# templates

name: Create AI-Powered YouTube Shorts with OpenAI, ElevenLabs, 0CodeKit!
author_name: dada
author_username: lin
categories: []
created_at: 2025-04-17T11:00:05.102Z
updated_at: 2025-04-17T11:00:05.102Z
url: https://n8n.io/workflows/3584
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-14 21:18:32
description:
  YouTube Shorts Automation with AI-Powered Video Generation

  Overview

  This workflow automates the creation of engaging YouTube Shorts by leveraging AI tools to generate scripts, audio, images, and videos, then compiles them into a final video ready for upload. It uses OpenAI for script and image prompt generation, ElevenLabs for text-to-speech, Replicate for image and video generation, Cloudinary for audio storage, and Creatomate for final video rendering. The workflow segments the script into 6-second clips, creates corresponding visuals, and combines them with audio, adding smooth transitions for a polished result.

  Why is this workflow useful?

  Creating YouTube Shorts manually is time-consuming, requiring scriptwriting, voiceovers, and video editing. This workflow automates the entire process, enabling creators to produce high-quality, engaging Shorts in minutes. It’s ideal for content creators, marketers, or businesses looking to maintain a consistent social media presence with minimal effort.

  Who is this workflow for?

  Content Creators**: YouTubers or TikTok creators aiming to produce viral Shorts quickly.
  Digital Marketers**: Businesses promoting products or services through short-form video content.
  Hobbyists**: Individuals experimenting with AI-driven video production without advanced editing skills.

  What will you need to use this workflow?

  n8n Account**: Free or paid, hosted on n8n Cloud or self-hosted.
  OpenAI API Key**: For generating scripts and image prompts (GPT-4o-mini model).
  ElevenLabs API Key**: For text-to-speech conversion.
  Replicate API Key**: For generating images and videos.
  Cloudinary Account**: For storing audio files.
  Creatomate API Key**: For rendering the final video.
  Basic JSON Knowledge**: To understand and tweak the workflow output if needed.

  How does this workflow work?

  Trigger: The workflow starts manually via the "Test Workflow" button.
  Script Generation: OpenAI (GPT-4o-mini) generates a script with an intro (40-70 chars), base (280-350 chars), and CTA (55 chars), plus a title and description with hashtags.
  Text-to-Speech: ElevenLabs converts the script into an MP3 audio file with timestamps.
  Audio Upload: The audio is uploaded to Cloudinary for storage.
  Script Segmentation: A Python script segments the audio into 6-second clips, creating transcription chunks.
  Image Prompt Generation: OpenAI generates a visual prompt for each segment in the style of CNSTLL, ensuring simple, animatable visuals.
  Image Generation: Replicate creates a 9:16 image for each segment based on the prompt.
  Video Generation: Replicate’s Minimax model generates 5-second video clips from the images.
  Video Compilation: Creatomate combines the video clips with the audio, adding fade transitions and a final black shape for a smooth close.
  Final Output: The rendered video is retrieved from Creatomate, ready for YouTube Shorts.

  Setup instructions

  Import the Workflow: Copy the provided JSON into n8n and import it as a new workflow.
  Add Credentials:
     Configure OpenAI API credentials for the "Ideator" and "Image Prompter" nodes.
     Set up ElevenLabs API key in the "Script Generator" node.
     Add Replicate API key for the "Request Image," "Request Video," and "Get Video" nodes.
     Configure Cloudinary credentials for the "Upload to Cloudinary" node.
     Set Creatomate API key for the "Editor" and "Get Final Video" nodes.
  Test the Workflow:
     Click "Test Workflow" to run it manually.
     Replace &lt;user-query&gt; in the "Ideator" node with your video topic (e.g., "Fitness tips for beginners").
  Verify Outputs: Check each node’s output, ensuring audio, images, and videos are generated correctly.
  Customize (Optional):
     Adjust segment duration in the "HTTP Request" node’s Python code (default: 6 seconds).
     Modify fade duration or video resolution in the "Create Editor JSON" node.
  Save and Activate: Save the workflow and activate it for regular use.

  Tips for getting the most out of this workflow

  Optimize Prompts**: Use specific, concise queries in the "Ideator" node for better script quality (e.g., "Minimalist home decor ideas").
  Check API Limits**: Ensure your API accounts (OpenAI, ElevenLabs, Replicate, Creatomate) have sufficient credits.
  Experiment with Styles**: Tweak the CNSTLL style in the "Image Prompter" node for unique visuals, but keep prompts simple to avoid AI generation errors.
  Monitor Rendering Time**: Video rendering in Creatomate may take up to 70 seconds; adjust the "Rendering" node’s wait time if needed.
  Add Hashtags**: Enhance the generated description with trending hashtags like #YouTubeShorts, #AI, or niche-specific tags.

  Troubleshooting

  Error in Script Generation**: Verify your OpenAI API key and ensure the query is clear.
  Audio Issues**: Check ElevenLabs API key and confirm the script length fits within API limits.
  Image/Video Failures**: Ensure Replicate API key is valid and prompts are simple (avoid complex scenes or humans).
  Rendering Errors**: Confirm Creatomate API key and check JSON structure in the "Create Editor JSON" node.
  Contact Support**: Reach out to n8n Community Forum or respective API providers for persistent issues.

  Built with

  n8n Nodes**: Manual Trigger, OpenAI, HTTP Request, Set, Split Out, Aggregate, Merge, Wait.
  External Services**: OpenAI (GPT-4o-mini), ElevenLabs (Multilingual v2), Replicate (Flux-Cinestill, Minimax Video-01), Cloudinary, Creatomate.
  Custom Code**: Python for audio segmentation and JSON rendering.

  Example output

  For a query like "Morning routine hacks":

  Script**:
    Intro: "Struggling to start your day right?"
    Base: "Try these 3 morning hacks: 5-min meditation to clear your mind, a quick stretch routine to boost energy, and a cold shower to stay alert. Set your day up for success!"
    CTA: "Save this and try it tomorrow!"
  Title**: "3 Morning Hacks You NEED to Try!"
  Description**: "Kickstart your day with these easy hacks! 🧘‍♀️🚿 #MorningRoutine #Productivity #YouTubeShorts"
  Video**: A 15-second Short with three 5-second clips (meditation scene, stretching POV, cold shower close-up), synced with audio and fade transitions.

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metadata_json:
  {"categories":["automation","content creation","video production","AI/ML integration","social media"],"complexity":"complex","use_cases":["Automated YouTube Shorts creation","Repurposing long-form content into short-form video","Rapid social media content production for marketing","Generating voiceover, visuals, and final rendered videos programmatically","A/B testing short video variations"],"estimated_setup_minutes":45,"required_services":["n8n (Cloud or self-hosted)","OpenAI (GPT-4o-mini)","ElevenLabs (text-to-speech)","Replicate (image & video models)","Cloudinary (audio storage)","Creatomate (video rendering)"],"key_features":["AI script and title/description generation","Text-to-speech conversion with timestamps","Automatic audio segmentation into short clips","AI image prompt generation and 9:16 image creation","AI-driven short video clip generation from images (Replicate) ￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼￼"],"target_audience":["Content creators (YouTubers, TikTokers)","Digital marketers and social media managers","Small businesses and agencies producing short-form video ads/content for clients」「Hobbyists experimenting with AI video production"]}


name: 🤖 AI Restaurant Assistant for WhatsApp, Instagram & Messenger
author_name: Amanda Benks
author_username: amanda
categories: []
created_at: 2025-04-17T11:46:33.900Z
updated_at: 2025-04-17T11:46:33.900Z
url: https://n8n.io/workflows/3585
scraped_at: 2025-09-14 19:11:00
description:
  Hi, I’m Amanda! 💌

  This workflow was created with so much love, care, and attention… especially for you, who runs a restaurant, a cozy little burger place, or a delivery business full of heart. 🥰

  I know how busy your days can be, so I made this sweet AI assistant to help you take care of your customers on WhatsApp, Instagram, Messenger (or Evolution API). It sends your beautiful menu, checks ZIP codes, creates payment links, and even notifies the kitchen when the order is ready. All gentle, all automatic, all with love. 💛

  💡 What this workflow does

  Replies to customers via WhatsApp API, Instagram Direct, Messenger, and Evolution API  
  Checks ZIP codes to see if delivery is available using Google Maps  
  Sends your menu as images, because food should look as good as it tastes 🍕  
  Collects item selections and offers lovely upsells like drinks or extras  
  Creates payment links with the Asaas API  
  Confirms when the payment is complete and sends the order to the kitchen  
  Stores all messages and session data safely in Supabase  
  Uses OpenAI GPT-4o to talk naturally and kindly with your customers

  ⚙️ How to set it up (I’ll guide you with care 🧸)

  Connect your webhook from WhatsApp, Instagram, Messenger, or Evolution API  
  Create a Supabase table called n8n_workflow_followup  
     You can use this ready-made template here:  
       👉 Supabase Sheet Template  
  Add your API keys (OpenAI, Supabase, Google Maps, and Asaas) securely in n8n  
  Customize the AI prompt with your brand’s voice and sweet style 💫  
  Set your delivery radius (default is 10km, but you can change it!)  
  Upload your menu images (from Google Drive, your website, or any link)  
  That’s it! Your assistant is now ready to serve with kindness and automation 💕

  🍯 Works with:

  ✅ n8n Cloud and Self-Hosted n8n  
  🔐 All API credentials are safely stored using n8n’s secure credential manager

  Want something customized just for you?
  Chat with me, I’d love to help 💻💛 Chat via WhatsApp (+55 17 99155-7874)
  .
  .
  .
  Tradução em Português:
  Oi, eu sou a Amanda! 💌
  Esse workflow foi feito com muito carinho, dedicação e cuidado... pensando especialmente em você, que tem um restaurante, lanchonete ou delivery cheio de amor pelo que faz. 🥰

  Eu sei como o dia a dia pode ser corrido, e foi por isso que eu criei esse atendente com IA: pra te ajudar a responder clientes no WhatsApp, Instagram, Messenger (ou Evolution API), enviar cardápio com imagens lindas, calcular entregas, gerar links de pagamento e até avisar a cozinha. Tudo com jeitinho, sem complicação, e com muito coração. 💛

  💡 O que esse fluxo faz

  Atende clientes pelo WhatsApp API, Instagram Direct, Messenger e Evolution API  
  Valida CEP e calcula se o cliente está dentro da área de entrega (usando Google Maps)  
  Envia cardápio com imagens, porque comer começa pelos olhos 🍕  
  Coleta os pedidos e também oferece bebidas e adicionais  
  Gera link de pagamento automaticamente com a API do Asaas  
  Confirma o pagamento e avisa a cozinha quando estiver tudo certo  
  Armazena mensagens, horários e histórico no Supabase  
  Usa o GPT-4o da OpenAI pra conversar de forma educada e natural com seus clientes

  ⚙️ Como configurar (com meu passo a passo cheio de cuidado 🧸)

  Conecte seu webhook do WhatsApp, Instagram, Messenger ou Evolution API  
  Crie uma tabela no Supabase chamada n8n_workflow_followup  
     Você pode usar esse modelo aqui:  
       👉 Planilha modelo Supabase  
  Adicione suas chaves de API do OpenAI, Google Maps, Supabase e Asaas no gerenciador do n8n  
  Personalize o prompt da IA com o nome do seu restaurante, estilo de fala e sua magia 💫  
  Defina a distância máxima de entrega (padrão: 10km)  
  Coloque seus próprios links de imagens do cardápio (pode ser do Drive, site ou CDN)  
  Prontinho! Agora o seu restaurante tem um atendente inteligente, gentil e muito eficiente 💕

  🍯 Funciona com:

  ✅ n8n Cloud e n8n auto-hospedado  
  🔐 E suas credenciais ficam guardadinhas com segurança no próprio n8n, tá bom?

  Quer algo feito especialmente pra você?
  Fala comigo com todo carinho 💻💛 Falar no WhatsApp (+55 17 99155-7874)

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name: AI-Powered WhatsApp Chatbot 🤖📲 for Text, Voice, Images & PDFs with memory 🧠
author_name: Davide
author_username: n3witalia
categories: []
created_at: 2025-04-17T14:22:12.162Z
updated_at: 2025-04-17T14:22:12.162Z
url: https://n8n.io/workflows/3586
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 19:34:30
description:
  This workflow is a highly advanced multimodal AI assistant designed to operate through WhatsApp. It can understand and respond to text, images, voice messages, and PDF documents by combining OpenAI models with smart logic to adapt to the content received.

  🎯 Core Features

  📥 1. Automatic Message Type Detection
  Using the Input type node, the bot detects whether the user has sent:
  Text
  Voice messages
  Images
  Files (PDF)
  Other unsupported content

  💬 2. Smart Text Message Handling
  Text messages are processed by an OpenAI GPT-4o-mini agent with a customized system prompt.
  Replies are concise, accurate, and formatted for mobile readability.

  🖼️ 3. Image Analysis & Description
  Images are downloaded, converted to base64, and analyzed by an image-aware AI model.
  The output is a rich, structured description, designed for visually impaired users or visual content interpretation.

  🎙️ 4. Voice Message Transcription & Reply
  Audio messages are downloaded and transcribed using OpenAI Whisper.
  The transcribed text is analyzed and answered by the AI.
  Optionally, the AI reply can be converted back to voice using OpenAI's text-to-speech, and sent as an audio message.

  📄 5. PDF Document Extraction & Summary
  Only PDFs are allowed (filtered via MIME type).
  The document’s content is extracted and combined with the user's message.
  The AI then provides a relevant summary or answer.

  🧠 6. Contextual Memory
  Each user has a personalized session ID with a memory window of 10 interactions.
  This ensures a more natural and contextual conversation flow.

  How It Works  

  Thisworkflow is designed to handle incoming WhatsApp messages and process different types of inputs (text, audio, images, and PDF documents) using AI-powered analysis. Here’s how it functions:  

  Trigger: The workflow starts with the **WhatsApp Trigger node, which listens for incoming messages (text, audio, images, or documents).  
  Input Routing: The **Input type (Switch node) checks the message type and routes it to the appropriate processing branch:  
    Text: Directly forwards the message to the AI agent for response generation.  
    Audio: Downloads the audio file, transcribes it using OpenAI, and sends the transcription to the AI agent.  
    Image: Downloads the image, analyzes it with OpenAI’s GPT-4 model, and generates a detailed description.  
    PDF Document: Downloads the file, extracts text, and processes it with the AI agent.  
    Unsupported Formats: Sends an error message if the input is not supported.  
  AI Processing: The **AI Agent1 node, powered by OpenAI, processes the input (text, transcribed audio, image description, or PDF content) and generates a response.  
  Response Handling**:  
    For audio inputs, the AI’s response is converted back into speech (using OpenAI’s TTS) and sent as a voice message.  
    For other inputs, the response is sent as a text message via WhatsApp.  
  Memory: The **Simple Memory node maintains conversation context for follow-up interactions.  

  Setup Steps  
  To deploy this workflow in n8n, follow these steps:  

  Configure WhatsApp API Credentials:  
     Set up WhatsApp Business API credentials (Meta Developer Account).  
     Add the credentials in the WhatsApp Trigger, Get Image/Audio/File URL, and Send Message nodes.  

  Set Up OpenAI Integration:  
     Provide an OpenAI API key in the Analyze Image, Transcribe Audio, Generate Audio Response, and AI Agent1 nodes.  

   Adjust Input Handling (Optional):  
     Modify the Switch node ("Input type") to handle additional message types if needed.  
     Update the "Only PDF File" IF node to support other document formats.  

  Test & Deploy:  
     Activate the workflow and test with different message types (text, audio, image, PDF).  
     Ensure responses are correctly generated and sent back via WhatsApp.  

  Need help customizing?  
  Contact me for consulting and support or add me on Linkedin. 

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metadata_json:
  {"categories":["automation","chatbot","AI","messaging","document processing"],"complexity":"complex","use_cases":["WhatsApp-based customer support and conversational automation","Document Q&A and knowledge base retrieval from PDFs","Voice message transcription and automated replies","Image understanding and response (e.g., receipts, photos)","Lead qualification, routing and escalation with context memory"],"estimated_setup_minutes":60,"required_services":["WhatsApp Business API (or Twilio/WhatsApp Cloud API) for messaging/webhooks","OpenAI API (GPT + audio models such as Whisper) or compatible LLM provider","n8n with LangChain nodes (installed/openAi, lmChatOpenAi, agent, memory nodes)","Publicly reachable webhook / hosting for n8n (or tunneling service)","Optional: file storage/hosting (S3, Google Drive) and OCR service for images"],"key_features":["Multimodal input handling: text, voice, images, PDFs","LLM-powered conversational responses (OpenAI via LangChain nodes)","Memory buffer to retain conversational context","Agent node to orchestrate tools and dynamic actions","File extraction and PDF parsing to surface document content into chat flow (extractFromFile node usage and HTTP requests for file fetching/processing)"],"target_audience":["Developers building chatbots/integrations","Automation engineers implementing messaging workflows","Customer support teams wanting WhatsApp automation with context memory"]}


name: Track Daily Product Hunt Launches with Website Verification in Google Sheets
author_name: Ifeoluwa Ajetomobi
author_username: vickylove
categories: []
created_at: 2025-04-17T14:43:40.711Z
updated_at: 2025-04-17T14:43:40.711Z
url: https://n8n.io/workflows/3588
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-14 21:18:32
description:
  This workflow helps you stay updated with daily launches on Product Hunt. It automatically fetches product details (name, tagline, description, and website), checks if the website redirects to another URL, and logs the final information into a Google Sheet.  

  Perfect for indie hackers, product managers, content curators, and anyone tracking daily launches.

  How It Works  

  Schedule Trigger – Runs the workflow daily.
  Set Date – Captures today’s date in ISO format for filtering Product Hunt posts.
  HTTP Request (Product Hunt API) – Retrieves Product Hunt posts for the day using GraphQL.
  Extract Product Info (Code Node) – Parses the response to pull key details:  
     Name  
     Tagline  
     Description  
     Website URL  
  HTTP Request (URL Check) – Follows each website URL to detect if it redirects.
  Merge Data – Combines product info with the final destination URL.
  Google Sheets Node – Appends all processed product info to your sheet.

  Pre-conditions  

  A valid Product Hunt API token
  A Google account with access to Google Sheets
  A Google Sheet already created with the correct columns (see below)
  Connected Google Sheets and HTTP credentials in n8n

  Google Sheets Setup  

  Your spreadsheet should include the following columns (in order):  
  Name  
  Tagline  
  Description  
  Original URL  
  Final URL (after redirect)  

  Ensure your Google Sheets node uses the correct Spreadsheet ID and Sheet Name.

  Setup Instructions  

  Product Hunt API Auth:  
     Replace {{YOUR_PRODUCT_HUNT_API_KEY}} in the HTTP Request headers:
        {
       "Authorization": "Bearer {{YOUR_PRODUCT_HUNT_API_KEY}}"
     }
     
  Google Sheets Node:  
     Connect your Google account.  
     Insert your Spreadsheet ID in the settings.  
     Specify the sheet name (e.g., Daily Launches).  
     Use the “Append” operation and map the 5 data fields accordingly.

  Notes  

  Only fetches the first 10 posts for the day (can be extended).
  Consider adding Slack, Discord, or Email nodes to notify you of new entries.
  Useful for building launch databases, research, or content inspiration.

nodes_used:
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metadata_json:
  {"categories":["automation","integration","data collection"],"complexity":"medium","use_cases":["Track daily Product Hunt launches","Build a launch database for research","Content curation and inspiration","Competitive/product discovery","Monitor redirects and verify product websites"],"estimated_setup_minutes":15,"required_services":["Product Hunt API (GraphQL) with API token","Google Sheets (Google account and Spreadsheet)"],"key_features":["Daily scheduled run","Fetches Product Hunt posts via GraphQL","Parses name, tagline, description, and website","Follows website URLs to detect final redirected URL","Appends results to a Google Sheet (append operation)"],"target_audience":["Indie hackers","Product managers","Content curators and researchers`,`Growth marketers"]}


name: MCP AI Agent Google Calendar - Create, Update & Manage Events
author_name: Amanda Benks
author_username: amanda
categories: []
created_at: 2025-04-17T14:53:38.759Z
updated_at: 2025-04-17T14:53:38.759Z
url: https://n8n.io/workflows/3589
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-14 21:18:32
description:
  Hi! I’m Amanda :) 💖 
  I created this sweet little workflow with lots of love and care, just for you who wants to manage your Google Calendar in a smart and gentle way 💌

  This AI-powered agent connects with MCP (Multi-Channel Protocol) and understands natural language like “book a meeting tomorrow at 3pm”, “reschedule my call to Monday”, or “what events do I have on Wednesday?” — and it does everything quietly and beautifully in your calendar 🧸

  💡 What this lovely agent does

  🗓️ Creates new events in your Google Calendar (with or without guests)  
  ✏️ Updates existing events with new times or details  
  🧹 Deletes events you no longer need  
  🔍 Retrieves scheduled events by date  
  🤖 Works through GPT-4o or any AI via MCP Agent

  ⚙️ How to set it up (gently and step-by-step)

  Webhook is ready for MCP messages at POST /mcp/calendar  
  Connect your Google Calendar account using OAuth2 inside n8n  
  Link it to your favorite AI tool (like LangChain, Typebot, etc.) that can talk to the MCP agent  
  All details like title, time, date, and guests are parsed automatically from natural language 💫

  ✨ Requirements

  Google Calendar connected to n8n  
  n8n instance (Cloud or Self-hosted — both are supported!)  
  An AI interface that talks to the MCP agent (like LangChain or Typebot)  
  MCP Trigger API set up in your n8n environment

  This agent is perfect for therapists, consultants, coaches, small teams, or anyone who wants to keep their calendar flowing naturally and peacefully with a little help from AI 💆‍♀️🧠

  Want something customized just for you?
  Chat with me 💻💛 Chat via WhatsApp (+55 17 99155-7874)
  .
  .
  Tradução para Português:
  💖 Oi! Eu sou a Amanda :)

  Esse fluxinho aqui foi feito com muito cuidado pra você que quer automatizar sua agenda do Google Calendar de forma inteligente, simples e com muito carinho 💌

  Ele funciona como um agente que conversa com outro sistema de IA (via MCP) e consegue entender pedidos como “agende uma consulta amanhã às 15h”, “remarque a reunião para segunda”, ou “quais eventos tenho na quarta?” — tudo isso feito direto no seu calendário, sem você precisar abrir nada 🧸

  💡 O que ele faz com amor

  🗓️ Cria eventos no seu Google Calendar (com ou sem convidados)  
  ✏️ Atualiza eventos já existentes com novos horários  
  🧹 Exclui eventos que você não precisa mais  
  🔍 Busca seus compromissos com base em datas específicas  
  ❤️ Tudo isso com suporte ao modelo GPT-4o via agente MCP

  ⚙️ Como configurar (bem facinho, prometo!)

  Conecte o webhook: o endpoint do MCP já vem prontinho com o caminho mcp/calendar  
  Conecte sua conta do Google Calendar usando o OAuth2 no n8n  
  Adicione a integração do MCP Trigger com seu sistema de IA (LangChain, Typebot, etc.)  
  Todos os campos como título, data, hora e convidados são extraídos automaticamente via IA 💫

  ✨ Requisitos

  Conta Google Calendar integrada ao n8n  
  Instância n8n (Cloud ou Self-hosted)  
  Integração com uma IA que converse com o MCP Agent (como LangChain)  
  Acesso à API MCP ativado no n8n

  Esse agente é ideal pra psicólogos, consultores, times de atendimento, terapeutas — ou qualquer pessoa fofa que quer deixar sua agenda fluindo sozinha, com a ajuda de um toque de inteligência 💆‍♀️🧠

  Quer algo feito só pra você?
  Fala comigo com carinho 💻💛 Falar no WhatsApp (+55 17 99155-7874)

nodes_used:
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metadata_json:
  {"categories":["automation","calendar","AI integration","scheduling","productivity"],"complexity":"medium","use_cases":["Create events from natural language","Update/reschedule existing calendar events","Delete unwanted events","Retrieve events by date or range","Manage guests and event details via AI"],"estimated_setup_minutes":20,"required_services":["Google Calendar (OAuth2)","n8n (Cloud or self-hosted)","MCP (Multi-Channel Protocol) / MCP Trigger","AI provider compatible with MCP (e.g., GPT-4o via LangChain, Typebot)","Public webhook endpoint for MCP (POST /mcp/calendar)"],"key_features":["Natural-language parsing of scheduling requests via MCP AI agent","Create, update, and delete Google Calendar events","Fetch scheduled events by date or range","Support for event guests and details extraction","Prebuilt webhook endpoint and MCP trigger integration"],"target_audience":["therapists","consultants","coaches and solo professionals','small teams and office admins','appointment-based businesses','developers/technical integrators"]}


name: ✨ Meta Ads Campaign Report by Period – Auto-Send via WhatsApp & Email
author_name: Amanda Benks
author_username: amanda
categories: []
created_at: 2025-04-17T15:51:47.721Z
updated_at: 2025-04-17T15:51:47.721Z
url: https://n8n.io/workflows/3591
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-14 21:18:32
description:
  Hi, I’m Amanda 🌷
  I created this workflow with great care to help you simplify your daily reporting routine. If you manage Meta Ads campaigns, you know how time-consuming it can be to open Ads Manager, filter data, and build client reports.

  This automation does all that for you — pulling campaign data by period, calculating key metrics, filtering only what matters, and sending everything via WhatsApp or Email, fully formatted and ready to share.

  What it does

  Collects ad performance data from multiple accounts  
  Filters campaigns and creatives with real results  
  Calculates metrics like CPC, CTR, CPV, conversions, and spend  
  Formats the report clearly and professionally  
  Sends the report via WhatsApp (Evolution API) or Gmail  
  Runs automatically every morning (optional schedule)

  Setup Guide

  Use this Google Sheet template to manage your accounts  
  Connect Google Sheets, Gmail, and Meta Ads to n8n  
  Set your action_type filters (lead, purchase, etc.)  
  Customize your message and delivery time

  Requirements

  Google account connected to n8n  
  Facebook Graph API access  
  WhatsApp via Evolution API (optional)  
  Basic n8n knowledge

  Want it customized for your business?
  Let’s chat → WhatsApp me (+55 17 99155-7874)

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.aggregate","n8n-nodes-base.filter","n8n-nodes-base.stickyNote","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.googleSheets","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.splitInBatches","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.facebookGraphApi","n8n-nodes-base.if","n8n-nodes-base.googleSheets","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.if","n8n-nodes-base.set","n8n-nodes-base.switch","n8n-nodes-base.gmail","n8n-nodes-base.httpRequest","n8n-nodes-base.stickyNote","n8n-nodes-base.noOp","n8n-nodes-base.stickyNote","n8n-nodes-base.code","n8n-nodes-base.code"]

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metadata_json:
  {"categories":["automation","integration","reporting","marketing","data processing"],"complexity":"medium","use_cases":["Daily Meta Ads performance reports","Automated client reporting via WhatsApp or Email","Campaign and creative performance monitoring","Aggregating metrics across multiple ad accounts","Scheduled delivery of formatted reports"],"estimated_setup_minutes":30,"required_services":["Google Sheets","Gmail","Facebook/Meta Graph API (Meta Ads)","WhatsApp via Evolution API (optional)","n8n (connected instance)"],"key_features":["Pulls ad performance data by period from multiple accounts","Filters campaigns and creatives with real results","Calculates key metrics (CPC, CTR, CPV, conversions, spend)","Formats professional, ready-to-share reports","Sends reports via WhatsApp (Evolution API) or Gmail email delivery"],"target_audience":["Digital marketers","Performance marketing teams","Marketing agencies handling clients' Meta Ads accounts`,`Growth teams and analysts"]}


name: Automate Web Interactions with Claude 3.5 Haiku and Airtop Browser Agent
author_name: Airtop
author_username: cesar-at-airtop
categories: []
created_at: 2025-04-17T19:32:52.649Z
updated_at: 2025-04-17T19:32:52.649Z
url: https://n8n.io/workflows/3592
scraped_at: 2025-09-14 19:11:00
metadata_generated_at: 2025-09-14 21:18:31
description:
  About this AI Agent

  This workflow is designed to automate web interactions by simulating a human user, using a combination of the Agent node and AI tools powered by Airtop.

  How does this workflow works?

  Form Submission Trigger: The workflow starts with a form submission trigger node named "On form submission". This node collects user instructions for the web AI agent, including a prompt and an optional Airtop profile name for sites requiring authentication.

  AI Agent: The core of the workflow is the "AI Agent" node, which uses a smart web agent to manage a remote web browser. It is designed to fulfill user requests by interacting with the browser through various tools.

  Browser Session Management

  Start Browser: The "Start browser" node initiates a new browser session and window. It is essential for obtaining the sessionId and windowId required for subsequent operations.
  Session and Window Management: The workflow includes nodes for creating and managing browser sessions and windows, such as "Session" and "Window".
  Web Interaction Tools:

  Load URL: This node loads a specified URL into the browser window.
  Query: The "Query" node allows the agent to ask questions and extract information from the current web page.
  Click: This node simulates clicking on elements within the web page.
  Type: The "Type" node types text into specified elements on the page.
  Session Termination: The "End session" node is used to terminate the browser session once the tasks are completed.

  Output Handling

  Structured Output Parser: This node processes the agent's results into a structured format.

  Output: The final results are set and prepared for output.
  Slack Integration: Although currently disabled, there is a "Slack" node intended to send messages to a Slack channel, potentially for notifications or live view URLs.

  Seting up your agent

  Airtop API Credentials:
  Users must have valid Airtop API credentials to interact with the web browser tools. This includes nodes like "Click", "Query", "Load URL", "End session", "Type", "Session", and "Window".
  Slack API Credentials (Optional):

  If users want to enable Slack notifications, they need to configure Slack OAuth2 credentials. The Slack node is currently disabled but can be used to send messages to a Slack channel.
  Anthropic API Credentials:

  The "Claude 3.5 Haiku" node requires Anthropic API credentials. Users need to have access to this API to utilize the language model features.

nodes_used:
  ["@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.airtopTool","n8n-nodes-base.airtopTool","n8n-nodes-base.airtopTool","n8n-nodes-base.airtopTool","n8n-nodes-base.airtopTool","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.lmChatAnthropic","n8n-nodes-base.formTrigger","n8n-nodes-base.slack","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.set","n8n-nodes-base.airtop","n8n-nodes-base.airtop","n8n-nodes-base.stickyNote","n8n-nodes-base.set","n8n-nodes-base.executeWorkflowTrigger","n8n-nodes-base.slack"]

workflow_json_compressed:
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metadata_json:
  {"categories":["automation","integration","web-automation","AI-agent"],"complexity":"complex","use_cases":["Automate web form submissions and multi-step site interactions","Web data extraction / scraping with contextual queries","Automated UI testing and end-to-end interaction flows","Perform authenticated actions using stored Airtop profiles","Orchestrate complex web workflows via an AI agent and parse structured outputs"],"estimated_setup_minutes":30,"required_services":["Airtop API (remote browser tools and profiles)","Anthropic (Claude 3.5 Haiku) API","Slack OAuth2 (optional, for notifications)","n8n instance"],"key_features":["AI-driven agent (Claude 3.5 Haiku) controlling a remote browser","Browser session & window management (start, session, window, end)","Web interaction tools: Load URL, Query, Click, Type","Support for authenticated Airtop profiles for sites requiring login","Structured output parsing to produce machine-readable results from agent output, form-triggered execution, optional Slack notifications"],"target_audience":["Developers","Automation engineers / RPA practitioners","QA / Test engineers doing end-to-end UI testing or scripted interactions with sites requiring auths/flows used by products/clients"]}


name: Extract Business Leads from Google Maps with Dumpling AI to Google Sheets
author_name: Yang
author_username: yang
categories: []
created_at: 2025-04-17T20:51:09.545Z
updated_at: 2025-04-17T20:51:09.545Z
url: https://n8n.io/workflows/3593
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:31
description:
  Who is this for?

  This workflow is built for marketers, sales teams, agencies, virtual assistants, and anyone who regularly researches or contacts local businesses. It's ideal for building lead lists, tracking competitors, or creating location-specific outreach campaigns.

  What problem is this workflow solving?

  Instead of manually searching Google Maps and copying business info into spreadsheets, this automation pulls structured business data (e.g. restaurants, gyms, service providers) and logs it directly into Google Sheets. It saves hours of work and ensures cleaner, more usable data.

  What this workflow does

  The workflow takes a Google Maps search query (like "best restaurants in New York") and sends it to Dumpling AI. It returns a list of places including their name, address, website, phone number, rating, and more. Each result is split into a row and automatically added to a Google Sheet.

  Setup

  Dumpling AI  
     Sign up at Dumpling AI  
     Generate your API key  
     In the HTTP Request node, select Header Auth and paste your key in the Authorization field

  Google Sheets  
     Create a sheet with tab name Leads  
     Add the following column headers to row 1:  
       Name, Address, Phone number, Website, Rating, Price Level, Type, Booking Link, Position  
     Connect your Google Sheets account and link this sheet in the node

  Customize the Query  
     In the HTTP node, replace the query string (e.g., "best+restaurants+in+New+York") with your own search term

  Run It  
     Use the manual trigger to test  
     Optionally swap in a Schedule or Webhook node to run it automatically

  How to customize this workflow to your needs

  Change the search query to target different cities or business types  
  Use filters to only save leads with a minimum rating or price level  
  Add GPT to summarize listings or qualify leads  
  Swap Google Sheets for Airtable or a CRM system for deeper integration

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.manualTrigger","n8n-nodes-base.httpRequest","n8n-nodes-base.splitOut","n8n-nodes-base.googleSheets"]

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metadata_json:
  {"categories":["automation","integration","data extraction","lead generation"],"complexity":"simple","use_cases":["Build local business lead lists","Competitor or market research","Location-specific outreach campaigns","Automating data entry into Google Sheets","Qualifying or enriching prospect data"],"estimated_setup_minutes":10,"required_services":["Dumpling AI (API key)","Google Sheets (Google account)"],"key_features":["Send Google Maps-style queries to Dumpling AI and receive structured place data","Extract fields: name, address, phone, website, rating, price level, type, booking link, position","Split results into individual rows and append to a Google Sheet","Easy query customization and scheduling via webhook/scheduler","Optional enrichment/filters (e.g., minimum rating) or swap Google Sheets for CRM/Airtable"],"target_audience":["Marketers","Sales teams","Agencies and consultants doing local outreach or research"]}


name: 🧠 FloWatch 👁️ Analyze and Diagnose n8n Workflow Errors via OpenAI and Email
author_name: RealSimple Solutions
author_username: joeperes
categories: []
created_at: 2025-04-17T23:41:56.986Z
updated_at: 2025-04-17T23:41:56.986Z
url: https://n8n.io/workflows/3595
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-14 21:18:32
description:
  🧠 Analyze and Diagnose n8n Workflow Errors Automatically via OpenAI and Email



  &gt; ⚠️ This template is available on ☁️ Cloud & 🖥️ self-hosted n8n instances with the OpenAI node enabled.

  👤 Who is this for?

  This workflow is designed for n8n developers, automation engineers, and DevOps teams who want to automatically capture and analyze workflow errors, and receive professional HTML-styled diagnostics directly in their inbox.

  💥 What problem does this solve?

  Manually troubleshooting failed workflows in n8n can be time-consuming. This template streamlines error detection by:

  Capturing workflow failures using the Error Trigger node
  Diagnosing root causes with the help of OpenAI
  Sending a fully-formatted, human-readable HTML error report via email
  Including practical resolutions and next-step suggestions

  This helps you or your team resolve issues faster and avoid repeated manual debugging.

  ⚙️ What this workflow does

  ⚡ Triggers on any n8n workflow error
  📦 Extracts relevant error metadata including node, execution ID, and timestamps
  🧠 Sends error content to OpenAI for analysis and recommendations
  💌 Generates an HTML email report with inline styles and clear formatting
  📥 Emails the result to a system administrator or support email

  🛠️ Setup

  Install the OpenAI node in your self-hosted n8n instance.
  Add your OpenAI API Key securely in credentials.
  Configure the SMTP Email node with your email credentials.
  Adjust the Error Trigger to monitor specific workflows or all workflows.
  Set your preferred admin or dev email address in the final node.

  🔧 How to customize this workflow to your needs

  🧩 Use a [Set node] to define your variables, such as:
    Default admin email
    Workflow filter (optional)
  ✍️ Customize the prompt sent to OpenAI if you want deeper or more specific analysis
  🎨 Modify the email HTML styles to match your brand or internal format
  💾 Add additional logging (e.g., to Airtable, Google Sheets, or Notion) for long-term error tracking

  📌 Sticky Note

  Title: Automated Error Reporter with AI-Powered Diagnosis  
  Description: Captures any n8n error, sends it to OpenAI, and emails a beautiful HTML report to the administrator with steps to resolve the issue. Requires OpenAI credentials and SMTP configured.

nodes_used:
  ["n8n-nodes-base.errorTrigger","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.if","n8n-nodes-base.n8n","n8n-nodes-base.code","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.set","n8n-nodes-base.gmail","n8n-nodes-base.code"]

workflow_json_compressed:
  [encoded data, 6260 characters]

metadata_json:
  {"categories":["automation","monitoring & alerting","error handling","integration"],"complexity":"medium","use_cases":["Automated capture of n8n workflow failures","AI-powered root-cause analysis of errors","Send formatted HTML diagnostic emails to admins/support","Streamline incident triage and reduce manual debugging time","Optional logging of errors to external systems"],"estimated_setup_minutes":20,"required_services":["n8n Cloud or self-hosted n8n with OpenAI node enabled","OpenAI API (OpenAI key)","SMTP/email provider (e.g., Gmail, SendGrid)"],"key_features":["Triggers on any n8n workflow error using Error Trigger node","Extracts error metadata (node, execution ID, timestamps)","Sends error details to OpenAI for analysis and remediation suggestions","Generates a styled HTML email report with actionable steps","Configurable admin email and workflow filters via Set node(s)"],"target_audience":["n8n developers","Automation engineers","DevOps/SRE teams responsible for n8n workflows」「Support/ops teams receiving error reports"]}


name: Daily AI News Translation & Summary with GPT-4 and Telegram Delivery
author_name: SamirLiu
author_username: samir
categories: []
created_at: 2025-04-18T07:05:41.418Z
updated_at: 2025-04-18T07:05:41.418Z
url: https://n8n.io/workflows/3596
scraped_at: 2025-09-14 19:11:00
metadata_generated_at: 2025-09-14 21:18:31
description:
  📝 What this workflow does

  Every morning at 8 a.m., this workflow fetches the latest AI-related articles from both GNews and NewsAPI. It merges up to 40 new articles daily, selects the 15 most relevant ones on AI technology and applications, and uses GPT-4.1 to generate concise summaries in accurate Traditional Chinese (while preserving essential English technical terms). Each summary also includes the article link for easy referral. The compiled digest is then posted to your designated Telegram account or group.

  👥 Who is this for?

  AI enthusiasts, professionals, and anyone interested in artificial intelligence news
  Individuals and teams wanting a concise daily digest of AI developments in Traditional Chinese
  Telegram users who prefer automated information delivery

  🎯 What problem does this workflow solve?

  With the rapid evolution of AI technology, it can be overwhelming to keep up with new developments. This workflow addresses information overload by automatically collecting, summarizing, and translating the most important AI news each morning — all delivered conveniently to your chosen Telegram channel or group.

  ⚙️ Setup

  🔑 Add NewsAPI and GNews API Keys
      Register for accounts on NewsAPI.org and GNews to obtain your API keys.
      Input your NewsAPI key directly into the Fetch NewsAPI articles node.
      Input your GNews API key into the Fetch GNews articles node.
  🤖 Set up your Telegram Bot
      Create a Telegram Bot via BotFather and copy the generated Bot Token.
      In n8n, create Telegram Bot credentials using this token.
      In the Send summary to Telegram node, enter the chat ID of your target user, group, or channel to receive the messages.
  🧠 Configure OpenAI Credentials
      In n8n, create a new credential using your OpenAI API key.
      Assign this credential to the GPT-4.1 Model node (or equivalent OpenAI/AI nodes).

  After completing these steps, your workflow is fully configured to fetch, summarize, and deliver daily AI news to your selected Telegram chat automatically.

  🛠️ How to customize this workflow

  🔍 Change the topic:** Update the keywords in the NewsAPI and GNews nodes for other subjects (e.g., "blockchain", "quantum computing").
  ⏰ Adjust delivery time:** Modify the scheduled trigger to your preferred hour.
  ✍️ Tweak summary style or language:** Refine the prompt in the AI summarizer node for different tones or translate into other languages as needed.

  📦 Dependencies

  NewsAPI account
  GNews account
  Telegram Bot
  OpenAI API access (for GPT-4.1) or compatible AI model for Langchain agent

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.merge","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.stickyNote","n8n-nodes-base.telegram"]

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metadata_json:
  {"categories":["automation","integration","news aggregation","summarization","translation"],"complexity":"medium","use_cases":["Daily AI news digest","Automated translation of news into Traditional Chinese","Curating and distributing relevant AI articles to teams or communities","Monitoring AI developments for research or product teams","Content curation for newsletters or social channels"],"estimated_setup_minutes":20,"required_services":["NewsAPI (NewsAPI.org)","GNews API","OpenAI (GPT-4.1) or compatible AI model","Telegram Bot / Telegram API"],"key_features":["Scheduled daily fetch of AI articles (configurable time)","Merge and deduplicate articles from NewsAPI and GNews","Selects top ~15 most relevant AI articles","Generates concise summaries in Traditional Chinese while preserving key English technical terms","Includes article links in each summary for reference and citation supportsends compiled digest to a Telegram chat or channel"],"target_audience":["AI enthusiasts","Developers and engineers","Product managers and researchers tracking AI news','Community managers and marketers who distribute updates"]}


name: Log meal nutrients from Telegram to Google Sheets using an AI agent
author_name: PollupAI
author_username: zeerobug
categories: []
created_at: 2025-04-18T08:53:18.483Z
updated_at: 2025-04-18T08:53:18.483Z
url: https://n8n.io/workflows/3599
scraped_at: 2025-09-14 19:11:01
description:
  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

nodes_used:
  ["@n8n/n8n-nodes-langchain.chatTrigger","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.telegram","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.limit","n8n-nodes-base.telegramTrigger","n8n-nodes-base.if","n8n-nodes-base.set","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.splitOut","n8n-nodes-base.code","n8n-nodes-base.googleSheets","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.telegram","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 5048 characters]


name: LINE Chatbot with Google Sheets Memory and Gemini AI
author_name: Jakkrapat Ampring
author_username: guitarpmacc
categories: []
created_at: 2025-04-18T09:18:31.925Z
updated_at: 2025-04-18T09:18:31.925Z
url: https://n8n.io/workflows/3600
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:32
description:
  Main Use Case
  This workflow enables automated, AI-assisted replies to users messaging a LINE Official Account, while storing and referencing chat history from Google Sheets to maintain context. Ideal for businesses or support teams that want to provide smart, personalized customer interactions using AI with memory.

  How It Works (Step-by-Step)
  Connect to LINE Official Account's API
  A Webhook listens for incoming messages from users on LINE.
  When a message is received, it triggers the workflow.

  Prepare the Data
  An Edit Fields module structures incoming data (e.g. extracts user ID, message content).
  This ensures data is clean and usable downstream.

  Retrieve Chat History
  The user’s previous conversations are fetched from a Google Sheet.
  This ensures the AI has memory and can continue conversations contextually.

  Prepare Prompt
  The retrieved chat history is combined with the new message to form a complete prompt for the AI.
  Example format: “User previously said X. Now they said Y. How should we respond?”

  AI Agent: Google Gemini
  The formatted prompt is passed to an AI Agent (Google Gemini Chat Model).
  The AI generates a response based on the message + history.
  Tools used: Chat ModeMemory, ToolOutputParser for accurate replies.

  Split & Clean History
  The conversation history is split into smaller chunks for cleaning and storage.
  This ensures the Google Sheet remains readable and manageable over time.

  Save Chat History
  The cleaned new message and AI reply are saved to Google Sheets.
  This updates the chat history for future context.

  Send Reply to LINE
  The AI-generated reply is sent back to the user via a POST HTTP Request to the LINE Messaging API.

  How to Set Up
  Prerequisites:
  LINE Official Account
  Google Sheet to store chat history
  Google Gemini API or AI agent with context memory
  Automation platform (e.g., n8n, as this seems visually similar)

  Step-by-Step:
  Create a Webhook on LINE:
  Set the webhook URL to your automation service.
  Enable webhook events.

  Design Your Google Sheet:
  Create a sheet with columns: User ID, Timestamp, Message, AI Reply.

  Set Up Modules in Automation Platform:
  Webhook: receives user messages.
  Edit Fields: extract user ID and message.
  Google Sheets Read: fetch message history.
  Prompt Composer: format prompt using past history + new message.
  AI Agent: connect to Google Gemini for smart replies.
  Split & Clean: clean and chunk history if needed.
  Google Sheets Write: save the updated conversation.
  HTTP Request: send reply to LINE via Messaging API.

  Test Your Workflow:
  Send a message from LINE.
  Watch the full loop: receive → process → AI → store → reply.

  Deploy & Monitor:
  Ensure error handling is in place (e.g., for blank messages or failed API calls).
  Regularly check your Google Sheets for storage limits. (If limits reached, you can increase the history row.)

  📦 Benefits
  Maintains context in conversations
  Personalized, AI-driven responses
  Easy history tracking via Google Sheets
  Fully automated and scalable

nodes_used:
  ["n8n-nodes-base.webhook","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","n8n-nodes-base.set","n8n-nodes-base.httpRequest","n8n-nodes-base.googleSheets","n8n-nodes-base.set","n8n-nodes-base.googleSheets","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.code","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
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metadata_json:
  {"categories":["chatbot","automation","integration","AI","data storage"],"complexity":"medium","use_cases":["Automated customer support replies with context","Personalized conversational commerce or lead qualification","Maintaining conversation memory for follow-ups","Logging and auditing chat interactions for analysis","FAQ or rule-based escalation with AI assistance"],"estimated_setup_minutes":45,"required_services":["LINE Messaging API (LINE Official Account)","Google Sheets (Google account)","Google Gemini API / Gemini Chat agent (or equivalent AI agent)","n8n or similar automation/orchestration platform","Publicly reachable webhook / HTTP endpoint"],"key_features":["Webhook-triggered message intake from LINE","Extracting and normalizing incoming fields","Fetching and combining past chat history from Google Sheets","Prompt composition combining history + new message","AI-powered response generation via Google Gemini (chat + memory) with output parsing tools (ToolOutputParser)"],"target_audience":["Customer support teams","Small and medium businesses","Developers / automation engineers implementing chatbots for clients or internal tools"]}


name: Scrape Indeed Job Listings for Hiring Signals Using Bright Data and LLMs
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-04-18T10:30:44.845Z
updated_at: 2025-04-18T10:30:44.845Z
url: https://n8n.io/workflows/3601
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:32
description:
  Scrape Indeed Job Listings for Hiring Signals Using Bright Data and LLMs

  How the flow runs
  Fill the form with job position you're hunting for.
  Bright data's scraper will scrape Indeed based on your requirments.  
  Workflow waits for the snapshot.  
  Data returns as JSON.  
  Jobs append to Google Sheets.  
  Each row goes to an LLM to analyze if you're a good fit for the job (based on your prompts).  
  The LLMswrites YES or NO next to each job opportunity, helping you find job posts that are relevant to you.

  What you need
  Google Sheets with our template.  
  Bright Data dataset and API key.  
  OpenAI key for GPT‑4o mini (or any other LLM).  
  n8n with required nodes.

  Form fields To Fill
  Job Location** – city or region.  
  Keyword** – role or skills.  
  Country** – two‑letter code.

  Setup steps
  Copy the sheet template link.  
  Import the JSON workflow. 
  Add your credentials in nodes.  
  Test the form manually.  
  Add a schedule if desired.

  Bright Data filter example
  [
    {
      "country": "US",
      "domain": "indeed.com",
      "keyword_search": "Growth Marketer",
      "location": "Miami",
      "date_posted": "Last 24 hours"
    }
  ]

  Tips
  -Choose Last 24 hours often.

  -Increase wait time for big snapshots.

  -Narrow keywords to save credits.


  **Need help?
  **Email me anytime: 
  Yaron@nofluff.online
  YouTube: @YaronBeen
  LinkedIn: https://www.linkedin.com/in/yaronbeen/

  Bright Data Docs: https://docs.brightdata.com/introduction

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metadata_json:
  {"categories":["web-scraping","automation","data-processing","recruiting"],"complexity":"medium","use_cases":["Automated scraping of Indeed job listings","Detecting hiring signals and relevance for a specific candidate","Populating and maintaining a Google Sheet with fresh job data","Using LLMs to classify/job-fit (YES/NO) per listing","Scheduled monitoring of new job postings"],"estimated_setup_minutes":30,"required_services":["Bright Data (dataset + API key)","Google Sheets (with provided template)","OpenAI (GPT-4o mini or any compatible LLM API key)","n8n (self-hosted or cloud instance)"],"key_features":["User form to input job keyword, location, and country","Bright Data scraper triggers and waits for snapshot results","Parsed job JSON appended to Google Sheets","Row-by-row LLM analysis to mark YES/NO fit based on user prompts","Support for scheduling and snapshot timing adjustments (wait time tuning and filters)"],"target_audience":["Job seekers looking to automate job discovery","Recruiters / talent sourcers","Growth marketers and professionals tracking openings in specific roles/regions"]}


name: Gmail MCP Server – Your All‑in‑One AI Email Toolkit
author_name: Brian Money
author_username: aspereo
categories: []
created_at: 2025-04-18T20:12:47.018Z
updated_at: 2025-04-18T20:12:47.018Z
url: https://n8n.io/workflows/3605
scraped_at: 2025-09-14 19:11:00
metadata_generated_at: 2025-09-14 21:18:31
description:
  Gmail MCP Server
  Expose Gmail’s full API as a single SSE “tool server” endpoint for your AI agents.

  What it does
  Spins up an MCP Trigger that streams Server‑Sent Events to LangChain/N8N AI Agent nodes. ​

  Maps 20+ common Gmail operations (search, send, reply, draft, label & thread management, mark read/unread, delete, etc.) to ai_tool connections, so agents can invoke them with a simple JSON payload. 

  Why you’ll love it
  Agent‑ready: Plug the SSE URL into any N8N Agent or any other AI tool that uses MCP and start reasoning over email immediately.

  Extensible: Add more GmailTool operations or swap credentials without touching your agent logic.

  How to use
  Import the workflow (n8n ≥ v1.88).

  Set up a gmailOAuth2 credential and select it on the GmailTool nodes.

  Open the Gmail MCP Server node, copy the SSE URL, and paste it into your AI agent’s “Tool Server” field.

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metadata_json:
  {"categories":["automation","integration","ai","email"],"complexity":"medium","use_cases":["Expose Gmail to AI agents via MCP/SSE","Automated email reading, searching and triage by agents","Agent-driven send/reply/draft workflows","Label, thread and mailbox management by AI","Rapid prototyping of email assistant capabilities"],"estimated_setup_minutes":20,"required_services":["Gmail (Google API) with OAuth2 credentials","n8n (v1.88 or newer) instance","AI agent or tool that supports MCP/SSE (e.g., LangChain, n8n Agent)"],"key_features":["Provides a single SSE/MCP tool-server URL exposing Gmail API","Maps 20+ common Gmail operations (search, send, reply, draft, labels, threads, mark read/unread, delete, etc.)","Agent-ready: plug-and-play with MCP-compatible AI agents","Credential-swappable and extensible: add operations without changing agent logic","Streams Server‑Sent Events for real‑time agent interaction"],"target_audience":["Developers building AI agents","AI/ML engineers integrating email into agent workflows","Automation engineers and IT teams managing email workflows"]}


name: Document Analysis & Chatbot Creation with Llama Parser, Gemini LLM & Pinecone DB
author_name: pavith
author_username: pavith
categories: []
created_at: 2025-04-19T06:23:10.288Z
updated_at: 2025-04-19T06:23:10.288Z
url: https://n8n.io/workflows/3606
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:32
description:
  📄Description
  This automation workflow enables users to upload files via an N8N form, automatically analyzes the content using Google Gemini agents, and delivers the analyzed results via email along with a chatbot link. The system leverages Llama Cloud API, Google Gemini LLM, Pinecone vector database, and Gmail to provide a seamless, multilingual content analysis experience.

  ✅ Prerequisites
  Before setting up this workflow, ensure the following are in place:

  An active N8N instance.

  Access to Llama Cloud API.

  Google Gemini LLM API keys (for Translator & Analyzer agents).

  A Pinecone account with an active index.

  A Gmail account with API access configured.

  Basic knowledge of N8N workflow setup.

  ⚙️ Setup Instructions
  Deploy the N8N Form

  Create a public-facing form using N8N.

  Configure it to accept:

  File uploads.

  User email input.

  File Preprocessing

  Store the uploaded files temporarily.

  Organize and preprocess them as needed.

  Content Extraction using Llama Cloud API

  Feed the files into the Llama Cloud API.

  Extract and parse the content for further processing.

  Translation (if required)

  Use a Translator Agent (Google Gemini).

  Check if the content is in English. If not, translate it.

  Content Analysis

  Forward the (translated) content to the Analyzer Agent (Google Gemini).

  Perform deep analysis to extract insights.

  Vector Storage in Pinecone

  Store both:

  The parsed and translated content.

  The analyzed content.

  Use Pinecone to store the content as embeddings for chatbot use.

  User Notification via Gmail

  Send the analyzed content and chatbot link to the user’s provided email using Gmail API.

  🧩 Customization Guidance
  To add more languages: Update the translation logic to include additional language support.

  To modify analysis depth: Adjust the prompts sent to the Gemini Analyzer Agent.

  To change the chatbot behavior: Retrain or reconfigure the chatbot to utilize the new Pinecone index contextually.

  🔁 Workflow Summary
  User uploads files and email via N8N form.

  Files are parsed using Llama Cloud API.

  Content is translated (if needed) using Gemini Translator Agent.

  Translated content is analyzed by the Gemini Analyzer Agent.

  Parsed and analyzed data is stored in Pinecone.

  User receives email with analyzed results and a chatbot link.

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metadata_json:
  {"categories":["automation","document processing","NLP/AI","knowledge management","chatbot"],"complexity":"complex","use_cases":["Automated document ingestion and semantic analysis","Multilingual content translation and summarization","Building a searchable chatbot over uploaded documents","Emailing analysis results and delivering chatbot access","Creating embeddings for knowledge-base search and retrieval"],"estimated_setup_minutes":90,"required_services":["n8n instance (hosted or self‑hosted)","Llama Cloud API","Google Gemini LLM API (Translator & Analyzer agents)","Pinecone (vector DB and active index)","Gmail API (for sending notifications)","Mistral Cloud (used for embeddings in workflow)"],"key_features":["Public file-upload form to collect documents and user email","File parsing and preprocessing via Llama Cloud API","Automatic language detection and translation with Gemini","Deep content analysis using Gemini Analyzer agents","Embeddings generation and storage in Pinecone for retrieval/QA chatbot use"],"target_audience":["Developers building AI document workflows","ML/AI engineers integrating LLMs and vector DBs","Data engineers/analysts needing automated content processing pipelines"]}


name: Find High-Intent Sales Leads by Scraping Glassdoor with Bright Data & GPT
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-04-19T06:36:28.418Z
updated_at: 2025-04-19T06:36:28.418Z
url: https://n8n.io/workflows/3607
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-14 21:18:32
description:
  🔍 Scrape Glassdoor with Bright Data

  Designed for sales teams, recruiters, and marketers aiming to automate job discovery and prospecting.

  This workflow scrapes Glassdoor job listings using Bright Data and automatically generates targeted pitches using AI, streamlining lead identification and outreach.

  🧩 How It Works

  This automation leverages n8n, Bright Data, Google Sheets, and OpenAI:

  1. Trigger
  Starts with a custom form input (Location, Keyword, Country).

  2. Bright Data Job Scrape
  Triggers a Bright Data dataset snapshot via HTTP Request.
  Polls snapshot progress using a Wait node, ensuring data readiness.
  Retrieves full job listings dataset once ready.

  3. Google Sheets Integration
  Writes detailed job data (company, role, location, overview, metrics) into a Google Sheet.
  Uses a pre-built template for organized data storage.

  4. Automated Pitch Generation (AI)
  Splits listings into actionable parts: company name, title, and description.
  Sends data to OpenAI (via LangChain) to generate relevant pitches or icebreakers.
  Saves generated content back into the same sheet for easy access.

  ✅ Requirements

  Ensure you have the following:

  Google Sheets
  Google account  
  Template Sheet with columns for job details and AI-generated pitches

  Bright Data
  Active account with Dataset API access  
  API key and dataset ID

  OpenAI
  Valid OpenAI API key for GPT models

  n8n Environment
  Nodes: HTTP Request, Wait, If, Google Sheets, Split Out, LangChain (OpenAI)
  Credentials:
    Google Sheets OAuth2
    Bright Data API credentials
    OpenAI API key

  ⚙️ Setup Instructions

  Step 1: Prepare Google Sheets  
  Copy the provided Google Sheets template  
  Do not change headers

  Step 2: Import & Configure Workflow in n8n  
  Import the workflow JSON file  
  Set Google Sheets node:
    Link to your copied sheet  
    Confirm correct tab name  

  Step 3: Configure Bright Data  
  Replace &lt;YOUR_BRIGHT_DATA_API_KEY&gt; with your real key  
  Set your dataset ID in all HTTP Request nodes

  Step 4: Configure OpenAI (LangChain)  
  Connect OpenAI API key to the LangChain node  
  Customize prompt to match tone and outreach style

  Step 5: Testing & Scheduling  
  Test via manual form trigger  
  Schedule runs or leave form enabled for on-demand use

  🧠 Tips & Best Practices

  Use specific keywords and locations for better results  
  Adjust polling intervals based on dataset size  
  Refine AI prompts regularly to improve pitch quality  
  Clean unused columns from your sheet to boost performance

  💬 Support & Feedback

  For help or customization:

  📧 Email: Yaron@nofluff.online  
  📺 YouTube: @YaronBeen  
  🔗 LinkedIn: linkedin.com/in/yaronbeen  

  📚 Bright Data Docs: docs.brightdata.com/introduction

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metadata_json:
  {"categories":["automation","data extraction","integration","lead generation","AI content generation"],"complexity":"medium","use_cases":["Find high-intent job-based sales leads","Recruiter sourcing and talent discovery","Automated outreach / personalized pitch generation","Market and hiring trend research"],"estimated_setup_minutes":45,"required_services":["Bright Data (Dataset API)","OpenAI (via LangChain)","Google Sheets (Google account)","n8n environment"],"key_features":["Scrapes Glassdoor job listings via Bright Data dataset snapshots","Polls snapshot progress and retrieves completed datasets","Writes structured job data into a predefined Google Sheets template","Splits listings and generates targeted pitches/icebreakers using OpenAI (LangChain)","Stores generated outreach copy back into the sheet for easy access and follow-up"],"target_audience":["Sales teams / SDRs","Recruiters and talent sourcers","Marketing and growth teams focused on outbound outreach"]}


name: Summarize YouTube Videos into Structured Content Ideas with AI and Airtable
author_name: Batu Öztürk
author_username: theozturkbatu
categories: []
created_at: 2025-04-19T14:53:57.801Z
updated_at: 2025-04-19T14:53:57.801Z
url: https://n8n.io/workflows/3609
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-14 21:18:32
description:
  Extract the main idea and key takeaways from YouTube videos and turn them into Airtable content ideas

  📝 Description
  Automatically turn YouTube videos into clear, structured content ideas stored in Airtable. This workflow pulls new video links from Airtable, extracts transcripts using a RapidAPI service, summarizes them with your favourite LLM, and logs the main idea and key takeaways—keeping your content pipeline fresh with minimal effort.

  ⚙️ What It Does
  Scans Airtable for new YouTube video links every 5 minutes.

  Extracts the transcript of the video using a third-party API via RapidAPI.

  Summarizes the content to generate a main idea and takeaways.

  Updates the original Airtable entry with the insights and marks it as completed.

  🛠 Prerequisites
  Before using this template, make sure you have:

  ✅ A RapidAPI account with access to the youtube-video-summarizer-gpt-ai API.

  ✅ A valid RapidAPI key.

  ✅ An OpenAI, Claude or Gemini account connected to n8n.

  ✅ An Airtable account with a base and table ready.

  🧰 Setup Instructions
  Clone this template into your n8n workspace.

  Open the Get YouTube Sources node and configure your Airtable credentials.

  In the Get video transcript node:

  Enter your X-RapidAPI-Key under headers.

  The API endpoint is pre-configured.

  Connect your LLM credentials to the Extract detailed summary node.

  (Optional) Adjust the summarization prompt in the LangChain node to better suit your tone.

  Set your preferred schedule in the Trigger node.

  📋 Airtable Setup
  Create a base (e.g., Content Hub) with a table named Ideas and the following columns:

  | Column Name | Type       | Required | Notes                      |
  |-------------|------------|----------|----------------------------|
  | Type       | Single select | ✅ | Must be set to Youtube Video |
  | Source | URL  | ✅ | The YouTube video URL       |
  | Status      | Checkbox        | ✅ | Leave empty initially; updated after processing   |
  | MainIdea        | Single line text | ✅ | Summary generated by OpenAI
  |
  | Key Takeaways        | Long text | ✅ | List of takeaways extracted from the transcript  


  Activate the workflow—and you're done!

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workflow_json_compressed:
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metadata_json:
  {"categories":["automation","integration","data processing"],"complexity":"medium","use_cases":["Generate structured content ideas from YouTube videos","Automate editorial/content pipeline updates in Airtable","Extract transcripts and summarize videos for repurposing","Produce main idea and key takeaways for content teams"],"estimated_setup_minutes":20,"required_services":["RapidAPI (youtube-video-summarizer-gpt-ai)","OpenAI or Anthropic Claude or Google Gemini (LLM)","Airtable account","n8n (cloud or self-hosted)"],"key_features":["Scans Airtable for new YouTube links on a schedule","Extracts video transcripts via RapidAPI","Summarizes content into main idea and key takeaways using an LLM","Writes insights back to the original Airtable record and marks it complete","Configurable summarization prompt (LangChain node)"],"target_audience":["Content marketers","Social media managers","Content creators and editors\",\"Automation engineers / n8n users"]}


name: Scrape Trustpilot Reviews Using Bright Data & GPT-4o-mini for Winning Ad Copy
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-04-19T15:01:54.627Z
updated_at: 2025-04-19T15:01:54.627Z
url: https://n8n.io/workflows/3610
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-14 21:18:32
description:
  🔍 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

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workflow_json_compressed:
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metadata_json:
  {"categories":["automation","integration","data processing","web scraping","marketing"],"complexity":"medium","use_cases":["Scrape competitor Trustpilot reviews","Extract and summarize negative customer feedback","Generate high-impact Facebook ad copy variations","Automate review collection and reporting","Distribute insights to marketing teams via email"],"estimated_setup_minutes":30,"required_services":["Bright Data (Dataset API)","Google Sheets (OAuth2)","OpenAI (GPT-4o-mini API key)","Email service/SMTP or n8n Communication node","n8n instance/workflow runner"],"key_features":["Automated Trustpilot scraping with Bright Data and polling for snapshots","Stores raw reviews in structured Google Sheet","Filters to 1–2 star reviews and aggregates common complaints","Summarizes pain points and feeds to GPT-4o-mini","Generates 3 ad copy variations targeting pain points (customizable prompts)」「Sends ad copy and summary via email to the marketing team」「Manual form trigger for inputting competitor URL and timeframe"],"target_audience":["Marketers","Business owners","Marketing agencies/consultants growth teams and copywriters"]}


name: Telegram giveaways among channel subscribers (Module "Giveaway")
author_name: Andrew
author_username: boanse
categories: []
created_at: 2025-04-19T16:04:43.183Z
updated_at: 2025-04-19T16:04:43.183Z
url: https://n8n.io/workflows/3611
scraped_at: 2025-09-14 19:11:03
metadata_generated_at: 2025-09-14 21:18:33
description:
  Who is this for?
  This workflow is ideal for businesses or individuals who want to run Telegram-based giveaways that require users to subscribe to certain channels in order to participate.

  What problem is this workflow solving?
  Running a fair and trackable giveaway on Telegram can be difficult without a system that verifies subscriptions and manages participants. This workflow simplifies that process, ensuring only eligible users are included and enabling a smooth drawing process.

  What this workflow does
  The giveaway organizer specifies a list of Telegram channels for participants to must subscribe to.
  The organizer shares a bot link with users.
  Users start the bot, confirming their participation in the giveaway.
  The bot tracks eligible participants.
  The administrator complete the giveaway and select winners.

  Setup
  Create tables in your Postgres database  
     Open the provided SQL script.
     Replace "n8n" with your schema name.
     Execute the script in your Postgres DB.

  Add credentials in n8n  
     Telegram credentials (Bot token, etc.)  
     Postgres database credentials

  How to customize this workflow to your needs
  Modify the SQL script to match your database schema if needed.
  Customize the Telegram bot messages and logic using the n8n Telegram nodes.
  Add additional nodes if you want to notify winners or log data in other services.

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.set","n8n-nodes-base.telegram","n8n-nodes-base.telegram","n8n-nodes-base.postgres","n8n-nodes-base.postgres","n8n-nodes-base.postgres","n8n-nodes-base.if","n8n-nodes-base.if","n8n-nodes-base.if","n8n-nodes-base.switch","n8n-nodes-base.switch","n8n-nodes-base.telegram","n8n-nodes-base.postgres","n8n-nodes-base.switch","n8n-nodes-base.telegram","n8n-nodes-base.telegram","n8n-nodes-base.telegram","n8n-nodes-base.switch","n8n-nodes-base.postgres","n8n-nodes-base.sort","n8n-nodes-base.postgres","n8n-nodes-base.aggregate","n8n-nodes-base.if","n8n-nodes-base.telegram","n8n-nodes-base.telegram","n8n-nodes-base.telegram","n8n-nodes-base.telegram","n8n-nodes-base.postgres","n8n-nodes-base.postgres","n8n-nodes-base.telegram","n8n-nodes-base.postgres","n8n-nodes-base.postgres","n8n-nodes-base.postgres","n8n-nodes-base.postgres","n8n-nodes-base.telegram","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.set","n8n-nodes-base.telegramTrigger","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  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

metadata_json:
  {"categories":["automation","marketing","social media","community management","giveaways"],"complexity":"medium","use_cases":["Running Telegram channel subscription-based giveaways","Verifying participant eligibility via channel subscriptions","Managing and tracking giveaway participants","Random winner selection and announcement","Automating contest workflows for growth/engagement"],"estimated_setup_minutes":45,"required_services":["Telegram Bot API (bot token)","PostgreSQL database","n8n instance"],"key_features":["Verifies subscriber eligibility across specified Telegram channels","Tracks and stores eligible participants in Postgres","Admin-triggered winner selection/drawing","Customizable Telegram bot messages and participant flow","Support for logging and further integrations via additional nodes"],"target_audience":["Marketers","Community managers","Small businesses and creators running promotions on Telegram」「Developers / automation engineers implementing contest logic"]}


name: Automate Testing and Collect Responses via Telegram in Postgres (Module "Quiz")
author_name: Andrew
author_username: boanse
categories: []
created_at: 2025-04-19T16:48:32.300Z
updated_at: 2025-04-19T16:48:32.300Z
url: https://n8n.io/workflows/3612
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-14 21:18:33
description:
  Who is this for?  
  This template is ideal for educators, HR professionals, and anyone looking to automate testing and collect responses through Telegram, while storing results in a Postgres database.

  What problem is this workflow solving?  
  Manually organizing and managing tests can be time-consuming and prone to error. This workflow automates the test distribution, response collection, and scoring process, ensuring a seamless and efficient testing experience.

  What this workflow does  
  Adds test content, including questions and answers, to a Postgres database  
  Sends a Telegram bot link to test participants  
  Automatically delivers the test via the Telegram bot  
  Collects and stores responses  
  Displays the participant's ranking at the end of the test  

  Setup  
  Create tables in Postgres  
     Replace "n8n" in the provided SQL script with the name of your actual schema  
     Run the script in your database to create the required tables  

  Add credentials  
     Set up and connect your Telegram credentials  
     Set up and connect your Postgres credentials  

  How to customize this workflow to your needs  
  Modify the test content directly in the Postgres database  
  Customize the Telegram bot messages to match your tone and branding.
  Adjust scoring logic if needed to reflect different evaluation methods.

nodes_used:
  ["n8n-nodes-base.switch","n8n-nodes-base.telegram","n8n-nodes-base.sort","n8n-nodes-base.wait","n8n-nodes-base.set","n8n-nodes-base.merge","n8n-nodes-base.telegram","n8n-nodes-base.switch","n8n-nodes-base.switch","n8n-nodes-base.switch","n8n-nodes-base.telegram","n8n-nodes-base.telegram","n8n-nodes-base.postgres","n8n-nodes-base.telegramTrigger","n8n-nodes-base.set","n8n-nodes-base.if","n8n-nodes-base.telegram","n8n-nodes-base.code","n8n-nodes-base.postgres","n8n-nodes-base.postgres","n8n-nodes-base.postgres","n8n-nodes-base.postgres","n8n-nodes-base.set","n8n-nodes-base.summarize","n8n-nodes-base.postgres","n8n-nodes-base.telegram","n8n-nodes-base.postgres","n8n-nodes-base.postgres","n8n-nodes-base.stickyNote","n8n-nodes-base.set","n8n-nodes-base.if","n8n-nodes-base.telegram","n8n-nodes-base.telegram","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  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

metadata_json:
  {"categories":["automation","integration","education","data processing","assessment"],"complexity":"complex","use_cases":["Automated student quizzes and classroom assessments","Employee screening and HR testing","Certification or training exams with automated scoring","Collecting quiz/survey responses via chat","Real-time ranking/leaderboard for participants"],"estimated_setup_minutes":30,"required_services":["Telegram Bot API","PostgreSQL","n8n (self-hosted or cloud)","Optional: AI/ML service (if using the AI/ML node)"],"key_features":["Store tests (questions/answers) in Postgres","Send Telegram bot link and deliver tests via bot","Collect and persist participant responses","Automated scoring and ranking/leaderboard display","Customizable messaging and scoring logic via DB and nodes"],"target_audience":["Educators","HR professionals and recruiters","Training managers and instructional designers\",\"n8n automation builders and integrators\",\"Developers / IT administrators"]}


name: Automate Telegram Channel Posts Using Postgres (Module "Cross-Posting")
author_name: Andrew
author_username: boanse
categories: []
created_at: 2025-04-19T17:41:14.399Z
updated_at: 2025-04-19T17:41:14.399Z
url: https://n8n.io/workflows/3614
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-14 21:18:33
description:
  Who is this for?
  This template is ideal for users managing Telegram channels who want to automate the process of posting messages, including text and images, directly from an bot.

  What problem is this workflow solving?
  Manually posting content to multiple Telegram channels can be time-consuming and inconsistent. This workflow automates that process, enabling efficient and consistent content delivery to one or more channels.

  What this workflow does
  This workflow connects to a Postgres database to retrieve post content and automatically sends text or image posts to designated Telegram channels where the bot is an admin. It supports scheduling and content customization through the database.

  Setup
  1. Create the necessary tables in your Postgres database
  Open the SQL script provided in the workflow.
  Replace "n8n" with your actual schema name.
  Run the script in your database to set up the required tables.

  2. Add credentials
  Telegram**: Create and connect a bot, ensuring it has admin access to the target channels.
  Postgres**: Connect your Postgres instance using valid credentials.

  How to customize this workflow to your needs
  Modify the SQL script to match your specific table or schema naming conventions.
  Adjust the content format or post frequency directly from your database.

nodes_used:
  ["n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.telegramTrigger","n8n-nodes-base.postgres","n8n-nodes-base.if","n8n-nodes-base.postgres","n8n-nodes-base.postgres","n8n-nodes-base.switch","n8n-nodes-base.switch","n8n-nodes-base.telegram","n8n-nodes-base.telegram","n8n-nodes-base.telegram","n8n-nodes-base.telegram","n8n-nodes-base.telegram","n8n-nodes-base.telegram","n8n-nodes-base.postgres","n8n-nodes-base.postgres","n8n-nodes-base.summarize","n8n-nodes-base.telegram","n8n-nodes-base.switch","n8n-nodes-base.postgres","n8n-nodes-base.if","n8n-nodes-base.postgres","n8n-nodes-base.switch","n8n-nodes-base.postgres","n8n-nodes-base.postgres","n8n-nodes-base.telegram","n8n-nodes-base.postgres","n8n-nodes-base.telegram","n8n-nodes-base.postgres","n8n-nodes-base.telegram","n8n-nodes-base.telegram","n8n-nodes-base.postgres","n8n-nodes-base.postgres","n8n-nodes-base.postgres","n8n-nodes-base.telegram","n8n-nodes-base.telegram","n8n-nodes-base.postgres","n8n-nodes-base.if","n8n-nodes-base.telegram","n8n-nodes-base.telegram","n8n-nodes-base.telegram","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.postgres"]

workflow_json_compressed:
  [encoded data, 4260 characters]

metadata_json:
  {"categories":["automation","integration","social media","content management"],"complexity":"medium","use_cases":["Automated posting to Telegram channels from a database","Cross-posting same content to multiple channels","Scheduling and publishing text and image posts","Maintaining consistent content delivery via DB-driven workflow"],"estimated_setup_minutes":30,"required_services":["Telegram Bot API (bot with admin rights on target channels)","Postgres database (with schema/tables for posts)","n8n instance (for scheduling/execution)"],"key_features":["Reads post content and metadata from Postgres","Sends text and image messages to one or more Telegram channels","Supports scheduling and frequency controls via database","Content customization via SQL/schema adjustments","Branching logic for different post types (text vs image)"],"target_audience":["Social media managers","Community managers","Developers/automation engineers implementing integrations for teams"]}


name: Verify Telegram Channel Subscriptions with Access Control using Postgres
author_name: Andrew
author_username: boanse
categories: []
created_at: 2025-04-19T18:20:13.113Z
updated_at: 2025-04-19T18:20:13.113Z
url: https://n8n.io/workflows/3615
scraped_at: 2025-09-14 19:11:03
metadata_generated_at: 2025-09-14 21:18:33
description:
  Who is this for?  
  This workflow is for Telegram bot developers or marketers who want to verify user subscriptions to specific Telegram channels and optionally reward them with downloadable files.

  What problem is this workflow solving?  
  This workflow ensures users have subscribed to required Telegram channels before they are granted access to resources or rewards, such as Google Drive files. It automates the subscription verification process, saving time and reducing manual effort.

  What this workflow does  
  Verifies if a user is subscribed to specific Telegram channels.  
  Allows adding and removing channel IDs for verification.  
  Sends referral links to users for subscription checks.  
  Optionally grants access to Google Drive files upon successful verification (currently inactive)
  Setup  
  Add the bot to your Telegram channels as an admin – this is required for the bot to check subscription status.  
  Add channel IDs via the bot – these are the channels users will need to subscribe to.  
  Send the referral link to users you want to verify.  
  Remove channels anytime from the subscription check list if needed.  
  Create tables in Postgres:  
     Replace "n8n" in the provided SQL script with your DB schema name.  
     Run the script in your Postgres DB.  
  Add credentials:  
     Telegram  
     Postgres  

  How to customize this workflow to your needs  
  Modify the SQL script to suit your existing database structure.  
  Adjust the logic to enable or disable file delivery from Google Drive.  

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.telegram","n8n-nodes-base.postgres","n8n-nodes-base.aggregate","n8n-nodes-base.if","n8n-nodes-base.telegram","n8n-nodes-base.googleDrive","n8n-nodes-base.googleDrive","n8n-nodes-base.postgres","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.telegramTrigger","n8n-nodes-base.postgres","n8n-nodes-base.switch","n8n-nodes-base.switch","n8n-nodes-base.telegram","n8n-nodes-base.postgres","n8n-nodes-base.telegram","n8n-nodes-base.postgres","n8n-nodes-base.telegram","n8n-nodes-base.telegram","n8n-nodes-base.telegram","n8n-nodes-base.telegram","n8n-nodes-base.postgres","n8n-nodes-base.postgres","n8n-nodes-base.summarize","n8n-nodes-base.telegram","n8n-nodes-base.switch","n8n-nodes-base.postgres","n8n-nodes-base.switch","n8n-nodes-base.telegram","n8n-nodes-base.postgres","n8n-nodes-base.if","n8n-nodes-base.telegram","n8n-nodes-base.telegram","n8n-nodes-base.postgres","n8n-nodes-base.if","n8n-nodes-base.postgres","n8n-nodes-base.postgres","n8n-nodes-base.telegram","n8n-nodes-base.telegram","n8n-nodes-base.if","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 4196 characters]

metadata_json:
  {"categories":["automation","integration","messaging/chatbot","access control","database"],"complexity":"complex","use_cases":["Gate access to downloads or resources based on Telegram channel subscriptions","Automate verification of Telegram channel membership","Manage channel lists and referral links for subscription checks","Reward or onboard users after verifying subscriptions"],"estimated_setup_minutes":45,"required_services":["Telegram Bot API (bot added as channel admin)","Postgres database","n8n","Google Drive (optional, for delivering files)"],"key_features":["Checks if a user is subscribed to one or more Telegram channels","Add/remove channel IDs stored in Postgres","Send referral links and perform subscription checks via bot","Optional delivery of Google Drive files upon successful verification","Postgres-backed persistence and configurable SQL schema"],"target_audience":["Telegram bot developers","Marketers and community managers","Growth hackers running referral or gated-content flows using n8n"]}


name: Automated Lead Generation & Contact Enrichment with Hunter.io and Perplexity AI
author_name: Velebit from Innovatio
author_username: innovatio
categories: []
created_at: 2025-04-19T18:41:48.286Z
updated_at: 2025-04-19T18:41:48.286Z
url: https://n8n.io/workflows/3616
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:32
description:
  Who is this for?

  This template is ideal for B2B founders, solopreneurs, growth marketers, SDRs, or anyone looking to scale their lead generation and enrichment with no-code tools to low-code tools.

  Whether you're building your first lead pipeline or upgrading a manual spreadsheet, LeadAIgen automates the entire discovery → enrichment → logging process using AI and verified email data.

  What problem does this solve?

  Lead sourcing and enrichment are time-consuming, inconsistent, and often require multiple tools or manual scraping.

  This workflow solves that by chaining AI + contact discovery, validating everything, and storing clean, structured data in Google Sheets — ready for outreach or CRM sync.

  What this workflow does:

  ✅ Accepts an industry/topic prompt via chat trigger or Telegram,  
  🤖 Uses OpenRouter (Perplexity) to find 15 relevant companies with domains,  
  📤 Parses the results, filters duplicates based on your Google Sheet,  
  📩 Enriches each domain with up to 3 real personal emails using Hunter.io,  
  💡 If no emails found → Fallback AI tries to locate general email info,  
  📊 Updates your Google Sheet with all valid enriched leads (status: “Enriched”),  
  🔁 Runs in safe batches of 10 to protect your API limits,  
  🛠️ Includes logic to clean data, validate JSON, and slice leads.

  Setup:

  Create Google Sheets, Hunter.io, and OpenRouter credentials in your n8n instance  
  Import the JSON workflow  
  Set your OpenRouter model (default = Perplexity Sonar Large)  
  Connect your Google Sheet (must contain a header row with Domain, Status, etc.)  
  Paste your Hunter API key into the Hunter.io node  
  (Optional) Add Telegram Bot trigger to chat with your lead generator  

  🗒 Color-coded workflow notes:

  To make customization easier, this template includes Innovatio's signature visual sticky note system inside the n8n canvas.

  You’ll find:

  🟩 Green Notes → Main Steps  
  The core logic blocks — from company generation to AI fallback and Google Sheets update.

  🟦 Blue Notes → Personalization Tips  
  How to adapt filters, prompts, and data mappings for your business needs.

  🟨 Yellow Notes → Optional / Advanced  
  Expand with Telegram chat triggers, Airtable integration, CRM push, or lead scoring logic.

  🟫 Gray Notes → Welcome, Outro & Upgrade Suggestions  
  Clear guidance and CTAs if you want help scaling this further.

  👉 Each node includes comments or setup notes so you can learn the system as you use it.

  How to customize this workflow?

  🎯 Swap Google Sheets for Airtable for relational views and tagging,  
  🤖 Replace Perplexity with GPT-4, Claude, or Mixtral inside OpenRouter,  
  📬 Auto-send enriched leads to Gmail, Slack, or your CRM,  
  🗣️ Connect this to Telegram for on-the-go company generation,  
  🔁 Want dynamic lead scoring or auto-categorization? We can help — velebit@innovatio.design

  Final notes

  This template was designed by Velebit from Innovatio.  
  External links (e.g. documentation or support email) lead only to official sources with no affiliate tracking or paid placements.

  A separate license applies to the paid version on Gumroad, which includes commercial use rights, extended fallback logic, and advanced upgrade tips.

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.googleSheets","n8n-nodes-base.if","@n8n/n8n-nodes-langchain.lmChatOpenRouter","@n8n/n8n-nodes-langchain.chainLlm","n8n-nodes-base.code","n8n-nodes-base.googleSheets","n8n-nodes-base.if","n8n-nodes-base.googleSheets","@n8n/n8n-nodes-langchain.chatTrigger","@n8n/n8n-nodes-langchain.lmChatOpenRouter","@n8n/n8n-nodes-langchain.chainLlm","n8n-nodes-base.merge","n8n-nodes-base.googleSheets","n8n-nodes-base.if","n8n-nodes-base.code","n8n-nodes-base.hunter","n8n-nodes-base.code","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.telegramTrigger","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.code","n8n-nodes-base.googleSheets","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.airtable","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.googleSheets","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.scheduleTrigger"]

workflow_json_compressed:
  [encoded data, 4248 characters]

metadata_json:
  {"categories":["automation","integration","lead generation","data enrichment","sales enablement"],"complexity":"complex","use_cases":["B2B lead discovery and enrichment","Building/automating prospect lists for outreach","Populating and maintaining CRM or Google Sheets with validated contacts","Batch-validated email discovery and fallback AI lookups","No-code/low-code lead pipeline creation for growth teams"],"estimated_setup_minutes":30,"required_services":["n8n instance","Google Sheets","Hunter.io API key","OpenRouter (Perplexity Sonar Large recommended)","Telegram Bot (optional for chat trigger)","Gmail/Slack/CRM (optional for downstream delivery)","Airtable (optional alternative to Google Sheets)"],"key_features":["Accepts industry/topic prompts via chat or Telegram trigger","Uses OpenRouter/Perplexity to source relevant companies/domains","Parses and deduplicates results against existing Google Sheet","Enriches domains with up to 3 personal emails via Hunter.io","AI fallback when no emails are found to locate general contact info or suggestions"],"target_audience":["B2B founders","Solopreneurs","Growth marketers and SDRs"]}


name: Generate Monthly Financial Reports with Gemini AI, SQL, and Outlook
author_name: Amjid Ali
author_username: amjid
categories: []
created_at: 2025-04-19T20:25:03.594Z
updated_at: 2025-04-19T20:25:03.594Z
url: https://n8n.io/workflows/3617
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:31
description:
  🚀 AI-Powered Business Performance Reporting Automation

  Unlock executive-level insights with ZERO manual work!  
  This n8n template empowers you to automate your entire monthly business performance reporting using dynamic SQL queries, AI-driven analysis, and beautiful HTML dashboards — all delivered directly to your inbox.

  🎯 What This Automation Does

  📆 Triggers automatically every month (5th of each month)
  🧮 Fetches financial data from SQL (ERPNext or any database)
  🔁 Loops over cost centers to analyze each business unit individually
  📊 Generates Profit & Loss reports, WIP, Employee stats, and vertical breakdowns
  🤖 Uses Google Gemini 2.5 AI to perform advanced financial analysis
  💌 Delivers a polished HTML report to your email inbox
  🔧 Fully modular – replace data source with Excel, Google Sheets, or APIs

  🧑‍🏫 Step-by-Step Video Tutorial

  🎥 Watch the full tutorial on YouTube:  
    
  📌 Learn how each node works and see the AI-generated report in action.

  🌐 Useful Links

  🔗 Sign up for n8n Cloud (recommended for non-tech users):  
    👉 https://n8n.syncbricks.com

  📘 Download the step-by-step Guidebook (Free):  
    👉 https://lms.syncbricks.com/books/n8n

  📚 Explore the full course on n8n (includes templates, workflows, and AI integrations):  
    👉 https://lms.syncbricks.com/courses/n8n

  🛠 Requirements

  ✅ n8n (Self-hosted or Cloud)
  ✅ SQL Database (MySQL / PostgreSQL / ERPNext)
  ✅ Microsoft Outlook or Gmail (to send the report)
  ✅ Gemini API Key (for AI analysis)
  ✅ Basic understanding of your data schema

  💡 Why Use This Template?

  ⏱ Saves 2-3 days of manual work every month
  📈 Improves financial visibility across business units
  🤝 Great for CFOs, COOs, Finance Analysts, and BI teams
  🔄 Scales across multiple divisions and companies
  🧠 Leverages AI for actionable insights and recommendations

  🧩 Customize It Your Way

  Replace the SQL nodes with:
    Excel / Google Sheets
    Airtable / APIs
    Custom Applications

  Swap the AI model:
    OpenAI GPT
    Claude
    DeepSeek

  Adjust the report structure or HTML style

  🙌 Get Started Now

  🎯 Import the JSON template → Connect your data → Receive business insights via email.  
  Don’t let manual reporting slow down your decision-making.

  👉 Sign up for n8n Cloud  
  👉 Learn n8n with Amjid  
  👉 Download Guide

  Created by Amjid Ali | SyncBricks™ – Automation for Everyone

nodes_used:
  ["n8n-nodes-base.scheduleTrigger","n8n-nodes-base.mySql","n8n-nodes-base.splitInBatches","n8n-nodes-base.set","n8n-nodes-base.dateTime","n8n-nodes-base.code","n8n-nodes-base.set","n8n-nodes-base.mySql","n8n-nodes-base.filter","n8n-nodes-base.html","n8n-nodes-base.code","n8n-nodes-base.merge","n8n-nodes-base.code","n8n-nodes-base.microsoftOutlook","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.mySql","n8n-nodes-base.code","n8n-nodes-base.wait","n8n-nodes-base.code","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.toolCalculator","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.toolThink","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","n8n-nodes-base.mySql","n8n-nodes-base.mySql","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
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metadata_json:
  {"categories":["automation","reporting","data processing","AI integration","finance"],"complexity":"complex","use_cases":["Monthly financial reporting automation","Automated Profit & Loss and WIP generation","Multi–cost-center / multi–business-unit analysis","AI-driven financial insights and recommendations","Delivering polished HTML reports via email"],"estimated_setup_minutes":90,"required_services":["n8n (self-hosted or Cloud)","SQL database (MySQL / PostgreSQL / ERPNext)","Google Gemini API key","Email service (Microsoft Outlook / Gmail SMTP)"],"key_features":["Monthly scheduled trigger","Dynamic SQL queries and data fetching","Looping over cost centers for per-unit analysis","Generates P&L, WIP, employee stats, and vertical breakdowns","Google Gemini 2.5 AI-driven financial analysis and insights\n(plug-and-play for other LLMs like OpenAI/Claude/DeepSeek)"],"target_audience":["CFOs","COOs","Finance analysts / BI teams"]}


name: Auto Invoice & Receipt OCR to Google Sheets – Drive, Gmail, & Telegram Triggers
author_name: Daniel Ng
author_username: danielng
categories: []
created_at: 2025-04-19T23:34:02.191Z
updated_at: 2025-04-19T23:34:02.191Z
url: https://n8n.io/workflows/3618
scraped_at: 2025-09-14 19:11:00
metadata_generated_at: 2025-09-14 21:18:32
description:
  The Best Invoice & Receipt OCR Automation - FREE (for a limited time)

  Automatically process invoices and receipts using Gemini OCR, extracting data directly into Google Sheets from multiple sources including Google Drive, Gmail, and Telegram. This powerful workflow ensures your bookkeeping is always accurate, organized, and efficient, significantly reducing manual effort and potential errors.

  Who is this for?

  This workflow is ideal for busy entrepreneurs, startup founders, freelancers, small business owners, bookkeepers, and accountants who aim to eliminate manual, repetitive, and error-prone bookkeeping tasks. Whether you regularly manage expenses from physical paper receipts, digital invoices, or email attachments, this workflow will dramatically streamline your bookkeeping processes and save you significant time and effort each month.

  What problem is this workflow solving?

  Manual data entry of invoices and receipts is notoriously tedious, incredibly time-consuming, and highly susceptible to human error. Mistakes in bookkeeping can lead to financial inaccuracies, compliance issues, and wasted resources. By automating the extraction of invoice data, this workflow streamlines your financial management process, significantly improves accuracy, reduces operational overhead, and allows you to redirect valuable resources and attention toward strategic, revenue-generating business activities.

  What this workflow does

  This template provides a powerful, automated solution for invoice and receipt data extraction using Google's Gemini API for OCR (Optical Character Recognition) via direct HTTP requests.

  Main Flow (Google Drive Trigger): The main workflow triggers (Google Drive Trigger New Files) whenever a new file (PDF or image) is added to a designated Google Drive folder. It uses a SplitInBatches node (Loop Over Items) to process incoming files one by one. For each file, it:  
     Downloads the file (Google Drive Get Receipt).  
     Converts it to base64 (Move file to base64 string).  
     Sends the file data and a detailed prompt to the Gemini API (gemini-2.0-flash model specified in the Prompt node, sent via the Gemini API HTTP Request node). The prompt requests structured JSON output with specific fields and formatting (like comma decimal separators, no currency symbols, and a dedicated currency field).  
     Parses the JSON response (JSON to string, Parse string nodes).  
     Appends the extracted data (Invoice Date, Category, Sender, Currency, etc.), along with the original filename and a link to the file, to a specified Google Sheet (Add to Google Sheets).  
     Includes Wait nodes to help manage potential rate limits.  
  Supplementary flow 1 (Gmail Trigger): An additional trigger (Gmail Trigger) monitors your Gmail account for emails with a specific label. When a matching email with attachments arrives:  
     It loops through emails and attachments.  
     It renames the attachment using the format YYYY-MM-DD_SenderUsername (e.g., 2025-04-19_some.sender) using the Create File Name node.  
     It saves the renamed attachment to the designated Google Drive folder (Google Drive Save Files), which then triggers the core OCR process above.  
  Supplementary Trigger 2 (Telegram Trigger): Another optional trigger (Telegram Trigger Image) allows you to forward photos of physical receipts to your configured Telegram bot:  
     It renames the image file using the format YYYY-MM-DD_Telegram (e.g., 2025-04-19_Telegram) via the Create File Name For Telegram node.  
     It saves the renamed image to the designated Google Drive folder (Google Save Files 2), also triggering the core OCR process.

  Setup

  Credentials: Add the following credentials in n8n, using the names specified in the template or your own:  
     Google OAuth2: For Google Drive, Google Sheets, Gmail.  
     Telegram: For the Telegram bot trigger  
     Gemini API Key: Obtain a free API key from Google AI Studio. You will need to paste this key directly into the Query Parameters of the Gemini API (HTTP Request) node in the workflow.  
  Google Drive: Create a specific folder in your Google Drive where all invoices/receipts will be stored and processed from. Update the target Folder in the Google Drive Trigger New Files, Google Drive Save Files, and Google Save Files 2 nodes to use your designated folder.  
  Google Sheets: Create a new Google Sheet, or clone this Sheet template. Ensure it has columns matching the desired output fields (see default list below, including Currency). Update the target Spreadsheet and Sheet Name in the Add to Google Sheets node to point to your sheet.  
  Gmail (Optional): Create a label in Gmail (e.g., "receipts"). Update the Label filter in the Gmail Trigger node to use the label you created. Consider setting up filters in Gmail to automatically apply this label to relevant emails.  
  Telegram (Optional): Configure the Telegram Trigger Image node with your bot credentials.  
  Gemini API Node: Open the Gemini API (HTTP Request) node. In the "Query Parameters" section, replace the placeholder API key with your actual Gemini API Key. Verify the URL uses the correct model name by referencing the Prompt node's model value (gemini-2.0-flash by default).  
  Customize Prompt: Open the Prompt (Set) node.  
     Crucially, change the first line "My company is Sisu Digital..." to reflect your company or remove it if not needed.  
     Review the list of categories and the specific formatting instructions (e.g., comma for decimals, no currency symbols, date format, "N/A" for notes) to ensure they match your requirements. You can adjust these details here.  
  Activate Workflow: Test each trigger path (Drive upload, labeled Gmail, Telegram photo) with sample files/emails/messages, then activate the workflow.

  How to customize this workflow to your needs

  Gemini Prompt/Model:* Modify the prompt text, the list of categories, or the detailed formatting instructions within the *Prompt (Set) node. You can also change the model value in the Prompt node to use a different Gemini model (ensure the model supports the API endpoint used in the HTTP Request node).  
  Extracted Fields:* Modify the prompt in the *Prompt node to extract different fields or change formatting. Update the parsing logic in the Parse string node if needed, and ensure your Google Sheet columns match in the Add to Google Sheets node. The default extracted fields (based on the updated prompt) are:  
    Invoice Date: (DD/MM/YYYY)  
    Category: (From predefined list)  
    Sender: (Issuing company)  
    Description: (Brief details)  
    Amount (0% VAT): (Net amount, comma decimal, no currency symbol)  
    VAT %: (Rate number, comma decimal, no % sign, "0,0" if none)  
    Total: (Gross amount, comma decimal, no currency symbol)  
    Currency: (Uppercase abbreviation, e.g., "EUR", "USD")  
    Note: (Relevant notes, or "N/A")  
    (Added by workflow): File Name, File URL  
  Triggers & Targets:* Enable/disable or modify the *Gmail and Telegram triggers. Select your desired Google Drive folder, Google Sheet, and Gmail label directly within the respective nodes.  
  File Naming:* Adjust the Javascript code in the *Create File Name (for Gmail) or Create File Name For Telegram nodes to change the renaming pattern. Current formats: YYYY-MM-DD_SenderUsername (Gmail), YYYY-MM-DD_Telegram (Telegram).  
  Configuration Method:** Update configuration like folders, sheets, and labels directly within the relevant nodes. For easier management of multiple settings, consider adding a central 'Set' node at the beginning of the workflow to define these values and use expressions to reference them in other nodes.

  Important Considerations

  AI Accuracy:** AI models can make mistakes. Always review the data extracted into Google Sheets for accuracy, especially with specific formatting like decimal separators. This workflow automates heavily but requires final verification.  
  Gemini API Usage:* This template uses the *Gemini API via HTTP Request. Be mindful of Google's API rate limits, usage policies, and potential costs associated with the model used (gemini-2.0-flash by default), especially if you change it. Monitor Google's terms.  
  Loops and Waits:* The workflow uses *SplitInBatches and Wait nodes to process items individually and pause execution, which helps prevent hitting API rate limits but processes files sequentially rather than in parallel.

  Support Disclaimer

  This workflow is provided as-is for your convenience. Use it responsibly, and feel free to build upon it for your unique needs\!  
  This workflow has been thoroughly tested and is confirmed to be working flawlessly at the time of release. However, setup complexity or unexpected errors may occur depending on your environment, customizations, or API changes.  
  Please note that I cannot offer personalized support or troubleshooting for this template (without a fee\!). If you encounter an issue, feel free to send me a message describing the problem. If the issue is determined to be a genuine bug within the shared template, I will do my best to fix it and update the workflow. Otherwise, the issue is likely due to a setup misconfiguration or modification on your side. In those cases, I recommend using ChatGPT or referring to n8n documentation to debug the problem.

nodes_used:
  ["n8n-nodes-base.set","n8n-nodes-base.extractFromFile","n8n-nodes-base.httpRequest","n8n-nodes-base.set","n8n-nodes-base.code","n8n-nodes-base.googleSheets","n8n-nodes-base.googleDrive","n8n-nodes-base.telegramTrigger","n8n-nodes-base.gmailTrigger","n8n-nodes-base.code","n8n-nodes-base.splitInBatches","n8n-nodes-base.if","n8n-nodes-base.splitInBatches","n8n-nodes-base.wait","n8n-nodes-base.splitInBatches","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.googleDriveTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.googleDrive","n8n-nodes-base.googleDrive","n8n-nodes-base.wait","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
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metadata_json:
  {"categories":["automation","integration","data processing","OCR","bookkeeping"],"complexity":"medium","use_cases":["Automated invoice and receipt data extraction","Populate Google Sheets with structured bookkeeping data","Ingest attachments from Google Drive, Gmail, and Telegram","Reduce manual bookkeeping and data-entry errors","Expense tracking and accounting prep"],"estimated_setup_minutes":30,"required_services":["n8n","Google Drive (OAuth2)","Google Sheets (OAuth2)","Gmail (OAuth2) - optional","Telegram Bot (optional)","Gemini API / Google AI Studio (HTTP API key)"],"key_features":["Multi-source triggers: Drive, Gmail label, Telegram images","Gemini OCR via HTTP request with custom prompt for structured JSON","SplitInBatches + Wait nodes for rate-limit management","Auto file rename and save to Drive to standardize inputs","Parse OCR JSON and append rows to Google Sheets with file link/name fields included and currency handling format rules"],"target_audience":["Entrepreneurs","Small business owners","Freelancers and contractors`,`Bookkeepers and accountants`,`Operations/finance teams`,`Developers or automation builders integrating OCR into workflows"]}


name: Translate SRT Files with Google Translate
author_name: DanielV
author_username: danielv
categories: []
created_at: 2025-04-20T10:09:18.893Z
updated_at: 2025-04-20T10:09:18.893Z
url: https://n8n.io/workflows/3620
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-14 21:18:32
description:
  This workflow is designed to translate SRT subtitle files from one language to another using Google Translate.

  The workflow follows these main steps:

  Accept an SRT file upload and target language selection
  Extract and parse the SRT file content
  Split the content into translatable segments
  Translate each segment using Google Translate
  Reassemble the translated content into a proper SRT format
  Return the translated file to the user

  You'll need a Google Console Cloud account to access the Translate API.

  Who is this for?

  This workflow is designed for content creators, video editors, translators, and anyone who needs to translate subtitle files (.srt) from one language to another. It's particularly useful for those working with international content, educational materials, or preparing videos for global audiences.

  What problem does this workflow solve?

  Translating subtitle files manually is time-consuming and error-prone. Professional translation services can be expensive, especially for multiple videos or long content. This workflow automates the translation process while maintaining the proper SRT format including timestamps and subtitle numbering.

  Setup

  Set up Google Translate credentials:
  -- Create a Google Cloud project and enable the Google Translate API
  -- Create OAuth credentials and configure them in the Google Translate node
  Customize language options:
  -- The default workflow includes English (EN) and Japanese (JP) options
  -- Add more language options by editing the dropdown field in the "Receive SRT File to Translate" node
  -- Use standard language codes that Google Translate supports
  Add more languages:
  -- Edit the form trigger node to include additional language options in the dropdown

nodes_used:
  ["n8n-nodes-base.splitOut","n8n-nodes-base.googleTranslate","n8n-nodes-base.aggregate","n8n-nodes-base.set","n8n-nodes-base.convertToFile","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.form","n8n-nodes-base.formTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.extractFromFile","n8n-nodes-base.code"]

workflow_json_compressed:
  [encoded data, 4936 characters]

metadata_json:
  {"categories":["automation","integration","localization","data processing"],"complexity":"medium","use_cases":["Translate SRT subtitle files between languages","Localize video content for international audiences","Bulk or automated subtitle translation for courses/tutorials","Quick subtitle translation for editors and creators"],"estimated_setup_minutes":30,"required_services":["Google Cloud Translate API (Google Cloud Console account with credentials)"],"key_features":["Accept SRT file upload and target language selection","Parse SRT and split text into translatable segments","Translate each segment via Google Translate API","Reassemble translated segments into valid SRT (timestamps and numbering preserved)","Return translated .srt file to user"],"target_audience":["Content creators","Video editors","Translators and localization teams','Educators and course creators"]}


name: Send Hourly Crypto Market Analysis from Binance to Telegram
author_name: Aurélien P.
author_username: aurelienpp
categories: []
created_at: 2025-04-20T14:40:50.131Z
updated_at: 2025-04-20T14:40:50.131Z
url: https://n8n.io/workflows/3621
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:32
description:
  📈 Daily Crypto Market Summary Bot (Binance to Telegram)

  This workflow fetches 24h price change data from Binance for selected crypto pairs (BTC/USDC, ETH/USDC, SOL/USDC) every hour using a cron schedule.  
  It performs in-depth analysis—including volatility, volume, bid-ask spread, momentum, and market comparison—then formats a detailed market summary.  
  The final report is sent to a Telegram chat using HTML formatting, highlighting top gainers, losers, and key metrics in a clean, readable layout.

  🔑 Key Features
  ⏱ Runs every hour (cron: 5 * * * *)
  🔍 Filters and analyzes major coins: BTC, ETH, SOL
  📊 Calculates market metrics:
    Volatility
    Bid-ask spread
    Momentum
    Estimated market cap
    Market average comparison
  📈 Highlights gainers, losers, and top coins by volume
  ✂️ Splits messages to fit Telegram’s 4096 character limit
  💬 Sends output in rich HTML format to a Telegram group or chat

  🎯 Use Cases
  ✅ Crypto traders wanting hourly performance insights
  ✅ Telegram groups needing automated market updates
  ✅ Analysts monitoring key coin metrics in real-time
  ✅ Bot developers creating crypto dashboards or alerts

  🛠 Technical Details
  Data Source:** Binance 24hr ticker API (/api/v3/ticker/24hr)
  Coins Monitored:** BTCUSDC, ETHUSDC, SOLUSDC (can be expanded)
  Metrics Calculated:**
    Price change percentage
    Volatility (high vs low price)
    Bid-ask spread %
    Momentum (vs weighted average)
    Estimated market cap
    Number of trades
    Market average movement
  Message Format:**
    HTML with emojis, bold styling, and section headings
    Auto-split messages when exceeding Telegram's 4096-char limit
  Error Handling:**
    Retry on HTTP failure (up to 5 times with 5s delay)
    Message length checked and split for Telegram compatibility

  ⚙️ Setup Requirements
  Telegram Bot Token — Create a bot via @BotFather on Telegram
  Chat ID — Use a personal ID or group chat ID (add the bot to the group)
  n8n Instance — Either cloud or self-hosted
  (Optional) Modify relevantSymbols in the Function node to track different coins

  🧠 Notes
  This workflow is highly customizable—feel free to modify the analytics, tracked pairs, or formatting.
  Great base for alerting systems or crypto dashboards.

  📷 Example Output (Telegram)
  📊 Crypto Market Summary — 2025-04-20 14:05:05 UTC

  🌐 Market Overview (BTC, ETH, SOL)
  Average Change: -1.54%
  24h Volume: $850,358,765.46
  Most Volatile: SOLUSDC (4.53%)
  Most Liquid: BTCUSDC (0.0000% spread)

  💹 Top by Volume
  ETHUSDC: $403,860,356.75 | -1.640%
  SOLUSDC: $279,241,338.60 | -1.706%
  BTCUSDC: $167,257,070.12 | -1.261%

  📉 Losers

  SOLUSDC
  🔻 Change: -1.71% (24h)
  💰 Current: $137.10
  📊 Range: $135.82 - $141.97
  📈 Volatility: 4.53%
  🔄 Volume: 2.01M | $279,241,338.60
  ⚖️ Bid-Ask Spread: 0.0073%
  ⬇️ vs Market Avg: -0.17%
  🔽 Momentum: -1.42%
  🔢 Trades: 366,119

  ETHUSDC
  🔻 Change: -1.64% (24h)
  💰 Current: $1,577.42
  📊 Range: $1,565.60 - $1,631.98
  📈 Volatility: 4.24%
  🔄 Volume: 252.11K | $403,860,356.75
  ⚖️ Bid-Ask Spread: 0.0044%
  ⬇️ vs Market Avg: -0.10%
  🔽 Momentum: -1.53%
  🔢 Trades: 596,801

  BTCUSDC
  🔻 Change: -1.26% (24h)
  💰 Current: $84,336.65
  📊 Range: $83,963.35 - $85,634.50
  📈 Volatility: 1.99%
  🔄 Volume: 1.97K | $167,257,070.12
  ⚖️ Bid-Ask Spread: 0.0000%
  ⭐ vs Market Avg: 0.27%
  🔽 Momentum: -0.68%
  🔢 Trades: 124,202

nodes_used:
  ["n8n-nodes-base.scheduleTrigger","n8n-nodes-base.httpRequest","n8n-nodes-base.telegram","n8n-nodes-base.function","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 4984 characters]

metadata_json:
  {"categories":["automation","crypto","monitoring","messaging","data-processing"],"complexity":"medium","use_cases":["Hourly crypto performance notifications","Telegram market summary bots for communities","Real-time monitoring for traders and analysts","Building alerting systems or crypto dashboards"],"estimated_setup_minutes":15,"required_services":["Binance API (24hr ticker)","Telegram Bot API (Bot token & Chat ID)","n8n instance (cloud or self-hosted)"],"key_features":["Cron-driven hourly schedule","Fetches Binance 24h ticker for selected pairs (BTC/USDC, ETH/USDC, SOL/USDC)","Calculates metrics: price change %, volatility, bid-ask spread %, momentum, estimated market cap, trade count","Identifies top gainers/losers and top-by-volume","Formats rich HTML messages with emojis and sections for Telegram groups/chats','Auto-splits messages to respect Telegram 4096-char limit','Retry logic on HTTP failures (up to 5 attempts with delay)','Customizable tracked symbols in function node"],"target_audience":["Crypto traders","Telegram group admins/moderators","Market analysts/data analysts monitoring crypto metrics\",\"Bot developers/integrators"]}


name: AI-Powered Upwork Cover Letter Generator – Pinecone, Groq, Google Gemin, SerpAPI
author_name: Udit Rawat
author_username: ailistmaster
categories: []
created_at: 2025-04-20T15:24:51.535Z
updated_at: 2025-04-20T15:24:51.535Z
url: https://n8n.io/workflows/3622
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-14 21:18:32
description:
  🚀 Automated Upwork Cover Letter Generator with n8n + MacOS Shortcut + Pinecone Context Retrieval

  This n8n automation is designed to streamline the Upwork proposal process by generating highly personalized, context-aware cover letters using your own skills and project data stored in a Pinecone vector store.

  With the help of an AI Agent powered by Groq’s Qwen LLM, and triggered instantly via a MacOS Shortcut, this system takes job descriptions from your clipboard and returns a ready-to-use HTML cover letter—right on your desktop.

  ⚙️ Workflow Breakdown

  🔹 MacOS Shortcut – Trigger the Workflow Instantly
  The process begins with a MacOS Shortcut that captures job description text from your clipboard and sends it to a custom webhook in n8n.

  🔹 Webhook Node – Receive and Process Input
  The webhook node receives the clipboard data, along with the required credentials for authentication. This node serves as the entry point to the full automation.

  🔹 Field Mapping & Pre-Processing
  A series of basic logic nodes map and clean up the input fields. These are then passed to an LLM Chain to generate specific questions related to the job description.

  🔹 Question Answer Chain + Vector Search (Pinecone)
  Using your previously stored skills and project data in a Pinecone vector store, the system retrieves relevant information to answer the generated questions and builds a rich context around the job description.

  🔹 AI Agent Node – Generate Personalized Cover Letter
  With both the job post and contextual data, the AI Agent (powered by Groq’s Qwen LLM) creates a tailored cover letter.  
  The agent is equipped with:

  🔍 Google Search Tool  
  🧠 Vector Store Retriever Tool  
  🗃️ Buffer Memory  

  This ensures the generated proposal is insightful, relevant, and professional.

  🔹 Markdown to HTML – Clean Output Conversion
  The markdown output from the AI is converted into HTML using a Markdown node, making it easy to paste directly into Upwork or emails.

  🔹 Return to Shortcut – Display Final Result
  The final HTML response is sent back to the MacOS Shortcut, which displays it in a modal window for easy review and copy-paste.

  💼 Use Case

  This automation is built specifically for freelancers on Upwork (or any freelance platform) who want to:

  ✅ Save time on repetitive proposal writing  
  ✅ Create job-specific cover letters with context  
  ✅ Stand out with better personalization  
  ✅ Reduce manual effort with automation  

  Whether you’re a beginner or a seasoned pro, this tool elevates your workflow while staying simple to use.

  📦 Setup Instructions

  Import Workflow to your n8n instance  
  Create and Configure MacOS Shortcut (drag-and-drop ready)  
  Prepare and Embed Your Skills/Project Data into Pinecone  
  Add API Credentials:
     Groq (for Qwen LLM)  
     Pinecone  
     n8n Webhook (Basic Auth if needed)  
  Run the Workflow & Submit Smarter Proposals

  &gt; Note: This workflow is designed for building and returning Upwork cover letters using job descriptions copied to your clipboard. All generation is context-aware and tailored per submission.

nodes_used:
  ["@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.vectorStorePinecone","@n8n/n8n-nodes-langchain.embeddingsGoogleGemini","n8n-nodes-base.webhook","@n8n/n8n-nodes-langchain.memoryBufferWindow","@n8n/n8n-nodes-langchain.lmChatGroq","n8n-nodes-base.respondToWebhook","n8n-nodes-base.markdown","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.chainLlm","@n8n/n8n-nodes-langchain.lmChatGroq","@n8n/n8n-nodes-langchain.chainRetrievalQa","@n8n/n8n-nodes-langchain.retrieverVectorStore","@n8n/n8n-nodes-langchain.toolVectorStore","@n8n/n8n-nodes-langchain.toolSerpApi","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
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metadata_json:
  {"categories":["automation","integration","AI/ML","productivity"],"complexity":"complex","use_cases":["Automate and generate personalized Upwork/freelance cover letters","Retrieve contextual skills/projects from a vector store to enrich proposals","Clipboard-to-modal workflow via MacOS Shortcut for instant proposal generation","Convert AI-generated markdown to ready-to-use HTML for Upwork/email"],"estimated_setup_minutes":45,"required_services":["Pinecone (vector store)","Groq Qwen LLM (lmChatGroq)","Google Gemini embeddings (Google embeddings)","SerpAPI (or other web-search API)","n8n instance (webhooks, nodes)","MacOS Shortcuts (local trigger)"],"key_features":["Clipboard-triggered MacOS Shortcut to invoke n8n webhook","Field mapping and pre-processing of job descriptions","LLM question chain to generate clarifying/context questions","Vector search in Pinecone to pull relevant skills/projects","AI Agent with tools: web search, vector retriever, buffer memory for context-aware generation"],"target_audience":["Freelancers and Upwork users","Independent consultants and contractors","Developers/technical users who set up API integrations and automations"]}


name: AI-Powered Gmail MCP Server
author_name: Luciano Gutierrez
author_username: koresoluciones
categories: []
created_at: 2025-04-20T21:13:40.047Z
updated_at: 2025-04-20T21:13:40.047Z
url: https://n8n.io/workflows/3623
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-14 21:18:32
description:
  🤖 AI-Powered Gmail MCP Server for n8n

  Description
  This n8n workflow template leverages an external AI Model Control Plane (MCP) Server to automate various Gmail tasks, such as composing emails, replying to threads, and handling follow-ups using dynamically generated content. It uses the native n8n Gmail nodes available from v1.88.0 onwards.

  Who is this template for?
  Ideal for developers, automation engineers, and power users using self-hosted n8n (v1.88.0+) who want to integrate artificial intelligence directly into their email workflows via a dedicated MCP Server for enhanced control and customization over AI interactions.

  What problem does this workflow solve?
  ⚙️ Reduces Manual Effort: Decreases the work involved in writing, sending, and following up on emails in Gmail.
  ✅ Consistency and Quality: Ensures standardized, professional responses free from typos by leveraging controlled AI prompts.
  🔄 Complete Automation: Automates the entire email cycle: from the initial send, through waiting for a reply, to sending automated follow-ups based on AI logic.

  Workflow Overview
  This template provides a structured approach to integrating Gmail with an MCP Server:

  📡 MCP Trigger (“MCP_GMAIL”): An n8n Webhook node that receives HTTP calls from your MCP Server. It standardizes the inputs (like recipient, subject, AI prompt) for all subsequent Gmail nodes. (You will need to configure your MCP Server to call this webhook URL).
  📤 SEND_EMAIL (Gmail Node v2.1): Sends new messages. The email body (message field) is typically populated by content generated from an AI prompt processed by your MCP server and passed via the trigger.
  🔄 REPLY_EMAIL (Gmail Node v2.1): Automatically replies to existing conversations (threads). It uses AI-generated content (via MCP) to formulate the reply based on the thread context. Requires Message ID and/or Thread ID.
  📥 GET_EMAIL (Gmail Node v2.1): Fetches data for a specific message (using Message ID) for analysis, processing, or archiving. Useful for retrieving context before replying.
  ⏳ SEND_AND_WAIT (Gmail Node v2.1): Sends an email and pauses the workflow execution until a reply is received in that specific conversation (thread). This is crucial for building automated follow-up sequences. It then outputs data from the reply message.

  Note:* All Gmail nodes in this template use the native n8n *Gmail Tool*, integrated since v1.88.0. No additional installation of community nodes is required. See the official n8n documentation for more details on node configuration.

  Prerequisites
  Ensure you have the following before importing:

  🚀 A self-hosted n8n instance running version 1.88.0 or higher.
  ☁️ A Google Cloud project with the Gmail API correctly enabled.
  🔑 Gmail OAuth2 credentials configured in your n8n instance. Navigate to Settings &gt; Credentials &gt; New &gt; Google &gt; Gmail (OAuth2 API) to set this up if you haven't already.
  🧠 Access to your MCP Server and an API Key (or other authentication method) required to interact with it via HTTP requests.

  How to Import and Configure
  Follow these steps to get the template running:

  In your n8n interface, navigate to Templates → Import from URL.
  Paste the JSON link provided for this workflow template.
  Configure the necessary credentials within n8n under Credentials:
      Gmail OAuth2: Select the Google OAuth2 credential you previously configured that has access to the desired Gmail account.
      MCP API Key: You'll likely need to configure credentials for interacting with your MCP Server. This might involve setting up a Header Auth credential in n8n with your MCP API Key, or configuring the HTTP Request node within the workflow directly, depending on your MCP's authentication scheme. Link this credential where needed (e.g., in the Trigger node if MCP calls n8n with auth, or in HTTP Request nodes if n8n calls MCP).
  Activate the Workflow: Ensure the workflow toggle is set to "Active" in the top right corner.
  Webhook URL: Copy the Webhook URL from the "MCP_GMAIL" Trigger node (Test or Production URL as needed) and configure your MCP Server to send requests to this URL.
  Recommendation:
      Rename the nodes with clear, descriptive names relevant to your specific use case (e.g., ✨ Generate Sales Email Body via MCP, 📥 Fetch Customer Replies).
      Utilize the workflow notes (sticky notes on the canvas) to document specific logic, prompt details, or configuration choices for future reference.

  Customization & Technical Guidance
  Tailor the workflow to your specific needs:

  🔍 Search Filters: In nodes that fetch emails (like GET_EMAIL or if you add a Gmail - Get Many node), refine the search using the Search field (standard Gmail search operators) or filter by Label Names to process specific emails (e.g., unread from a specific sender, emails with a certain label).
  ✍️ AI Fine-Tuning (Prompt Engineering): The core of the AI integration happens in the prompts sent to your MCP Server. Modify these prompts (often constructed within function nodes or directly in the trigger input expected from MCP) in the message or body fields passed to the send/reply nodes. Adjust prompts to control:
      Tone & Style: Formal, informal, empathetic, technical, etc.
      Content & Format: Request bullet points, summaries, specific data extraction.
      Dynamic Variables: Inject data from previous n8n nodes (e.g., customer name, order details, previous email content) into the prompt for context-aware generation. Example: `"Reply to the following email thread [{{ $json.thread_content }}] addressing the customer {{ $json.customer_name }} about their query..."`
  🔗 Post-Response Actions: Extend the workflow after key actions, especially the SEND_AND_WAIT node. Add nodes to:
      Log results to a database (MySQL, PostgreSQL, Airtable).
      Update CRM records (HubSpot, Salesforce).
      Send notifications (Slack, Discord, Telegram).
      Trigger other n8n workflows.
  🛡️ Error Handling: Implement robust error handling. Connect the red output pins (error output) of critical nodes (like Gmail nodes or HTTP Requests to MCP) to an Error Trigger node. From there, you can:
      Log detailed error information to a monitoring tool or spreadsheet.
      Send failure notifications.
      Implement retry logic (using loops or specific retry settings on nodes).
      Route to alternative paths or fallback workflows.

nodes_used:
  ["n8n-nodes-base.gmailTool","n8n-nodes-base.gmailTool","n8n-nodes-base.gmailTool","n8n-nodes-base.gmailTool","@n8n/n8n-nodes-langchain.mcpTrigger"]

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metadata_json:
  {"categories":["automation","integration","email","AI"],"complexity":"medium","use_cases":["Automated email composition using AI","AI-driven replies to Gmail threads","Automated follow-ups and wait-for-reply flows","Context-aware personalization using dynamic prompts","Logging or syncing email activity to CRMs/databases"],"estimated_setup_minutes":60,"required_services":["Self-hosted n8n (v1.88.0+)","Google Cloud project with Gmail API enabled","Gmail OAuth2 credentials","External MCP (Model Control Plane) Server with API access"],"key_features":["Webhook trigger to receive standardized inputs from MCP","Send new emails with AI-generated content (Gmail node)","Reply to existing threads using AI-generated replies (Gmail node)","Fetch specific messages for context or archiving (GET_EMAIL)","Send-and-wait flow that pauses until a reply is received for automated follow-ups (SEND_AND_WAIT)"],"target_audience":["Developers","Automation engineers","Power users/self-hosted n8n operators (sales, support, marketing)"]}


name: Scrape Competitor Reviews & Generate Ad Creatives with Bright Data & OpenAI
author_name: Yaron Been
author_username: yaron-nofluff
categories: []
created_at: 2025-04-21T07:44:21.325Z
updated_at: 2025-04-21T07:44:21.325Z
url: https://n8n.io/workflows/3624
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:32
description:
  Scrape Competitor Reviews & Generate Ad Creatives with Bright data and OpenAI

  How the Flow Runs

  Fill the Form
     Enter the Amazon product URL to analyze competitor reviews.

  Trigger Bright Data Scraper
     Bright Data scrapes Amazon reviews based on the provided URL.

  Wait for Snapshot Completion
     Periodically checks Bright Data until the scraping is complete.

  Retrieve JSON Data
     Collects the scraped review data in JSON format.

  Save Reviews to Google Sheets
     Automatically appends the scraped reviews to your Google Sheets.

  Aggregate Reviews
     Consolidates all reviews into a single summary for simpler analysis.

  Analyze Reviews with OpenAI LLM
     Sends the aggregated reviews to OpenAI (GPT-4o mini) to summarize competitors’ main weaknesses clearly.

  Generate Creative Ad Image
     OpenAI generates a visually appealing 1080x1080 ad image addressing these identified pain points.

  Send Ad Creative via Gmail
     Automatically emails the creative and review summary to your media buying team for immediate use in Meta ads.

  What You Need

  Google Sheets:** Template
  Bright Data:** Dataset and API key:
  www.brightdata.com
  OpenAI API Key:** For GPT-4o mini or your preferred LLM
  Automation Tool:** Ensure it supports HTTP Requests, Wait, Conditional (If), Google Sheets integration, Form Trigger, OpenAI integration, and Gmail integration.

  Form Fields to Fill

  Amazon Product URL:** Enter the competitor’s product URL from Amazon.

  Setup Steps

  Copy the provided Google Sheet template.
  Import the JSON workflow into your automation tool.
  Update credentials for Bright Data, Google Sheets, Gmail, and OpenAI.
  Test manually by submitting the form and verifying functionality.
  Optional: Set a schedule for regular workflow execution.

  Bright Data Trigger Example

  [
    {
      "url": "https://www.amazon.com/example-product"
    }
  ]

  Tips
  Frequently update URLs to ensure fresh insights.

  Allow more wait time for extensive data scrapes.

  Focus on targeted products to optimize cost-efficiency.

  Need Help?
  Email: Yaron@nofluff.online

  Resources:

  YouTube:
  https://www.youtube.com/@YaronBeen/videos

  LinkedIn:
  https://www.linkedin.com/in/yaronbeen/

  Bright Data Documentation:
  https://docs.brightdata.com/introduction

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequest","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequest","n8n-nodes-base.wait","n8n-nodes-base.if","n8n-nodes-base.httpRequest","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.stickyNote","n8n-nodes-base.googleSheets","n8n-nodes-base.formTrigger","n8n-nodes-base.aggregate","@n8n/n8n-nodes-langchain.chainLlm","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.gmail"]

workflow_json_compressed:
  [encoded data, 5308 characters]

metadata_json:
  {"categories":["automation","data collection","marketing","web scraping","AI content generation"],"complexity":"medium","use_cases":["Competitor review aggregation and analysis","Generate ad creatives from competitor pain points","Automated reporting to media buying teams","E-commerce product & market research","Creative ideation for Meta ads"],"estimated_setup_minutes":45,"required_services":["Bright Data (dataset + API key)","OpenAI (GPT-4o mini or compatible LLM)","Google Sheets","Gmail","n8n or compatible automation tool with HTTP/Wait/If/Form/OpenAI nodes","Target website (Amazon)"],"key_features":["Scrape Amazon reviews via Bright Data and poll for completion","Retrieve and store review JSON to Google Sheets","Aggregate reviews into a single summary","Analyze aggregated reviews with OpenAI to identify competitor weaknesses","Generate a 1080x1080 ad image via OpenAI addressing pain points`,`Auto-email the ad creative and summary to media buying team via Gmail`,`Form-triggered workflow with optional scheduled runs"],"target_audience":["Growth marketers","Media buyers and ad teams","E‑commerce managers and sellers conducting competitor research`,`Marketing agencies and creative teams`,`Automation engineers or devs implementing workflows"]}


name: General 3D Presentation Workflow with Midjourney, GPT-4o-image and Kling APIs
author_name: PiAPI
author_username: piapi
categories: []
created_at: 2025-04-21T07:49:04.453Z
updated_at: 2025-04-21T07:49:04.453Z
url: https://n8n.io/workflows/3625
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-14 21:18:32
description:
  Who is this template for?
  This workflow creates 360° or 180° spinning videos of high-quality 3D models with PiAPI API. 

  Good for:

  Designers**: Generate inspiration into 3D designs and make them spin to gain concrete details in a efficient way. 
  Online shoppers**: Show protential products from all angles in videos and preview overall texture of models.
  Content Creators** (including toy bloggers): Make fun videos of collectible models. 
  3D beginners:** Get simple spinning animations easily and make fun with them in a convenient way. 

  How to customize this workflow to your need？
  To use this workflow, usually we need four steps:  
  Fill in x-api-key in Mijdourney Generator node and Generate Kling Video node, fill in Header Parameters of GPT-4o Image Generator (e.g., Bearer + your X-API-Key)
  Enter your model prompt based on your inspiration.
  Click Test Workflow.
  Get the video URL in the last node.

  Use Case 
  The prompt node concludes the main features of creations. An example for users' reference is listed as follow: 
  Input Prompt
  A blind box character design, in the chibi style, a super cute little girl wearing a white long-sleeved dress and pearl earrings with her head bowed in a prayer pose, facing upwards, wearing an oversized off-white dress with large round pearls on the shoulders, minimalist simple dress with Ruffles, against a beige background, a full-body shot in a three-quarter profile view, with a black, blue, and gray color scheme, soft lighting, 3D rendering, clay material, high detail, in the Pixar style. Clean white skin, brown renaissance braided bun. --ar 1:1 --niji 6

  Output Video
  An Example for your reference.

  More Example Results for Reference

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.wait","n8n-nodes-base.if","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.if","n8n-nodes-base.if","n8n-nodes-base.wait","n8n-nodes-base.code","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 4480 characters]

metadata_json:
  {"categories":["automation","design","content creation","3D processing","AI-generated media"],"complexity":"medium","use_cases":["Generate 360°/180° spinning videos of 3D models","Quick prototyping of product visuals for e‑commerce","Create engaging social content and toy/collectible showcases","Convert text prompts into 3D-styled renders and animated previews","Automate multi‑API media pipelines (image generation → video creation)"],"estimated_setup_minutes":15,"required_services":["Midjourney Generator API (or equivalent image/3D generator)","GPT-4o Image (OpenAI or compatible)","Kling Video API / PiAPI (video rendering)","HTTP/Webhook accessible endpoint (for n8n)","Optional: cloud storage/CDN for hosting output videos"],"key_features":["Turn text prompts into high-quality 3D-style renders","Create 180° or 360° spinning videos from generated models","Configurable API keys/headers for Midjourney, GPT-4o-image and Kling nodes","Automated end-to-end workflow with webhook trigger and final video URL output","Suitable prompt template included for consistent results"],"target_audience":["Designers and concept artists","E‑commerce/product teams and online shoppers","Content creators and toy bloggers/social creators of visual media"]}


name: Create Animated Illustrations from Text Prompts with Midjourney and Kling API
author_name: PiAPI
author_username: piapi
categories: []
created_at: 2025-04-21T08:38:58.884Z
updated_at: 2025-04-21T08:38:58.884Z
url: https://n8n.io/workflows/3626
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:32
description:
  What does the workflow do?
  This workflow is primarily designed to generate animated illustrations for content creators and social media professionals with Midjourney (unoffcial) and Kling (unofficial) API served by PiAPI. 
  PiAPI is an API platform which provides professional API service. With service provided by PiAPI, users could generate a fantastic animated artwork simply using workflow on n8n without complex settings among various AI models.

  What is animated illustration?
  An animated illustration is a digitally enhanced artwork that combines traditional illustration styles with subtle, purposeful motion to enrich storytelling while preserving its original artistic essence.

  Who is this workflow for?

  Social Media Content Creators: Produces animated illustrations for social media posts.
  Digital Marketers: Generates marketing materials with motion graphics.
  Independent Content Producers: Creates animated content without specialized animation skills.

  Step-by-step Setting Instructions
  To simplify workflow settings, usually users just need to change basic prompt of the image and the motion of the final video following the instrution below:
  Sign in your PiAPI account and get your X-API-Key.
  Fill in your X-API-Key of PiAPI account in Midjourney and Kling nodes.
  Enter your desired image prompt in the Prompt node.
  Enter the motion prompt in Kling Video Generator node.

  For more complex or customization settings, users could also add more nodes to get more output images and generate more videos. Also, they could change the target image to gain a better result. As for recommendation,  users could change the video models for which we would recommend live-wallpaper LoRA of Wanx. Users could check API doc to see more use cases of video models and image models for best practice.

  Use Case
  Input Prompt
  A gentle girl and a fluffy rabbit explore a sunlit forest together, playing by a sparkling stream. Butterflies flutter around them as golden sunlight filters through green leaves. Warm and peaceful atmosphere, 4K nature documentary style. --s 500 --sref 4028286908  --niji 6

  Output Video
  When there is troubleshooting
  Check if the X-API-Key has been filled in nodes needed.
  Check your task status in Task History in PiAPI to get more details about task status. 

  More Generation Case for Reference

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.code","n8n-nodes-base.httpRequest","n8n-nodes-base.if","n8n-nodes-base.wait","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequest","n8n-nodes-base.stickyNote","n8n-nodes-base.wait","n8n-nodes-base.code","n8n-nodes-base.if"]

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metadata_json:
  {"categories":["automation","content creation","media generation","AI/ML","integration"],"complexity":"medium","use_cases":["Generate animated illustrations from text prompts for social media","Create short motion-graphic marketing assets","Rapid prototyping of animated visual content from static prompts","Produce looped or stylized videos (e.g., 4K nature / documentary style)","Batch-generate multiple images and convert to animated videos"],"estimated_setup_minutes":10,"required_services":["n8n instance","PiAPI account (X-API-Key)","Midjourney (unofficial) via PiAPI","Kling video-generation API (unofficial) via PiAPI","Optional: specific image/video model files (e.g., Wanx live-wallpaper LoRA)"],"key_features":["Text-to-image generation via Midjourney (through PiAPI)","Image-to-video animation via Kling video generator","Simple prompt and motion prompt inputs to control output","Supports multiple outputs and further node-driven customization","Task monitoring and troubleshooting via PiAPI Task History info in workflow nodes"],"target_audience":["Social media content creators","Digital marketers","Independent content producers / solo creators"]}


name: Generate Graphic Wallpaper with Midjourney, GPT-4o-mini and Canvas APIs
author_name: PiAPI
author_username: piapi
categories: []
created_at: 2025-04-21T09:05:42.375Z
updated_at: 2025-04-21T09:05:42.375Z
url: https://n8n.io/workflows/3627
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:32
description:
  Who is the template for?
  This workflow is specifically designed for content creators and social media professionals, enabling Instagram and X (Twitter) influencers to produce highly artistic visual posts, empowering marketing teams to quickly generate event promotional graphics, assisting blog authors in creating featured images and illustrations, and helping knowledge-based creators transform key insights into easily shareable card visuals.

  Set up Instructions
  Fill in your API  key from PiAPI.
  Fill in Basic Params Node following the sticky note guidelines.
  Set up a design template in Canvas Switchboard. 
  Make a simple template in Switchboard.

  Click Crul and get the API code to fill in JSON of Design in Canvas. 

  Click Test Workflow and get a url result.

  Use Case
  Here we will provide some setting examples to help users find a proper way to use this workflow. User could change these settings based on specific purposes.

  Basic Params Setting: 
  theme: Hope
  scenario: Don't know about the future, confused and feel lost with tech-development. 
  style: Cinematic Grandeur, Sci-Tech Aesthetic, 3D style
  example: 1. March. Because of your faith, it will happen. 2. Something in me will save me. 3. To everyone carrying a heavy heart in silence. You are going to be okay. 4. Tomorrow will be better.
  image prompt: A cinematic sci-fi metropolis where Deep Neural Nets control a hyper-connected society. Holographic interfaces glow in the air as robotic agents move among humans, symbolizing Industry 4.0. The scene contrasts organic human emotion with cold machine precision, rendered in a hyper-realistic 3D style with futuristic lighting. Epic wide shots showcase the grandeur of this civilization’s industrial evolution.

  Output Image:

  More Example Results for Reference

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequest","n8n-nodes-base.manualTrigger","n8n-nodes-base.code","n8n-nodes-base.httpRequest","n8n-nodes-base.wait","n8n-nodes-base.if","n8n-nodes-base.switch","n8n-nodes-base.httpRequest","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.httpRequest","n8n-nodes-base.set","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 4672 characters]

metadata_json:
  {"categories":["automation","content creation","design","image generation","social media"],"complexity":"medium","use_cases":["Create social media visuals for Instagram/X (Twitter) influencers","Generate event promotional graphics for marketing teams","Produce featured images and illustrations for blogs","Convert key insights into shareable card-style visuals for knowledge creators"],"estimated_setup_minutes":30,"required_services":["GPT-4o-mini (or compatible OpenAI model)","Midjourney or compatible image-generation API","Canvas Switchboard / Canvas API (design template)","PiAPI (API gateway / key as described)","HTTP/webhook endpoints for workflow triggers"],"key_features":["Automated prompt generation using GPT model","Image generation via Midjourney (or equivalent)","Inject generated images into a Canvas design template (Switchboard)","Parameterized inputs (theme, scenario, style, example text, image prompt) for reusable outputs","Webhook/HTTP endpoint to return final image URL or asset"],"target_audience":["Content creators","Social media managers/influencers","Marketing teams and designers producing promo assets  (visuals) for campaigns  )  )  )  )  )  )"]}


name: 3D Figurine Orthographic Views with Midjourney and GPT-4o-image API
author_name: PiAPI
author_username: piapi
categories: []
created_at: 2025-04-21T09:21:54.543Z
updated_at: 2025-04-21T09:21:54.543Z
url: https://n8n.io/workflows/3628
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-14 21:18:32
description:
  What this workflow does?
  This workflow primarily uses the GPT-4o API from PiAPI and automatically creates front/side/top views of 3D models from commands.

  Who is this for？
  3D Designers： Quickly generate standardized orthographic views for design review
  E-commerce Operators： Create multi-angle product display images
  3D Modeling Beginners： Instantly produce basic reference views

  Step-by-step Instruction
  Fill in X-API-Key of your PiAPI account and the image prompt based on your inspiration.
  Click Test workflow.
  Get the image url in the final node.

  OutPut

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.if","n8n-nodes-base.wait","n8n-nodes-base.code","n8n-nodes-base.httpRequest","n8n-nodes-base.if","n8n-nodes-base.code","n8n-nodes-base.code"]

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metadata_json:
  {"categories":["automation","AI/ML integration","image generation","design tools"],"complexity":"medium","use_cases":["Generate standardized orthographic views (front/side/top) from a single prompt","Produce multi-angle product images for e-commerce listings","Create quick reference images for 3D modeling and design review","Rapid prototyping of presentation assets or thumbnails for 3D assets"],"estimated_setup_minutes":10,"required_services":["PiAPI (GPT-4o / GPT-4o-image) - X-API-Key","Midjourney (optional, if using alternative image styling workflows)","n8n instance (with Webhooks/HTTP access)"],"key_features":["Automatically generates orthographic views: front, side, top","Uses GPT-4o-image via PiAPI to synthesize images from a prompt","Single configurable prompt drives multi-view output","Returns image URL in the final node for easy retrieval or embedding","Includes conditional/logic nodes and code nodes for processing and formatting"],"target_audience":["3D designers","E-commerce operators / product photographers","3D modeling beginners and students"]}


name: Ultimate AI Assistant: Automate Email, Calendar, WebSearch, Notion, RAG & X
author_name: Tianyi
author_username: muzi
categories: []
created_at: 2025-04-21T10:06:33.761Z
updated_at: 2025-04-21T10:06:33.761Z
url: https://n8n.io/workflows/3629
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:32
description:
  This is an ultimate AI assistant: Handle emails, schedule meetings, search the web, take notes, post to social media, and retrieve information from your knowledge base, all through simple Telegram commands (text, voice, or image). 

  What is included:

  1 Ready-to-use n8n workflow file (.json)
  4 Instructional videos demonstrating how to connect n8n with:
      Google Products (Gmail, Calendar, Sheets)
      Telegram
      Pinecone Vector Store
      Notion

  Who is this for?

  This workflow is ideal for:

  Individuals seeking to automate personal and professional tasks.
  Professionals needing efficient management of emails, calendars, and contacts.
  Content creators or researchers requiring quick information retrieval and drafting capabilities.
  Anyone wanting a centralized AI assistant.

  What problem is this workflow solving?

  Managing numerous digital tasks across different platforms can be time-consuming and fragmented. This workflow consolidates control into Telegram, leveraging AI to understand your needs and automate actions across email, calendar, contacts, web search, note-taking (Notion), social media (X), and your personal knowledge base (Pinecone RAG), saving you time and effort. It ensures tasks are handled correctly using a built-in verification step.

  What this workflow does:

  This workflow acts as a central AI Agent that:

  Receives Input via Telegram: Accepts text messages, voice notes (transcribes them using OpenAI), or images (analyzes them using OpenAI).
  Understands Requests: Uses an AI Agent (powered by models like GPT) to interpret the user's instructions.
  Orchestrates Tools: Selects and uses the appropriate tools based on the request:
      Email (Gmail): Send, read, reply, draft, and label emails.
      Calendar (Google Calendar): Create, get, update, and delete events, managing attendees if needed.
      Contacts (Google Sheets): Look up and add contact information.
      Web Search (Tavily): Search the internet for up-to-date information.
      Knowledge Retrieval (Pinecone): Query your personal vector database (RAG).
      Note Taking (Notion): Create notes in a specified Notion database.
      Social Media (X/Twitter): Post tweets directly to X.
  Maintains Context: Uses Window Buffer Memory to remember recent interactions.
  Ensures Accuracy: Employs a "Think" tool to double-check tool usage and task completion.
  Responds via Telegram: Sends the results or confirmation back to the user in the Telegram chat.

  Setup:

  Telegram: Connect your Telegram bot credentials.
  AI Model: Connect your OpenAI API key.
  Email: Connect your Gmail account.
  Calendar: Connect your Google Calendar account.
  Contacts: Connect your Google Sheets account.
  Knowledge Base (RAG): Connect Pinecone.
  Note Taking: Connect Notion and configure Notion Database.
  Web Search: Add Tavily API key.
  Social Media: Connect your X (Twitter) account.

  (Refer to the included videos for detailed setup guidance)

  How to customize this workflow:

  AI Prompts:** Modify the system messages and prompts within the "AI Agent" node.
  AI Models:** Swap out the language model.
  Tools:** Add, remove, or replace tool nodes.

  Category:

  Automation, AI Agent, Personal Assistant, Productivity, Task Management, Telegram

nodes_used:
  ["n8n-nodes-base.telegramTrigger","n8n-nodes-base.switch","@n8n/n8n-nodes-langchain.openAi","@n8n/n8n-nodes-langchain.openAi","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.telegram","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.vectorStorePinecone","@n8n/n8n-nodes-langchain.embeddingsOpenAi","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.memoryBufferWindow","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.telegram","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.toolThink","n8n-nodes-base.gmailTool","n8n-nodes-base.gmailTool","n8n-nodes-base.gmailTool","n8n-nodes-base.gmailTool","n8n-nodes-base.gmailTool","n8n-nodes-base.gmailTool","n8n-nodes-base.googleCalendarTool","n8n-nodes-base.googleCalendarTool","n8n-nodes-base.googleCalendarTool","n8n-nodes-base.googleCalendarTool","n8n-nodes-base.googleCalendarTool","n8n-nodes-base.googleSheetsTool","n8n-nodes-base.googleSheetsTool","@n8n/n8n-nodes-langchain.toolHttpRequest","n8n-nodes-base.twitterTool","n8n-nodes-base.notionTool","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["automation","AI assistant","productivity","integration","communication"],"complexity":"complex","use_cases":["Automate email workflows (send/read/reply/draft/label)","Schedule and manage calendar events with attendees","Lookup and manage contacts","Transcribe voice and analyze images from Telegram","Perform up-to-date web searches and RAG retrieval from personal vector DB (Pinecone) for research/answers/drafting support」「Create and update notes in Notion and post to X (Twitter)"],"estimated_setup_minutes":60,"required_services":["Telegram Bot API","OpenAI (GPT + transcription/image APIs)","Gmail (Google account)","Google Calendar","Google Sheets","Pinecone Vector DB","Notion","Tavily (web search API)","X (Twitter) API"],"key_features":["Unified AI agent interface via Telegram (text, voice, image)","Tool orchestration across email, calendar, contacts, web search, RAG, notes, social posting","Gmail integration for send/read/reply/draft/label","Google Calendar event create/get/update/delete with attendee management","Contacts stored/queried via Google Sheets integration」「Pinecone-powered RAG retrieval for personalized knowledge base answers」「Notion note creation in a specified database」「Post to X (Twitter) from the agent」「Window buffer memory to maintain conversation context」「'Think' verification step to double-check actions before executing"],"target_audience":["Individuals wanting personal automation","Professionals managing email/calendar/contacts","Content creators and researchers needing fast drafting and retrieval workflows」「Users who want a centralized AI assistant accessed via Telegram"]}


name: Build your own FileSystem MCP server
author_name: Jimleuk
author_username: jimleuk
categories: []
created_at: 2025-04-21T10:07:32.061Z
updated_at: 2025-04-21T10:07:32.061Z
url: https://n8n.io/workflows/3630
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:32
description:
  This template is for self-hosted n8n instances only.
  This n8n demonstrates how to build a simple FileSystem MCP server. Connecting to this server allows MCP clients and agents to list, read and create directories and files on the local machine or remote server.

  This MCP example is based off an official MCP reference implementation which can be found here -https://github.com/modelcontextprotocol/servers/tree/main/src/filesystem

  How it works
  A MCP server trigger is used and connected to 5 tools: 3 Execute Command tools and 2 custom workflow tools.
  The 3 Execute Command tools allow for listing, searching and creating directories. 
  The 2 custom workflow tools are for reading and writing files to disk.
  Special care has been to not allow the MCP agent to execute arbitrary linux commands on the target server. This is achieved by only allowing the agent to provide parameters such as filenames and paths rather than raw commands. 

  How to use
  This Filesystem MCP server will write to the server which hosts the n8n instance - this can be your local machine or a remove server. If your target filesystem is on neither, then modify the commands to connect to the desired server.
  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:
    "Please help me list all folders under the project directory."
    "Help me create a bash script to send a notification to Slack."
    "Search for the log file on the 22nd April and read its contents. What was the cause of the outage?"

  Requirements
  Linux file system for this example template. Feel free to modify if working on Windows.
  MCP Client or Agent for usage such as Claude Desktop - https://claude.ai/download

  Customising this workflow
  Implement the moving and renaming of files by adding more custom workflow tools to the MCP server.
  Remember to set the MCP server to require credentials before going to production and sharing this MCP server with others!

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.mcpTrigger","n8n-nodes-base.executeCommandTool","n8n-nodes-base.executeCommandTool","n8n-nodes-base.executeWorkflowTrigger","n8n-nodes-base.switch","n8n-nodes-base.executeCommand","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","n8n-nodes-base.executeCommand","n8n-nodes-base.executeCommandTool","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
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metadata_json:
  {"categories":["automation","integration","file management","self‑hosting"],"complexity":"medium","use_cases":["Expose local/remote filesystem operations to MCP clients (list, read, create files/folders)","Search and read log files for troubleshooting","Allow agents to create scripts or files on the host machine","Build custom file-management actions (move/rename/modify) by extending the workflow"],"estimated_setup_minutes":30,"required_services":["n8n self‑hosted instance (required)","MCP client/agent such as Claude Desktop","Target Linux filesystem where n8n runs (or adjusted commands/SSH access for a remote host)"],"key_features":["MCP server trigger to accept client requests","Execute Command tools for listing/searching/creating directories","Custom workflow tools for safe read/write file operations","Parameter whitelisting to prevent arbitrary command execution","Extendable to add move/rename operations"],"target_audience":["developers","DevOps / system administrators","power users self‑hosting automation tools"]}


name: Build your own PostgreSQL MCP server
author_name: Jimleuk
author_username: jimleuk
categories: []
created_at: 2025-04-21T10:09:09.689Z
updated_at: 2025-04-21T10:09:09.689Z
url: https://n8n.io/workflows/3631
scraped_at: 2025-09-14 19:11:00
metadata_generated_at: 2025-09-14 21:18:31
description:
  This n8n demonstrates how to build a simple PostgreSQL MCP server to manage your PostgreSQL database such as HR, Payroll, Sale, Inventory and More!

  This MCP example is based off an official MCP reference implementation which can be found here -https://github.com/modelcontextprotocol/servers/tree/main/src/postgres

  How it works
  A MCP server trigger is used and connected to 5 tools: 2 postgreSQL and 3 custom workflow.
  The 2 postgreSQL tools are simple read-only queries and as such, the postgreSQL tool can be simply used.
  The 3 custom workflow tools are used for select, insert and update queries as these are operations which require a bit more discretion.
  Whilst it may be easier to allow the agent to use raw SQL queries, we may find it a little safer to just allow for the parameters instead. The custom workflow tool allows us to define this restricted schema for tool input which we'll use to construct the SQL statement ourselves.
  All 3 custom workflow tools trigger the same "Execute workflow" trigger in this very template which has a switch to route the operation to the correct handler.
  Finally, we use our standard PostgreSQL node to handle select, insert and update operations. The responses are then sent back to the the MCP client.

  How to use
  This PostgreSQL MCP server allows any compatible MCP client to manage a PostgreSQL database by supporting select, create and update operations. You will need to have a database available before you can use this server.
  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:
    "Please help me check if Alex has an entry in the users table. If not, please help me create a record for her."
    "What was the top selling product in the last week?"
    "How many high priority support tickets are still open this morning?"

  Requirements
  PostgreSQL for database. This can be an external database such as Supabase or one you can host internally.
  MCP Client or Agent for usage such as Claude Desktop - https://claude.ai/download

  Customising this workflow
  If the scope of schemas or tables is too open, try restrict it so the MCP serves a specific purpose for business operations. eg. Confine the querying and editing to HR only tables before providing access to people in that department.
  Remember to set the MCP server to require credentials before going to production and sharing this MCP server with others!

nodes_used:
  ["n8n-nodes-base.postgresTool","n8n-nodes-base.postgresTool","n8n-nodes-base.executeWorkflowTrigger","@n8n/n8n-nodes-langchain.toolWorkflow","n8n-nodes-base.postgres","n8n-nodes-base.switch","n8n-nodes-base.postgres","@n8n/n8n-nodes-langchain.toolWorkflow","n8n-nodes-base.postgres","@n8n/n8n-nodes-langchain.toolWorkflow","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.mcpTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["integration","automation","database-management"],"complexity":"medium","use_cases":["Expose PostgreSQL read/write operations to an MCP client/agent","Provide controlled select/insert/update access for HR, Payroll, Sales, Inventory","Build an agent-accessible DB management endpoint for QA or business users","Create parameter-restricted tools to avoid raw SQL exposure"],"estimated_setup_minutes":30,"required_services":["PostgreSQL database (self-hosted or hosted e.g., Supabase)","n8n instance","MCP-compatible client/agent (e.g., Claude Desktop)"],"key_features":["MCP server trigger to accept agent queries","Two read-only PostgreSQL query nodes for safe reads","Three custom tool workflows for parameterized select/insert/update","Central executeWorkflow trigger with switch routing","Constructed SQL from validated parameters to limit raw SQL use"],"target_audience":["developers building agent-driven workflows","data engineers and DBAs","automation/platform engineers"]}


name: Build your own SQLite MCP server
author_name: Jimleuk
author_username: jimleuk
categories: []
created_at: 2025-04-21T10:10:32.218Z
updated_at: 2025-04-21T10:10:32.218Z
url: https://n8n.io/workflows/3632
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-14 21:18:32
description:
  This template is for Self-Hosted N8N Instances only.

  This n8n demonstrates how to build a simple SQLite MCP server to perform local database operations as well as use it for Business Intelligence.

  This MCP example is based off an official MCP reference implementation which can be found here -https://github.com/modelcontextprotocol/servers/tree/main/src/sqlite

  How it works
  A MCP server trigger is used and connected to 5 tools: 2 Code Node and 3 Custom Workflow.
  The 2 Code Node tools use the SQLLite3 library and are simple read-only queries and as such, the Code Node tool can be simply used.
  The 3 custom workflow tools are used for select, insert and update queries as these are operations which require a bit more discretion.
  Whilst it may be easier to allow the agent to use raw SQL queries, we may find it a little safer to just allow for the parameters instead. The custom workflow tool allows us to define this restricted schema for tool input which we'll use to construct the SQL statement ourselves.
  All 3 custom workflow tools trigger the same "Execute workflow" trigger in this very template which has a switch to route the operation to the correct handler.
  Finally, we use our Code nodes to handle select, insert and update operations. The responses are then sent back to the the MCP client.

  How to use
  This SQLite MCP server allows any compatible MCP client to manage a SQLite database by supporting select, create and update operations. You will need to have a SQLite database available before you can use this server.
  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:
    "Please create a table to store business insights and add the following..."
    "what business insights do we have on current retail trends?"
    "Who has contributed the most business insights in the past week?"

  Requirements
  SQLite for database.
  MCP Client or Agent for usage such as Claude Desktop - https://claude.ai/download

  Customising this workflow
  If the scope of schemas or tables is too open, try restrict it so the MCP serves a specific purpose for business operations. eg. Confine the querying and editing to HR only tables before providing access to people in that department.
  Remember to set the MCP server to require credentials before going to production and sharing this MCP server with others!

nodes_used:
  ["n8n-nodes-base.executeWorkflowTrigger","n8n-nodes-base.switch","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.mcpTrigger","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.code","@n8n/n8n-nodes-langchain.toolCode","@n8n/n8n-nodes-langchain.toolCode","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
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metadata_json:
  {"categories":["integration","automation","data processing","business intelligence","self-hosted"],"complexity":"medium","use_cases":["Expose a local SQLite database to MCP agents/clients","Run read (select) and write (insert/update) DB operations via an MCP server","Provide a restricted schema toolset for safer agent-driven SQL operations","Enable BI-style queries against local data from MCP clients"],"estimated_setup_minutes":30,"required_services":["Self-hosted n8n instance","SQLite database file/engine","MCP client/agent (e.g., Claude Desktop)"],"key_features":["MCP server trigger to accept agent requests","Custom workflow tools for controlled select/insert/update operations","Code nodes using sqlite3 for read-only queries and DB handling","Routing via switch to appropriate handler workflow","Sends query results back to MCP client"],"target_audience":["n8n administrators / self-hosting engineers","Developers building agent integrations","Data analysts / BI engineers wanting agent-accessible local data"]}


name: Automated AI Product Photography and Instagram Post Generator (Deepseek/Segmind)
author_name: Tianyi
author_username: muzi
categories: []
created_at: 2025-04-21T10:10:43.292Z
updated_at: 2025-04-21T10:10:43.292Z
url: https://n8n.io/workflows/3633
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-14 21:18:32
description:
  Automatically generate professional-grade product photography and ready-to-use Instagram posts using the power of AI, delivered straight to your Telegram for approval.

  Setup is incredibly simple: All you need is your product image URL and a API key from Segmind.

  Who is this for?

  This template is ideal for:

  E-commerce store owners** looking to create high-quality product visuals affordably (The estimated cost is approximately $0.10 per product photography and accompanying Instagram post).
  Dropshippers** needing unique product images to stand out.
  Social Media Managers & Marketers** seeking to automate content creation for platforms like Instagram.
  Small Businesses** wanting professional marketing assets without the high cost or effort.
  Anyone needing consistent, eye-catching product photos and social media captions on a regular schedule.

  What problem is this workflow solving?

  Creating professional product images is often expensive and time-consuming, requiring photographers, studios, and editing time. Consistently generating fresh and engaging social media content, especially for visual platforms like Instagram, adds another layer of complexity and effort. This workflow eliminates these bottlenecks by automating both high-quality image generation and relevant caption creation, freeing up your time and budget.

  What this workflow does:

  This n8n workflow automates the entire process on a schedule you define (e.g., every hour, every day):

  Scheduled Start: Triggers automatically based on your chosen time interval (e.g., every hour).
  Product Analysis: Takes your input product image URL and uses AI (GPT) to understand the product details.
  AI Prompt Generation: Based on the product analysis and your preference (whether to include a human model or not), it uses AI (Deepseek) to craft a sophisticated prompt specifically for generating professional product photography via Segmind.
  Instagram Post Creation: Simultaneously, the AI (Deepseek) generates an engaging Instagram post caption, complete with relevant hashtags, tailored to your product.
  AI Image Generation: Sends the product image, the generated prompt, and product details to the Segmind API to create a brand new, studio-quality product photograph.
  Telegram Validation: Downloads the newly generated product photo and sends both the photo and the generated Instagram post text directly to your specified Telegram chat. This allows you to quickly review and approve the content before using it.

  Setup: Get Running in Minutes!

  This workflow is designed for maximum ease of setup:

  Get Segmind API Key: Sign up or log in to Segmind and grab your API key here: https://cloud.segmind.com/console/api-keys
  Enter API Key: In the n8n workflow, click on the SegmindAPIKey node and paste your copied API key into the Value field.
  Enter Product Image URL: Click the InputYourImageURL node and paste the web address (URL) of your product image into the Value field.
  (Optional) Human Model Preference: Click the ImageInstruction node. Set the HumanModel value to true if you want a human model potentially included in the photo, or false if you want the product showcased alone or in a setting.
  Set Your Schedule: Click the Schedule Trigger node. Define how often you want the workflow to run (e.g., under Interval, set 1 and select Hours from the dropdown for hourly runs).
  Configure Telegram: Make sure you have a Telegram Bot credential configured in n8n. Then, in the SendProductPhotography and SendInstagramPost nodes, enter the correct Chat ID for where you want to receive the validation messages. [A video guidance is made to help you with telegram setup]
  Activate Workflow: Toggle the workflow to "Active" in the top right corner of n8n.

  That's it! The workflow will now automatically generate and send product photos and Instagram posts to your Telegram at your defined interval.

  How to customize this workflow:

  While the default setup works great, you can easily tweak it:

  Photography Style:** Modify the main prompt within the AI Agent1 node to guide the AI towards a specific aesthetic (e.g., "minimalist background," "bright natural lighting," "dark moody atmosphere").
  Instagram Post Tone:** Adjust the instructions within the AI Agent1 node to change the style or focus of the generated Instagram captions.
  Schedule:** Change the trigger interval in the Schedule Trigger node anytime.
  AI Models:** Experiment by changing the selected models in the OpenAI, OpenAI Chat Model1 (Deepseek).

  Category:

  Marketing, Social Media, E-commerce, Automation, AI, Content Creation, Product Photography

nodes_used:
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metadata_json:
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name: Build your own Google Drive MCP server
author_name: Jimleuk
author_username: jimleuk
categories: []
created_at: 2025-04-21T10:11:41.815Z
updated_at: 2025-04-21T10:11:41.815Z
url: https://n8n.io/workflows/3634
scraped_at: 2025-09-14 19:11:00
metadata_generated_at: 2025-09-14 21:18:31
description:
  This n8n demonstrates how to build a simple Google Drive MCP server to search and get contents of files from Google Drive.

  This MCP example is based off an official MCP reference implementation which can be found here -https://github.com/modelcontextprotocol/servers/tree/main/src/gdrive

  How it works
  A MCP server trigger is used and connected to 1x Google Drive tool and 1x Custom Workflow tool.
  The Google Drive tool is set to perform a search on files within our Google Drive folder.
  The Custom Workflow tool downloads target files found in our drive and converts the binaries to their text representation. Eg. PDFs have only their text contents extracted and returned to the MCP client.

  How to use
  This Google Drive MCP server allows any compatible MCP client to manage a person or shared Google Drive. Simple select a drive or for better control, specify a folder within the drive to scope the operations to.
  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:
    "Please help me search for last month's expense reports."
   "What does the company policy document say about cancellations and refunds?"

  Requirements
  Google Drive for documents.
  OpenAI for image and audio understanding.
  MCP Client or Agent for usage such as Claude Desktop - https://claude.ai/download

  Customising this workflow
  Add additional capabilities such as renaming, moving and/or deleting files.
  Remember to set the MCP server to require credentials before going to production and sharing this MCP server with others!

nodes_used:
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metadata_json:
  {"categories":["integration","automation","document processing","search","AI/LLM integration"],"complexity":"medium","use_cases":["Search and retrieve files from Google Drive via MCP","Extract and return text contents from binary files (PDFs, images, audio)","Expose a Google Drive-backed MCP server for LLM/agent access","Scope document searches to a drive or specific folder","Enable LLM-based understanding of images/audio using OpenAI"],"estimated_setup_minutes":30,"required_services":["n8n instance","Google Drive (OAuth access)","OpenAI (for image/audio understanding)","MCP client/agent (e.g., Claude Desktop)"],"key_features":["MCP server trigger to accept client queries","Google Drive file search and retrieval","Custom workflow node to download and convert binaries to text","PDF text extraction and binary-to-text conversion","Ability to scope searches to a drive or folder level','Supports adding actions like rename/move/delete with customization"],"target_audience":["Developers building MCP integrations","IT admins or platform engineers managing shared drives","Data engineers and knowledge managers enabling LLM access to documents"]}


name: Build your own Github MCP server
author_name: Jimleuk
author_username: jimleuk
categories: []
created_at: 2025-04-21T10:13:11.626Z
updated_at: 2025-04-21T10:13:11.626Z
url: https://n8n.io/workflows/3635
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:32
description:
  This n8n demonstrates how to build your own Github MCP server to personalise it to your organisation's repositories, issues and pull requests.

  This n8n implementation, though not as fully featured as the official MCP server offered by Github, allows you to control precisely what access and/or functionality is granted to users which can make MCP use simpler and in some cases, more secure. The use-case in this template is to simply view and comment on issues within a specific repository but can be extended to meet the needs of your team.

  This MCP example is based off an official MCP reference implementation which can be found here https://github.com/modelcontextprotocol/servers/tree/main/src/github

  How it works
  A MCP server trigger is used and connected to 3 custom workflow tools. We're using custom workflow tools as there is quite a few nodes required for each task.
  Behind these tools are regular Github nodes although preconfigured with credentials and targeted repository.
  The "Get Issue Comments" and "Create Issue Comment" tools depend on obtaining an Issue Number first. The agent should call the "Get Latest Issues" tool for this.

  How to use
  This Github MCP server allows any compatible MCP client to view and comment on Github Issues. You will need to have a Github account and repository access available before you can use this server.
  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 get me the latest issues about MCP?"
    "What is the current progress on Issue 12345?"
    "Please can you add a comment to Issue 12345 that they should try installing the latest version and see if that works?"

  Requirements
  Github for account and repository access. The repository need not be your own but you'll still need to ensure you have the correct permissions.
  MCP Client or Agent for usage such as Claude Desktop - https://claude.ai/download

  Customising this workflow
  Extend this template to interactive with pull requests or workflows within your own company's Github repositories. Alternatively,  pull in metrics and generate reports for programme managers.
  Remember to set the MCP server to require credentials before going to production and sharing this MCP server with others!

nodes_used:
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metadata_json:
  {"categories":["integration","developer tools","collaboration","automation"],"complexity":"medium","use_cases":["Expose repository issues to MCP clients","Allow MCP clients to view and comment on GitHub issues","Create a scoped/custom MCP server for controlled access to repo data","Integrate MCP clients with GitHub workflows and PRs (extensible)","Generate issue/metrics reports for programme managers"],"estimated_setup_minutes":30,"required_services":["GitHub (account + repository access)","n8n instance","MCP-compatible client (e.g., Claude Desktop)","GitHub API credentials"],"key_features":["MCP Trigger to receive client requests","Custom workflow tools: Get Latest Issues, Get Issue Comments, Create Issue Comment","Preconfigured GitHub nodes scoped to a target repository","Controlled permission scoping for safer MCP usage","Extensible to pull requests, workflows, and reporting/metrics"],"target_audience":["Developers","Repository maintainers","Platform/DevOps engineers`,`Program/product managers"]}


