by Varritech
Workflow: Publish to Contentful with Rich Text Formatting ⚡ About the Creators This workflow was created by Varritech Technologies, an innovative agency that leverages AI to engineer, design, and deliver software development projects 500% faster than traditional agencies. Based in New York City, we specialize in custom software development, web applications, and digital transformation solutions. If you need assistance implementing this workflow or have questions about content management solutions, please reach out to our team. 🏗️ Architecture Overview This workflow takes a JSON article payload, splits its markdown content into logical chunks, converts each chunk into Contentful Rich Text JSON via an AI agent, merges the resulting rich text nodes back into a single document, formats the entire entry according to Contentful's field schema, and finally publishes it to Contentful. Trigger → Executes when called by another workflow Split by Headings → Breaks markdown into ##-delimited chunks Markdown → Rich Text → AI agent converts each chunk to Contentful Rich Text JSON Combine Rich Text Objects → Aggregates all chunk outputs into one document Format Entry → Wraps metadata and rich-text content into Contentful schema Publish Entry → HTTP POST to Contentful API 📦 Node-by-Node Breakdown flowchart LR A[When Executed by Another Workflow] --> B[Split by Headings] B --> C[Markdown to Contentful format] C --> D[Combine Rich Text Objects] D --> E[Merge1] E --> F[Format1] F --> G[Create newly formatted Contentful Entry] 1. When Executed by Another Workflow Type: Execute Workflow Trigger Input Example: title, slug, category.id, description, keywords, content, metaTitle, metaDescription, readingTime, difficulty Purpose: Receives the JSON payload from the upstream workflow. 2. Split by Headings Type: Code Logic: Splits input.content into an array of markdown chunks at each second-level heading (##). Emits one item per chunk with index, slug, title, and contentChunk. 3. Markdown to Contentful format Type: LangChain Agent (+ OpenAI Chat model) System Prompt: Defines rules for generating valid Contentful Rich Text JSON (must include nodeType, data:{}, content:[], etc.). Provides examples for paragraphs, headings, lists, links, and images. User Prompt: Here is the markdown content to convert: Purpose: Converts each markdown chunk into an array of rich-text nodes. 4. Combine Rich Text Objects Type: Code Logic: Parses and merges all content arrays returned by the AI agent into one combined content array under a document root. 5. Merge1 Type: Merge Purpose: Joins the original item (with metadata) and the combined rich-text document into a single data stream. 6. Format1 Type: Code Logic: Maps workflow data into the Contentful entry schema by setting each field (title, slug, category link, description, keywords, rich-text content, metaTitle, metaDescription, readingTime, difficulty) under the appropriate locale and structure required by Contentful. 7. Create newly formatted Contentful Entry Type: HTTP Request Method: POST URL: https://api.contentful.com/spaces Headers: Authorization: Bearer token for Contentful Management API Content-Type: application/vnd.contentful.management.v1+json X-Contentful-Version: entry version number X-Contentful-Content-Type: content type ID Body: The formatted fields object produced by the previous node Purpose: Publishes the new entry with rich-text content to Contentful. 🔍 Design Rationale & Best Practices Chunked Conversion Splitting by headings prevents AI context limits and keeps conversions modular. Strict Rich Text Schema Enforcing nodeType, data, and content structure avoids validation errors on Contentful. Two-Phase Merge Separating "combine AI outputs" and "format entry" keeps transformations clear and testable. Idempotent Publish Uses explicit versioning and content type headers to ensure correct entry creation.
by Davide
The Agent Decisioner is a dynamic, AI-powered routing system that automatically selects the most appropriate large language model (LLM) to respond to a user's query based on the query’s content and purpose. This workflow ensures dynamic, optimized AI responses by intelligently routing queries to the best-suited model. Advantages 🔁 Automatic Model Routing:** Automatically selects the best model for the job, improving efficiency and relevance of responses. 🎯 Optimized Use of Resources:** Avoids overuse of expensive models like GPT-4 by routing simpler queries to lightweight models. 📚 Model-Aware Reasoning:** Uses detailed metadata about model capabilities (e.g., reasoning, coding, web search) for intelligent selection. 📥 Modular and Extendable:** Easy to integrate with other tools or expand by adding more models or custom decision logic. 👨💻 Ideal for RAG and Multi-Agent Systems:** Can serve as the brain behind more complex agent frameworks or Retrieval-Augmented Generation pipelines. How It Works Chat Trigger: The workflow starts when a user sends a message, triggering the Routing Agent. Model Selection: The AI Agent analyzes the query and selects the best-suited model from the available options (e.g., Claude 3.7 Sonnet for coding, Perplexity/Sonar for web searches, GPT-4o Mini for reasoning). Structured Output: The agent returns a JSON response with the user’s prompt and the chosen model. Execution: The selected model processes the query and generates a response, ensuring optimal performance for the task. Set Up Steps Configure Nodes: Chat Trigger: Set up the webhook to receive user messages. Routing Agent (AI Agent): Define the system message with model strengths and JSON output rules. OpenRouter Chat Model: Connect to OpenRouter for model access. Structured Output Parser: Ensure it validates the JSON response format (prompt + model). Execution Agent (AI Agent1): Configure it to forward the prompt to the selected model. Connect Nodes: Link the Chat Trigger to the Routing Agent. Connect the OpenRouter Chat Model and Output Parser to the Routing Agent. Route the parsed JSON to the Execution Agent, which uses the chosen model via OpenRouter Chat Model1. Credentials: Ensure OpenRouter API credentials are correctly set for both chat model nodes. Test & Deploy: Activate the workflow and test with sample queries to verify model selection logic. Adjust the routing rules if needed for better accuracy. Need help customizing? Contact me for consulting and support or add me on Linkedin.
by Automate With Marc
This n8n workflow template uses community nodes and is only compatible with the self-hosted version of n8n. 📈 StockPulse: AI-Picked Daily News for Your Portfolio Stay ahead of the market with this automated, AI-powered stock market news briefing delivered straight to your inbox — no code required. Watch Step-by-step Video Tutorial Here: https://www.youtube.com/watch?v=iZvPej9eLYE&t=201s ⚙️ What it does: This workflow runs every morning and: Triggers a scheduled prompt to a Langchain AI Agent (OpenAI) Uses the Tavily Web Search API to fetch fresh financial news relevant to your watchlist or portfolio Summarizes the top stories, highlighting: 🔍 Key headlines 💡 Investment opportunities ⚠️ Risks and macro trends 📊 Suggested trades Sends a clean, readable email via Gmail to your preferred address 🔧 Built with: 🧠 Langchain AI Agent (OpenAI GPT-4o) 🔍 Tavily Search Tool 📬 Gmail Node for Email Delivery ⏰ Daily Cron Trigger (customizable) 💼 Who it’s for: Investors and traders who want to save time on news gathering Financial creators looking for curated, actionable insights Non-technical users interested in automating stock news monitoring Anyone who wants to combine AI + automation + market data 🟢 Customize easily: Edit your stock list or news focus inside the Agent prompt 📨 Email ready: Just plug in your Gmail credentials and you’re good to go ⏱️ 10-minute setup — no coding required!
by Max Mitcham
Want to check out all my flows, follow me on: https://maxmitcham.substack.com/ https://www.linkedin.com/in/max-mitcham/ Email Manager - Intelligent Gmail Classification This automation flow is designed to automatically monitor incoming Gmail messages, analyze their content and context using AI, and intelligently classify them with appropriate labels for better email organization and prioritization. ⚙️ How It Works (Step-by-Step): 📧 Gmail Monitoring (Trigger) Continuously monitors your Gmail inbox: Polls for new emails every minute Captures all incoming messages automatically Triggers workflow for each new email received 📖 Email Content Extraction Retrieves complete email details: Full email body and headers Sender information and recipient lists Subject line and metadata Existing Gmail labels and categories Email threading information (replies/forwards) 🔍 Email History Analysis AI agent checks relationship context: Searches for previous emails from the same sender Checks sent folder for prior outbound correspondence Determines if this is a first-time contact (cold email) Analyzes conversation thread history 🤖 Intelligent Classification Agent Advanced AI categorization using: Claude Sonnet 4 for sophisticated email analysis Context-aware classification based on email history Content analysis for intent and urgency detection Header analysis for automated vs. human-sent emails 🏷️ Smart Label Assignment Automatically applies appropriate Gmail labels: To Respond: Requires direct action/reply FYI: For awareness, no action needed Notification: Service updates, policy changes Marketing: Promotional content and sales pitches Meeting Update: Calendar-related communications Comment: Document/task feedback 📋 Structured Processing Ensures consistent labeling: Uses structured output parsing for reliability Returns specific Label ID for Gmail integration Applies label automatically to the email Maintains classification accuracy 🛠️ Tools Used: n8n: Workflow automation platform Gmail API: Email monitoring and label management Anthropic Claude: Advanced email content analysis Gmail Tools: Email history checking and search Structured Output Parser: Consistent AI responses 📦 Key Features: Real-time email monitoring and classification Context-aware analysis using email history Intelligent cold vs. warm email detection Multiple classification categories for organization Automatic Gmail label application Header analysis for automated email detection Thread-aware conversation tracking 🚀 Ideal Use Cases: Busy executives managing high email volumes Sales professionals prioritizing prospect communications Support teams organizing customer inquiries Marketing teams filtering promotional content Anyone wanting automated email organization Teams needing consistent email prioritization `
by Samir Saci
Tags*: Sustainability, Supply Chain, AI Agent, CO2 Emissions, Carbon Interface API, Logistics, Automation Context Hi! I’m Samir — a Supply Chain Engineer and Data Scientist based in Paris, and founder of LogiGreen Consulting. I help logistics teams reduce their environmental footprint by combining AI automation and carbon estimation APIs. This workflow is part of our green logistics initiative, allowing businesses to track the CO₂ emissions of last-mile or regional shipments. > Automate carbon tracking for shipping operations with n8n! 📬 For business inquiries, feel free to connect with me on LinkedIn Who is this template for? This workflow is designed for logistics coordinators, transportation planners, or sustainability officers who want to estimate and record emissions for B2B shipments. Let’s imagine your carrier sends a shipment confirmation email after a pickup is scheduled: An AI Agent reads the email and extracts structured data: addresses, distance, cargo weight, and delivery time. The Carbon Interface API is then called to calculate CO₂ emissions based on weight and distance, and the results are stored in a Google Sheet. How does it work? This workflow automates the process of tracking CO₂ emissions for scheduled shipments: 📨 Gmail Trigger captures shipment confirmation emails 🧠 AI Agent parses the shipment info (pickup, delivery, weight, distance) 🚚 Carbon Interface API estimates CO₂ emissions 📊 Google Sheets is used to store shipment metadata and carbon results Steps: 💌 Trigger on new shipment confirmation email 🧠 Extract structured shipment info with AI Agent 📋 Store metadata in Google Sheets ⚙️ Call Carbon Interface API with weight and distance 📥 Append estimated CO₂ emissions to the shipment row What do I need to get started? You’ll need: A Gmail account to receive shipment confirmation emails A Google Sheet to track shipment data and CO₂ A free Carbon Interface API key OpenAI access for using the AI Agent parser A few sample emails from your logistics provider to test Next Steps 🗒️ Use the sticky notes in the n8n canvas to: Add your Gmail and Carbon Interface credentials Try with a sample shipment confirmation email Check your Google Sheet to verify emissions and timestamps This template was built using n8n v1.93.0 Submitted: June 7, 2025
by Miquel Colomer
Do you want to create a website screenshot without browser extensions? This workflow creates screenshots of any website using the uProc Get Screenshot by URL tool and sends an email with the screenshots. You need to add your credentials (Email and API Key - real -) located at Integration section to n8n. Node "Create Web + Email Item" can be replaced by any other supported service returning Website and Email values, like Google Sheets, Mailchimp, MySQL, or Typeform. Every "uProc" node returns an image URL of the captured website. This generated URL will remain only 24 hours in our server. You can set up the uProc node with several parameters: width: you can choose one of the predefined values to generate the screenshot, or you can set up a custom width you want. full-page: the tool will return a screenshot of the website from top to bottom with the defined width. In our workflow, we generate two screenshots: 1) One screenshot of 640 pixels width. 2) One full-page screenshot of 640 pixels width. Screenshots are downloaded by "Get File" nodes and saved to the screenshots folder in Dropbox. Finally, we use the Amazon SES node to send an HTML email with both screenshots to the specified email. We will receive the next email:
by isa024787bel
This n8n workflow automates sending out SMS notifications via Vonage which includes new tech-related vocabulary everyday. To build this handy vocabulary improver, you’ll need the following: n8n – You can find details on how to install n8n on the Quickstart page. LingvaNex account – You can create a free account here. Up to 200,000 characters are included in the free plan when you generate your API key. Airtable account – You can register for free. Vonage account – You can sign up free of charge if you aren’t already.
by Tamer
Gmail Daily Summary Scheduler - Template Description Never miss important emails again! This intelligent automation runs every morning at 8 AM to analyze your Gmail inbox from the past 24 hours and delivers a comprehensive summary powered by Google Gemini AI. 🚀 What it does: Automatically triggers daily at 8 AM (customizable) Fetches Gmail emails from the last 24 hours AI analyzes all emails to identify themes and key updates Highlights priority emails with reasons why they're important Delivers structured output in consistent JSON format 💡 Perfect for: Busy professionals managing high email volumes Team leads who need quick inbox overviews Anyone wanting to prioritize email responses efficiently Remote workers staying on top of communications 🎯 Key Features: Smart filtering - Only processes emails from the last 24 hours AI-powered analysis - Uses Google Gemini for intelligent summaries Priority detection - Identifies urgent, time-sensitive emails Consistent output - Structured JSON with summary and highlights Fully automated - Set it and forget it 📋 Sample Output: Summary: "Today's emails covered 3 project updates, 2 meeting requests, and 1 urgent client issue requiring immediate attention." Important Emails: Subject: "Project Deadline Extension Request" | Sender: client@company.com | Reason: Client requesting timeline change for major deliverable due this week Subject: "Tomorrow's Board Meeting Moved" | Sender: assistant@office.com | Reason: Last-minute schedule change requiring immediate calendar adjustment 🛠 Prerequisites: Gmail account with API access Google Gemini API credentials Basic n8n knowledge for credential setup ⚙️ Easy to Customize: Change schedule time (default: 8 AM daily) Adjust time window (default: 24 hours) Modify AI analysis focus Add email filters by sender, subject, etc. Extend with notifications (Slack, email, etc.) 🔒 Privacy Note: This workflow processes email content through Google Gemini API. Ensure compliance with your organization's data policies. Save hours of manual email sorting every week! Import this template and start getting intelligent email summaries delivered automatically every morning.
by Khairul Muhtadin
⚠️ Disclaimer This workflow uses a community node: npm install n8n-nodes-supadata Please make sure to install this before running the workflow. 🔎 Who is this for? This workflow is for anyone who wants quick summaries of YouTube videos, such as researchers, students, analysts, or busy professionals. Just send a video link via Telegram and receive a structured summary in seconds—no need to watch the entire video. 🧠 What problem is this workflow solving? Watching long videos to extract key information is time-consuming. This automation solves that by instantly: Fetching the full transcript of the video Summarizing the content with AI Sending a clean summary directly to Telegram for quick reading It’s a fast and reliable way to stay informed without the overwhelm. ⚙️ What this workflow does 💬 Telegram Trigger Start by sending a YouTube link to your Telegram bot. 🎙️ Get Transcript (Supadata) Uses Supadata API to retrieve the full video transcript. 🧠 Summarize with OpenAI GPT-4o Processes the transcript using a structured prompt to extract: Main theme of the video Target audience Key insights and tips Problems discussed and solutions mentioned Notable quotes or highlights 📨 Send to Telegram The final summary is formatted and sent back to your Telegram chat, ready for reading or saving. 🛠️ Requirements n8n instance (Cloud or self-hosted)** Supadata API Key OpenAI API Key Telegram Bot Token ✅ Output Example The Telegram summary includes: 🎯 Title and topic 💡 Key learnings 🛠️ Tips or insights 🚨 Issues raised and solutions 📝 Quotes or highlights Just send a link, and get the core message—fast. Perfect for learning on the go. 🧠📲 Made by: Khaisa Studio Tag: youtube, summarizer, telegram, openai Category: AI Automation, Video Tools Need a custom? contact me on LinkedIn or Web
by Vlad Temian
Description This workflow creates an automated video content pipeline that generates creative TikTok-style videos using AI. It combines OpenAI's GPT-4o-mini for idea generation with Sisif.ai's text-to-video AI technology to produce engaging short-form content automatically. Perfect for: Content creators, social media managers, marketing teams, and anyone who wants to maintain a consistent flow of AI-generated video content without manual intervention. Prerequisites Sisif.ai Account**: Sign up at sisif.ai and get your API token from sisif.ai/api/ OpenAI Account**: Get your API key from OpenAI platform n8n Instance**: Self-hosted or cloud instance How it Works The workflow operates on a scheduled cycle, generating fresh video content every 6 hours: 🤖 AI Idea Generation: OpenAI's GPT-4o-mini acts as a creative video strategist, generating unique, trend-aware video concepts optimized for TikTok and social media 🎬 Video Creation: Sisif.ai transforms each creative prompt into a high-quality 5-second video in 360x640 resolution ⏱️ Smart Monitoring: The workflow intelligently monitors video generation progress, waiting for completion before proceeding 📊 Data Processing: Final video data is structured and prepared for further use or storage Key Features ⚡ Fully Automated Runs every 6 hours without manual intervention Generates 4 unique videos daily (28 videos per week) Self-monitoring with automatic retry logic 🎯 Optimized for Social Media TikTok-perfect 360x640 resolution 5-second duration for maximum engagement Trend-aware content generation Action-packed, visual storytelling 🔧 Smart Architecture Simple HTTP requests for reliable operation Bearer token authentication for secure API access Automatic status checking and waiting logic Error handling and retry mechanisms
by Roshan Ramani
📧 Morning Mail Summary Ai Agent Simplify your mornings with this automated email summary workflow in n8n, designed for teams and individuals who want a quick, actionable snapshot of their inbox—every day, at a glance. 📌 Features Fully Automated**: Triggers daily at 8 AM IST Targeted Extraction**: Fetches messages from specific senders with dynamic date filtering Structured Data Aggregation**: Pulls key fields (sender, recipients, snippet) AI-Powered Summarization**: Uses LangChain + OpenRouter to generate: Insightful summaries Highlighted issues Assigned action items Memory-Enhanced Context**: Maintains continuity across days Stylish HTML Email Output**: Responsive design with: Summary section Action items Branded footer Team-Ready Sharing**: Auto-distributes to team with CC support 🛠️ How It Works Trigger: Daily schedule in n8n Fetch: Retrieves last 24h emails from target sender Organize: Aggregates email metadata Summarize: AI agent produces structured report: Key updates Critical issues Actionable tasks Send: Emails digest to team 🎯 Ideal For Project managers needing stakeholder briefings Customer success teams tracking communications Leadership staying informed efficiently Anyone streamlining email review 📦 Included Resources Complete n8n workflow JSON (6 nodes) Prompt template for structured summarization (Summary, Issues, Actions, Follow‑Ups). -Styled HTML email template, with responsive design and branding sections. 🆓 Get Started Import JSON into n8n Configure: Gmail / OpenRouter credentials Recipient lists Custom prompts Modify freely for your use case ⭐ Benefits ⏳ Time saved: Skip inbox digging 🔍 Focus: See only what matters ✨ Clarity: Structured tasks & deadlines 🔄 Consistency: Daily alignment for teams
by Rahul Joshi
SEO-Optimized Description: Streamline your interview scheduling process with this intelligent n8n automation template powered by Google Calendar, Google Sheets, and GPT-4. This workflow reads candidate information from a spreadsheet, automatically schedules interviews in Google Calendar, and sends personalized interview invitation emails—all without manual input. What This Template Does: 📋 Monitors a Google Sheet for new candidate entries every minute 🕒 Auto-selects the next available interview slot (Mon/Wed/Fri at 3 PM) 📅 Creates a calendar invite in your Google Calendar ✍️ Uses GPT-4 to generate personalized emails based on candidate data 📧 Sends the email invite with the interview link via Gmail Built-in logic ensures: Candidates never get same-day interviews AI-generated emails are concise, polite, and professionally formatted Scheduling remains conflict-free and easy to manage Requirements: Google Calendar API credentials Google Sheets with candidate info (Name, Email, Background) Gmail account with OAuth2 Azure OpenAI API (GPT-4o recommended) Perfect For: Startups, HR teams, and recruiters looking to automate interview scheduling, eliminate back-and-forth emails, and deliver a professional candidate experience—all with zero hassle.