by Yar Malik (Asfandyar)
Who’s it for This template is for users who want to combine the power of AI with Google Sheets for managing and calculating data quickly. It’s ideal for small businesses, data entry teams, and anyone who tracks lists, orders, or tasks in Google Sheets and needs AI-driven insights or calculations. How it works The workflow connects an AI agent with Google Sheets and a calculator tool. When a user sends a chat message, the AI interprets the request, retrieves or updates rows in the connected sheet, and performs calculations when needed. For example, it can read a list of orders from a sheet and calculate totals or averages instantly. It also supports creating, updating, and deleting rows from the sheet through natural language instructions. How to set up Copy the provided Google Sheet into your Google Drive. Connect your Google Sheets credentials in n8n. Add your OpenAI credentials for the AI agent. Deploy the workflow and start interacting with it by sending chat prompts. Requirements OpenAI account (for AI responses) Google Sheets account with a spreadsheet n8n instance with LangChain nodes enabled How to customize the workflow Change the spreadsheet fields (ID, Name, etc.) to match your own data structure. Modify the AI prompt to guide the agent’s tone or behavior. Extend the workflow by adding more Google Sheets operations or AI tools for advanced tasks.
by David Olusola
📧 Master Your First AI Email Agent with Smart Fallback! Welcome to your hands-on guide for building a resilient, intelligent email support system in n8n! This workflow is specifically designed as an educational tool to help you understand advanced AI automation concepts in a practical, easy-to-follow way. 🚀 What You'll Learn & Build: This powerful template enables you to create an automated email support agent that: Monitors Gmail** for new customer inquiries in real-time. Processes requests** using a primary AI model (Google Gemini) for efficiency. Intelligently falls back to a secondary AI model** (OpenAI GPT) if the primary model fails or for more complex queries, ensuring robust reliability. Generates personalized and helpful replies** automatically. Logs every interaction** meticulously to a Google Sheet for easy tracking and analysis. 💡 Why a Fallback Model is Game-Changing (and Why You Should Learn It): Unmatched Reliability (99.9% Uptime):** If one AI service experiences an outage or rate limits, your automation seamlessly switches to another, ensuring no customer email goes unanswered. Cost Optimization:** Leverage more affordable models (like Gemini) for standard queries, reserving premium models (like GPT) only when truly needed, significantly reducing your API costs. Superior Quality Assurance:** Get the best of both worlds – the speed of cost-effective models combined with the accuracy of more powerful ones for complex scenarios. Real-World Application:** This isn't just theory; it's a critical pattern for building resilient, production-ready AI systems. 🎓 Perfect for Beginners & Aspiring Automators: Simple Setup:** With drag-and-drop design and pre-built integrations, you can get this workflow running with minimal configuration. Just add your API keys! Clear Educational Value:** Learn core concepts like AI model orchestration strategies, customer service automation best practices, and multi-model AI implementation patterns. Immediate Results:** See your AI agent in action, responding to emails and logging data within minutes of setup. 🛠️ Getting Started Checklist: To use this workflow, you'll need: A Gmail account with API access enabled. A Google Sheets document created for logging. A Gemini API key (your primary AI model). An OpenAI API key (your fallback AI model). An n8n instance (cloud or desktop). Embark on your journey to building intelligent, resilient automation systems today!
by Intuz
This n8n template from Intuz provides a complete and automated solution for powerful cold outreach campaigns. It connects a Google Sheet of prospect data with Google Gemini to automatically generate highly personalized emails. By analyzing specific keywords and data points like company name, industry, or job title from your sheet, this automated workflow crafts unique, relevant messages that feel one-to-one, creating a complete system to dramatically improve your engagement and response rates. How it Works Manually writing personalized emails for a long list of leads is a significant bottleneck. This workflow eliminates that friction by creating an automated system that reads your lead list, understands the context, and writes compelling drafts for you. Scheduled Lead Processing:** On a schedule you define (e.g., daily), the workflow automatically activates to process your lead list. Fetches Your Lead List:** It connects to your designated Google Sheet and reads all the lead data you've prepared, such as names, companies, roles, and any custom notes or pain points. Intelligent Filtering:** The workflow is smart enough to know which leads have already been processed. Using an "If" node, it filters out any rows that already contain a generated email, ensuring it only works on new, untouched leads. AI-Driven Personalization (Google Gemini):** This is the core of the engine. For each new lead, it sends the relevant data to the Google Gemini Chat Model. The AI follows a custom prompt you define to draft a completely unique email, including a compelling subject line and a personalized body. Structured Data Output:** The workflow uses a Structured Output Parser to ensure the AI's response is always in a clean, predictable JSON format (e.g., {"subject": "...", "body": "..."}), making the data easy to handle in the next steps. Seamlessly Updates Your Spreadsheet:** Finally, the generated subject line and email body are written back into the correct row for that lead in your Google Sheet, ready for your team to copy, paste, and send. How to Use: Quick Start Guide 1. Import Workflow Template: Download the template’s JSON file and import it into your n8n instance via “File” > “Import from JSON.” 2. Configure Credentials: Google Gemini: Create and apply your API key credentials to the “Google Gemini Chat Model” node. Google Sheets: Set up and apply OAuth credentials for the Google account that owns your lead spreadsheet. Apply this credential to both the "Read Leads from Sheet" and "Update Sheet with Email" nodes. 3. Customize Nodes & Spreadsheet: Prepare Your Google Sheet:** Ensure your sheet has columns for lead data (e.g., FirstName, Company, Role) and empty columns to receive the output (e.g., GeneratedSubject, GeneratedEmail). Read Leads from Sheet:** Double-click this node and select your spreadsheet and sheet name from the list. If Node:** Update the condition to check your specific output column. For example, if your output column is named GeneratedEmail, the condition should check if {{$json.GeneratedEmail }} is empty. Basic LLM Chain Node:** This is the most important step. Edit the Template prompt to match your product, service, and desired tone. In the Template Variables section, make sure the values (e.g., {{ $('Read Leads from Sheet').item.json.FirstName }}) match the exact column names from your Google Sheet. Update Sheet with Email Node:** Select your spreadsheet and sheet name. Set the Lookup Column to a unique identifier for each lead (like their Email address). Then, map the output from the Prepare Data for Sheet node to the correct destination columns in your sheet. 4. Test & Activate: Test Run:** Click “Execute Workflow” to perform a test run. Check your Google Sheet to see if the first unprocessed lead was updated correctly with a new subject and body. Activate:** Once satisfied, toggle the workflow “Active” switch to enable it to run on your defined schedule. Requirements To use this workflow template, you will need: 1. n8n Instance: A running n8n instance (cloud or self-hosted). 2. Google Gemini Account: For generating the email content (requires a Google Gemini API Key from Google AI Studio). 3. Google Sheets Account: With a prepared spreadsheet containing your lead list and columns for the generated output. Connect with us Website: https://www.intuz.com/services Email: getstarted@intuz.com LinkedIn: https://www.linkedin.com/company/intuz Get Started: https://n8n.partnerlinks.io/intuz For Custom Worflow Automation Click here- Get Started
by David Olusola
📝 Auto-Generate Meeting Notes & Summaries (Zoom → Google Docs + Slack) This workflow automatically captures Zoom meeting data when a meeting ends, generates AI-powered notes, saves them to Google Docs, and instantly posts a summary with a link in Slack. ⚙️ How It Works Zoom Webhook → Triggers on meeting.ended or recording.completed. Normalize Data → Extracts meeting details (topic, host, duration, transcript). AI Notes (GPT-4) → Summarizes transcript into key decisions, action items, and next steps. Google Docs → Saves formatted meeting notes + transcript archive. Slack Post → Shares summary + link to notes in #team-meetings. 🛠️ Setup Steps 1. Zoom App Go to Zoom Developer Console → create App. Enable event meeting.ended. Paste workflow webhook URL. 2. Google Docs Connect Google OAuth in n8n. Docs auto-saved in your Google Drive. 3. Slack Connect Slack OAuth. Replace channel #team-meetings. 4. OpenAI Add your OpenAI API key. Uses GPT-4 for accurate summaries. 📊 Example Output Slack Message: 📝 Auto-Generate Meeting Notes & Summaries (Zoom → Google Docs + Slack) This workflow automatically captures Zoom meeting data when a meeting ends, generates AI-powered notes, saves them to Google Docs, and instantly posts a summary with a link in Slack. ⚙️ How It Works Zoom Webhook → Triggers on meeting.ended or recording.completed. Normalize Data → Extracts meeting details (topic, host, duration, transcript). AI Notes (GPT-4) → Summarizes transcript into key decisions, action items, and next steps. Google Docs → Saves formatted meeting notes + transcript archive. Slack Post → Shares summary + link to notes in #team-meetings. 🛠️ Setup Steps 1. Zoom App Go to Zoom Developer Console → create App. Enable event meeting.ended. Paste workflow webhook URL. 2. Google Docs Connect Google OAuth in n8n. Docs auto-saved in your Google Drive. 3. Slack Connect Slack OAuth. Replace channel #team-meetings. 4. OpenAI Add your OpenAI API key. Uses GPT-4 for accurate summaries. 📊 Example Output Slack Message: 📝 New Meeting Notes Available Topic: Marketing Sync Host: david@company.com Duration: 45 mins 👉 Read full notes here: https://docs.google.com/document/d/xxxx Google Doc: Executive Summary Key Decisions Action Items w/ Owners Next Steps Full Transcript ⚡ With this workflow, your team never scrambles for meeting notes again.
by Ali Khosravani
This workflow enriches your WordPress articles by automatically adding an AI-generated heading and a short concluding paragraph. It ensures each post ends with valuable, engaging content to improve user satisfaction, branding, and SEO. How It Works Fetches published articles from your WordPress site via the REST API. Cleans and formats the article text for processing. Sends the content to OpenAI with a structured prompt. AI generates a new heading + 3-line conclusion tailored to the article. Appends the generated text to the original content. Updates the article back in WordPress automatically. Requirements n8n version: 1.49.0 or later (recommended). Active OpenAI API key. WordPress REST API enabled. WordPress API credentials (username + application password). Setup Instructions Import this workflow into n8n. Go to Credentials and configure: OpenAI API (API key). WordPress API (username + application password). Replace https://example.com with your site’s URL. Run manually or schedule it to enhance content automatically. Categories AI & Machine Learning WordPress Content Marketing SEO Tags ai, openai, wordpress, seo, content enhancement, automation, n8n
by Rahul Joshi
Description Automatically score candidate questionnaire responses using Azure OpenAI (GPT-4o-mini), combine them with existing evaluations from Google Sheets, and keep your candidate database up to date—all in near real time. Get consistent, structured scores and key takeaways for faster, fairer decisions. ⚡📊 What This Template Does Monitors new questionnaire submissions in Google Sheets every minute. ⏱️ Evaluates responses with Azure OpenAI and returns structured JSON (score + takeaways). 🤖 Parses model output safely and normalizes fields. 🧩 Retrieves existing candidate data from a central Google Sheet. 📂 Calculates combined final scores and updates/append records by candidate name. ➕ Key Benefits Consistent, objective scoring across all responses. 🎯 Real-time processing from form submission to database update. 🚀 Clear JSON outputs for downstream reporting and analytics. 📈 No-code customization of questions, weights, and fields. 🛠 Scales effortlessly with high submission volumes. 📥 Features Continuous polling of the “BD Questionarie” → “Form Responses 1” sheet. 🔄 AI evaluation with GPT-4o-mini returning score (0–30) and takeaways. 🧠 Resilient JSON parsing (handles code fences and errors). 🧼 Candidate lookup in “Resume store” → “Sheet2” for data fusion. 🔗 Additive scoring model: Final Score = Existing Score + Questionnaire Score. ➕ Append or update records by name while preserving existing data. 📝 Requirements n8n instance (Cloud or self-hosted). 🌐 Google Sheets access: “BD Questionarie” spreadsheet (sheet: “Form Responses 1”) for new responses. “Resume store” spreadsheet (sheet: “Sheet2”) for existing profiles. Credentials configured in n8n (OAuth/Service Account) with read/write where needed. 🔐 Azure OpenAI access with a GPT-4o-mini deployment for evaluation and JSON output. 🤖 Ability to customize evaluation questions and scoring weights within the workflow. ⚙️ Target Audience Teams evaluating candidate questionnaires and consolidating scores. 👥 Operations teams centralizing hiring data in Google Sheets. 🗂️ Organizations seeking real-time, AI-assisted screening. 🧭 No-code/low-code builders standardizing hiring workflows. 🧱 *Step-by-Step Setup Instructions * Connect Google Sheets in n8n Credentials; grant access to “BD Questionarie” and “Resume store.” 🔑 Add Azure OpenAI credentials in n8n; ensure a GPT-4o-mini deployment is available. 🤝 Import the workflow, assign credentials to each node, and set the sheet IDs/ranges. 📋 Confirm name is the matching key, and adjust evaluation weights or questions as needed. ⚖ Run once to validate parsing and score calculation, then enable polling (every minute). ▶️
by Jinash Rouniyar
PROBLEM Thousands of MCP Servers exist and many are updated daily, making server selection difficult for LLMs. Current approaches require manually downloading and configuring servers, limiting flexibility. When multiple servers are pre-configured, LLMs get overwhelmed and confused about which server to use for specific tasks. This template enables dynamic server selection from a live PulseMCP directory of 5000+ servers. How it works A user query goes to an LLM that decides whether to use MCP servers to fulfill a given query and provides reasoning for its decision. Next, we fetch MCP Servers from Pulse MCP API and format them as documents for reranking Now, we use Contextual AI's Reranker to score and rank all MCP Servers based on our query and instructions How to set up Sign up for a free trial of Contextual AI here to find CONTEXTUALAI_API_KEY. Click on variables option in left panel and add a new environment variable CONTEXTUALAI_API_KEY. For the baseline model, we have used GPT 4.1 mini, you can find your OpenAI API key here How to customize the workflow We use chat trigger to initate the workflow. Feel free to replace it with a webhook or other trigger as required. We use OpenAI's GPT 4.1 mini as the baseline model and reranker prompt generator. You can swap out this section to use the LLM of your choice. We fetch 5000 MCP Servers from the PulseMCP directory as a baseline number, feel free to adjust this parameter as required. We are using Contextual AI's ctxl-rerank-v2-instruct-multilingual reranker model, which can be swapped with any one of the following rerankers: 1) ctxl-rerank-v2-instruct-multilingual 2) ctxl-rerank-v2-instruct-multilingual-mini 3) ctxl-rerank-v1-instruct You can checkout this blog for more information about rerankers to learn more about them. Good to know: Contextual AI Reranker (with full MCP docs): ~$0.035/query Includes 0.035 for reranking + ~$0.0001 for OpenAI instruction generation. OpenAI Baseline: ~$0.017/query
by Jinash Rouniyar
PROBLEM Evaluating and comparing responses from multiple LLMs (OpenAI, Claude, Gemini) can be challenging when done manually. Each model produces outputs that differ in clarity, tone, and reasoning structure. Traditional evaluation metrics like ROUGE or BLEU fail to capture nuanced quality differences. Human evaluations are inconsistent, slow, and difficult to scale. This workflow automates LLM response quality evaluation using Contextual AI’s LMUnit, a natural language unit testing framework that provides systematic, fine-grained feedback on response clarity and conciseness. > Note: LMUnit offers natural language-based evaluation with a 1–5 scoring scale, enabling consistent and interpretable results across different model outputs. How it works A chat trigger node collects responses from multiple LLMs such as OpenAI GPT-4.1, **Claude 4.5 Sonnet, and Gemini 2.5 Flash. Each model receives the same input prompt to ensure fair comparison, which is then aggregated and associated with each test cases We use Contextual AI's LMUnit node to evaluate each response using predefined quality criteria: “Is the response clear and easy to understand?” - Clarity “Is the response concise and free from redundancy?” - Conciseness LMUnit** then produces evaluation scores (1–5) for each test Results are aggregated and formatted into a structured summary showing model-wise performance and overall averages. How to set up Create a free Contextual AI account and obtain your CONTEXTUALAI_API_KEY. In your n8n instance, add this key as a credential under “Contextual AI.” Obtain and add credentials for each model provider you wish to test: OpenAI API Key: platform.openai.com/account/api-keys Anthropic API Key: console.anthropic.com/settings/keys Gemini API Key: ai.google.dev/gemini-api/docs/api-key Start sending prompts using chat interface to automatically generate model outputs and evaluations. How to customize the workflow Add more evaluation criteria (e.g., factual accuracy, tone, completeness) in the LMUnit test configuration. Include additional LLM providers by duplicating the response generation nodes. Adjust thresholds and aggregation logic to suit your evaluation goals. Enhance the final summary formatting for dashboards, tables, or JSON exports. For detailed API parameters, refer to the LMUnit API reference. If you have feedback or need support, please email feedback@contextual.ai.
by Oneclick AI Squad
This n8n workflow automates the generation of personalized marketing content for events, including emails, social media posts, and advertisements. Leveraging AI, it tailors content based on event details and target audience preferences, enhancing promotional efforts and engagement for organizers. Key Features Generates customized email, social media, and ad content for event promotion. Personalizes content based on event specifics and audience insights. Streamlines content creation with AI-driven suggestions and formatting. Delivers content ready for distribution across multiple channels. Supports real-time updates and adjustments for campaign optimization. Workflow Process The Webhook for Event Planning node receives event details and marketing preferences to initiate the workflow. The Read Event Details node extracts and organizes event data from Google Sheets for content creation. The Set Variables node defines key parameters and audience targeting criteria. The AI Agent for Event Plan node uses AI to generate optimized marketing content, including emails, social media posts, and ads. The Format Plan node structures the generated content into a polished, actionable format. The Save to Google Sheets node stores the generated content for tracking and future use. The Email Report node compiles a comprehensive event marketing plan and sends it to organizers via email. The Send Email Report node delivers the finalized report to the organizer. Setup Instructions Import the workflow into n8n and configure the Webhook for Event Planning with your event management system's API credentials. Set up Google Sheets integration for the Read Event Details and Save to Google Sheets nodes. Configure the AI Agent for Event Plan node with a suitable language model for content generation. Set up email credentials for the Email Report and Send Email Report nodes. Test the workflow by inputting sample event data to verify content generation and delivery. Monitor the output and adjust AI parameters or node settings as needed for optimal results. Prerequisites Webhook integration with the event management or input system. Google Sheets account for data storage and retrieval. AI/LLM service for content generation and personalization. Email service for report delivery. Access to event details and audience data for customization. Modification Options Modify the Read Event Details node to include additional data fields or sources. Adjust the Set Variables node to incorporate specific audience segments or branding guidelines. Customize the AI Agent for Event Plan node to focus on particular content types (e.g., video scripts, banners). Add social media posting nodes to directly publish content from the Format Plan node. Configure the Email Report node to include additional metrics or campaign analytics.
by Ivan Maksiuta
What this template does Collects the latest crypto news from multiple RSS feeds, filters and deduplicates them, uses OpenAI GPT-4 to analyze and select the top stories, translates and formats them into Russian, and posts a digest to a Telegram channel or group. The workflow runs automatically on a schedule and ensures all messages fit Telegram’s 4096-character limit. How it works (high level) RSS Sources: Reads fresh items from CoinDesk, Cointelegraph, Decrypt, Cryptobriefing, and Nulltx. Filter & Deduplicate: Keeps only unique items from the last 24 hours. AI Analysis (Crypto Analyst): An OpenAI agent identifies the most important events and selects the best article for each. AI Formatting (SMM Editor): Another OpenAI agent writes a styled digest in Russian with Telegram-compatible HTML formatting. Message Preparation: Long texts are split into safe chunks ≤ 4096 characters. Telegram Post: The digest is posted automatically to your configured Telegram channel or group. Prerequisites n8n Cloud or n8n >= 1.107.4 Credentials: OpenAI (gpt-4o-mini or gpt-4.1-mini) Telegram Bot with rights to post in your target chat Setup (5 minutes) Import this workflow into n8n. Open the Telegram node “Post to Group” and set your chatId (e.g., @your_channel or numeric ID). Connect your OpenAI and Telegram credentials. (Optional) Adjust the Scheduler interval (default: every 3 hours). Run once manually to test, then activate. Customization Add or replace RSS sources. Modify the prompts in Crypto Analyst and SMM Editor to adapt tone, style, or language. Swap out the Telegram node to publish on other platforms (Slack, Discord, etc.).
by Thesys
Analyze crypto markets with interactive graphs using CoinGecko and C1 by Thesys This n8n template can answer questions about real-time prices, market moves, trending coins, and token details with interactive UI in real time (cards, charts, buttons) instead of plain text using C1 by Thesys. Data is fetched through the CoinGecko Free MCP tool. 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’s the current price of Bitcoin and Ethereum?” “Give me today’s market summary: total market cap, BTC dominance, top gainers/losers.” “Compare ETH vs SOL over 30 days with a chart.” > Note: This template is for information and visualization, not financial advice. 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: 1️⃣ Thesys API Key You’ll need an API key to authenticate and use Thesys services. 👉 Get your key here 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: 💬 Join the Thesys Community 📧 Email support: support@thesys.dev
by 長谷 真宏
Who is this for This template is perfect for sales professionals, account managers, and business development teams who want to make memorable impressions on their clients. It automates the tedious task of researching gift shops and preparation spots before important meetings. What it does This workflow automatically prepares personalized recommendations for client visits by monitoring your Google Calendar, enriching data from Notion, and using AI to select the perfect options. How it works Trigger: Activates when a calendar event containing keywords like "visit," "meeting," "client," or "dinner" is created or updated Extract: Parses company name from the event title Enrich: Fetches customer preferences from your Notion database Search: Google Places API finds nearby gift shops and quiet cafes Analyze: GPT-4 recommends the best options based on customer preferences Notify: Sends a personalized message to Slack with recommendations Example Slack Output Here's what the final notification looks like: 🎁 Recommended Gift Shop Patisserie Sadaharu AOKI (★4.6) 3-5-2 Marunouchi, Chiyoda-ku 💡 Reason: The customer loves French desserts, so this patisserie's macarons would be perfect! ☕ Pre-Meeting Cafe Starbucks Reserve Roastery (★4.5) 5 min walk from meeting location Set up steps Setup time: approximately 15 minutes Google Calendar: Connect your Google Calendar account and select your calendar Notion Database: Create a customer database with "Company Name" (title) and "Preferences" (text) fields Google Places API: Get an API key from Google Cloud Console and add it to the Configuration node OpenAI: Connect your OpenAI account for AI-powered recommendations Slack: Connect your Slack workspace and update the channel ID in the final node Requirements Google Calendar account Notion account with a customer database Google Places API key (requires Google Cloud account) OpenAI API key Slack workspace with bot permissions How to customize Search radius: Adjust the searchRadius parameter in the Configuration node (default: 1000 meters) Event keywords: Modify the Filter node conditions to match your calendar naming conventions Notification channel: Change the Slack channel ID to your preferred channel