I need to get started? You’ll need: A Google Sheet connected to your n8n instance An OpenAI account with GPT-4 access A Google Task List Follow the Guide! Follow the sticky notes in the workflow or check my tutorial to configure each node and start using AI to monitor sustainability regulations in Europe. 🎥 Watch My Tutorial Notes AI filters are strict — you can customise the system prompt to match your needs This is ideal for tracking legislative risk for climate regulations This workflow was built using n8n version 1.85.4 Submitted: April 21, 2025

Overview Automated LinkedIn content generator that: Fetches trending AI news using NewsAPI Enhances content with Qdrant vector store context Generates professional LinkedIn posts using GPT-4o-mini Tracks email interactions in Google Sheets 🛠️ Prerequisites API Keys : NewsAPI, OpenAI (GPT-4o-mini), Qdrant Accounts : Gmail Oauth, Google Sheets, LinkedIn developer API Environment Variables : OPENAI_API_KEY NEWSAPI_KEY QDRANT_URL/QDRANT_API_KEY 📁 Google Sheets Setup Create a spreadsheet with these columns: ISO date Email address Unique ID "Approve" or "Reject" ⚙️ Setup Instructions Pre-populate Qdrant : Create collection "posts" with LinkedIn post examples Add 10+ example posts for style reference Node Configuration : Update Gmail credentials (OAuth2) Set fromEmail/toEmail in email nodes Configure Google Sheets document IDs Test Workflow : Run Schedule Trigger manually first Verify email notifications work Check Qdrant vector store connectivity 🎨 Customization Options Tone Adjustment : Modify system message in "AI Agent" Post Style : Update prompt in "Generate LinkedIn Post" Filter Criteria : Edit NewsAPI URL parameters Scheduling : Change interval in Schedule Trigger

Who is this for? Everyone! Did you dream of asking an AI "what hotel did I stay in for holidays last summer?" or "what were my marks last semester like?". Dream no more, as vector similarity searches and this workflow are the foundations to make it possible (as long as the information appears in your e-mails 😅). 100% Local and Open Source! This workflow is designed to use locally-hosted open source. Ollama as LLM provider, nomic-embed-text as the embeddings model, and pgvector as the vector database engine, on top of Postgres. Structured AND Vectorized This workflow combines structured and semantic search on your e-mail. No need for enterprise setups! Leverage the convenience of n8n and open source to get a bleeding edge solution. Setup You will need a PGVector database with embeddings for all your email. Use my other template Gmail to Vector Embeddings with PGVector and Ollama to set it up in a breeze! Make a copy of my Email Assistant: Convert Natural Language to SQL Queries with Phi4-mini and PostgreSQL, you will need it for structured searches. Install this template and modify the Call the SQL composer Workflow step, to point at your copy of the SQL workflow. Adjust the rest of necessary steps: Telegram Trigger, AI Chat model, AI Embeddings... Activate the workflow and chat around!

Who this is for? Indeed Data Scraper & Summarization with Airtable, Bright Data and Google Gemini is an automated workflow that extracts company profile information from Indeed using Bright Data Web Unlocker, transforms the data using Google Gemini's LLM, and forward the transformed response with the summary to a specified webhook for downstream use. This workflow is tailored for: Recruiters and HR teams who want quick summaries of companies listed on Indeed. Market researchers and analysts needing structured insights into businesses. Founders, investors, and consultants scouting potential competitors, partners, or clients. No-code enthusiasts looking to automate data extraction and enrichment pipelines without manual scraping or parsing. What problem is this workflow solving? Manually gathering structured information about companies on Indeed is time-consuming and inconsistent. Pages vary in structure, and extracting clean, digestible summaries can require technical scraping expertise. This workflow automates: Extracting company data from Indeed reliably using Bright Data Web Unlocker. Cleaning and summarizing the extracted content using Google Gemini LLM. Storing structured insights directly into Airtable for easy access and further workflows. Eliminates manual research, saves hours, and produces AI-enhanced, easily searchable records. What this workflow does Triggers on-demand. Pulls company page URLs from Airtable. Scrapes content from each Indeed company profile using Bright Data Web Unlocker. Sends the raw HTML to Google Gemini for extraction and summarization. Sends the summarized data to other platforms via a Webhook notification mechanism. Setup Sign up at Bright Data. Navigate to Proxies & Scraping and create a new Web Unlocker zone by selecting Web Unlocker API under Scraping Solutions. In n8n, configure the Header Auth account under Credentials for Bright Data. The Value field should be set with the Bearer XXXXXXXXXXXXXX. The XXXXXXXXXXXXXX should be replaced by the Web Unlocker Token. In n8n, configure the Google Gemini(PaLM) Api account with the Google Gemini API key (or access through Vertex AI or proxy). In n8n, configure the Airtable Personal Access Token account under Credentials. Update the Webhook Notifier with the Webhook endpoint of your choice. How to customize this workflow to your needs This workflow is built to be flexible - whether you're a company or a market researcher, entrepreneur, or data analyst. Here's how you can adapt it to fit your specific use case: Extend the scraper**: Modify Bright Data targets to pull job listings, salaries, or employee reviews via the Airtable data source. Customize the summary prompt**: Ask Gemini to extract different attributes hiring trends, practices etc. Routing the output to different destinations**: Send summaries or transformed response to Google Sheets, Airtable, or CRMs like HubSpot or Salesforce etc.

Disclaimer This template is only available on n8n self-hosted as it's making use of the community node for MCP Client. Who this is for? The Extract, Transform LinkedIn Data with Bright Data MCP Server & Google Gemini workflow is an automated solution that scrapes LinkedIn content via Bright Data MCP Server then transforms the response using a Gemini LLM. The final output is sent via webhook notification and also persisted on disk. This workflow is tailored for:​ Data Analysts : Who require structured LinkedIn datasets for analytics and reporting. Marketing and Sales Teams : Looking to enrich lead databases, track company updates, and identify market trends. Recruiters and Talent Acquisition Specialists : Who want to automate candidate sourcing and company research. AI Developers : Integrating real-time professional data into intelligent applications. Business Intelligence Teams : Needing current and comprehensive LinkedIn data to drive strategic decisions. What problem is this workflow solving? Gathering structured and meaningful information from the web is traditionally slow, manual, and error-prone. This workflow solves: Reliable web scraping using Bright Data MCP Server LinkedIn tools. LinkedIn person and company web scrapping with AI Agents setup with the Bright Data MCP Server tools. Data extraction and transformation with Google Gemini LLM. Persists the LinkedIn person and company info to disk. Performs a Webhook notification with the LinkedIn person and company info. What this workflow does? This n8n workflow performs the following steps: Trigger: Start manually. Input URL(s): Specify the LinkedIn person and company URL. Web Scraping (Bright Data): Use Bright Data's MCP Server, LinkedIn tools for the person and company data extract. Data Transformation & Aggregation: Uses the Google LLM for handling the data transformation. Store / Output: Save results into disk and also performs a Webhook notification. Pre-conditions Knowledge of Model Context Protocol (MCP) is highly essential. Please read this blog post - model-context-protocol You need to have the Bright Data account and do the necessary setup as mentioned in the Setup section below. You need to have the Google Gemini API Key. Visit Google AI Studio You need to install the Bright Data MCP Server @brightdata/mcp You need to install the n8n-nodes-mcp Setup Please make sure to setup n8n locally with MCP Servers by navigating to n8n-nodes-mcp Please make sure to install the Bright Data MCP Server @brightdata/mcp on your local machine. Sign up at Bright Data. Navigate to Proxies & Scraping and create a new Web Unlocker zone by selecting Web Unlocker API under Scraping Solutions. Create a Web Unlocker proxy zone called mcp_unlocker on Bright Data control panel. In n8n, configure the Google Gemini(PaLM) Api account with the Google Gemini API key (or access through Vertex AI or proxy). In n8n, configure the credentials to connect with MCP Client (STDIO) account with the Bright Data MCP Server as shown below. Make sure to copy the Bright Data API_TOKEN within the Environments textbox above as API_TOKEN=<your-token>. Update the LinkedIn URL person and company workflow. Update the Webhook HTTP Request node with the Webhook endpoint of your choice. Update the file name and path to persist on disk. How to customize this workflow to your needs Different Inputs: Instead of static URLs, accept URLs dynamically via webhook or form submissions. Data Extraction: Modify the LinkedIn Data Extractor node with the suitable prompt to format the data as you wish. Outputs: Update the Webhook endpoints to send the response to Slack channels, Airtable, Notion, CRM systems, etc.