# templates

name: Complete Shopify to Odoo Integration: Sync Orders, Products & Customers
author_name: Evozard
author_username: evozardconsulting
categories: []
created_at: 2025-05-15T10:58:11.724Z
updated_at: 2025-05-15T10:58:11.724Z
url: https://n8n.io/workflows/4069
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-14 21:18:32
description:
  This workflow functions like the integration of Shopify products with Odoo products, Shopify customers with Odoo customers, and paid Shopify orders with Odoo sales orders containing multiple products.
   
  Trigger (Shopify – Order Created & Paid): The workflow starts when a new order is created in Shopify and its status is marked as paid.
   
  Loop Through Each Line Item in the Order:
      For each product in the order:
          Check if Product Exists in Odoo (via Internal Reference/Default Code)
  	    If the product exists, proceed.
  	    If the product does not exist, create it in Odoo with the following details:
  	        Product Name
  		Description
  		Price
  		Internal Reference (Default Code)
   
  Check if Customer Contact Exists in Odoo (via Email):
      If the contact exists, proceed.
      If the contact does not exist, create a new contact in Odoo with:
          Full Name
          Email Address
          Phone Number
          Shipping or Billing Address (as available)
   
  Create a Sale Order in Odoo:
      Create a new Sale Order in Odoo using:
          The matched or newly created Customer Contact
          The matched or newly created All the Products in the Shopify order (with correct quantities and pricing)
      Each Shopify product in the order is matched to the corresponding Odoo product using the Internal Reference field
      
  Integration Setup References:
   
      Shopify Integration Setup:
      https://docs.n8n.io/integrations/builtin/credentials/shopify/
   
      Odoo Integration Setup:
      https://docs.n8n.io/integrations/builtin/credentials/odoo/

nodes_used:
  ["n8n-nodes-base.shopifyTrigger","n8n-nodes-base.odoo","n8n-nodes-base.code","n8n-nodes-base.splitOut","n8n-nodes-base.odoo","n8n-nodes-base.odoo","n8n-nodes-base.code","n8n-nodes-base.odoo","n8n-nodes-base.filter","n8n-nodes-base.odoo","n8n-nodes-base.odoo","n8n-nodes-base.filter","n8n-nodes-base.code","n8n-nodes-base.splitOut","n8n-nodes-base.code","n8n-nodes-base.odoo","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.odoo"]

workflow_json_compressed:
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metadata_json:
  {"categories":["integration","e-commerce","automation","ERP/CRM synchronization"],"complexity":"complex","use_cases":["Sync Shopify products to Odoo (create if missing)","Sync Shopify customers to Odoo (create if missing)","Create Odoo sales orders from paid Shopify orders with correct line items and pricing","Automate order processing and catalog consistency between Shopify and Odoo","Match products using Internal Reference/Default Code for reliable mapping"],"estimated_setup_minutes":60,"required_services":["Shopify (API)","Odoo (API/ERP)","n8n (workflow automation platform)"],"key_features":["Trigger on Shopify Order Created & Paid","Loop through order line items and handle each product","Check-for-or-create product in Odoo (name, description, price, internal reference)","Check-for-or-create customer in Odoo (name, email, phone, address)","Create Odoo Sale Order with matched products, quantities and pricing using Internal Reference matching"],"target_audience":["ecommerce managers","ERP/CRM administrators","integration engineers/developers implementing system-to-system syncs\",\"small and medium businesses using Shopify and Odoo"]}


name: Linking NocoDB Records via API 🔗
author_name: Max aka Mosheh
author_username: aiwithapex
categories: []
created_at: 2025-05-15T13:39:15.959Z
updated_at: 2025-05-15T13:39:15.959Z
url: https://n8n.io/workflows/4070
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-14 21:18:33
description:
  How it works:
  The n8n flow grabs the needed IDs, fetches the current links, adds your new one, and sends a single HTTP request to NocoDB to update the record’s linked entries.

  Set up steps:

  Plan for 10 minutes setup if you’re already running n8n and NocoDB.
  You’ll need to copy/paste table IDs, set up your HTTP node, and test once.
  No coding, just copy IDs.

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.nocoDb","n8n-nodes-base.set","n8n-nodes-base.httpRequest","n8n-nodes-base.nocoDb","n8n-nodes-base.httpRequest","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
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metadata_json:
  {"categories":["integration","automation","databases","no-code"],"complexity":"simple","use_cases":["Add a link between NocoDB records","Update a record's linked entries via API","Automate relational data maintenance between tables","Quickly test and apply record relationships without coding"],"estimated_setup_minutes":10,"required_services":["n8n","NocoDB (API access)","HTTP/Webhooks endpoint (for API requests)"],"key_features":["Retrieves required record/table IDs","Fetches current linked entries and appends a new link","Sends a single HTTP request to update linked records","No-code configuration—copy/paste IDs and test","Uses n8n NocoDB and HTTP nodes for orchestration"],"target_audience":["n8n users","No-code/low-code builders","Database administrators and data stewards`,`Integrators and product managers"]}


name: AI-Powered RAG Q&A Chatbot with OpenAI, Google Sheets, Glide & Supabase
author_name: Sam Yassine
author_username: samyassine
categories: []
created_at: 2025-05-15T14:00:56.738Z
updated_at: 2025-05-15T14:00:56.738Z
url: https://n8n.io/workflows/4071
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:32
description:
  Automate AI-Powered RAG System with Contextual Q&A, Google Sheets Integration, and Glide Frontend—Powered by n8n, OpenAI, Supabase, and Google Apps Script.

  Tools & Services Used
  Glide (Frontend for user interactions)

  Google Sheets (Stores questions and answers)

  Google Apps Script (Forms + media upload handling)

  OpenAI (Embeddings + GPT-4 to rank and generate answers)

  Supabase (Optional for image hosting)

  n8n (Automation logic and backend glue)

  Workflow Overview
  This automation performs the following steps:

  Trigger: Webhook receives a user question from a Glide frontend.

  Fetch Data: Retrieves Q&A entries (and optionally, image URLs) from a connected Google Sheet.

  Rank Relevance:

  OpenAI Embeddings rank the relevance of stored questions to the new input.

  Top matches are passed to a GPT-4 prompt for answer generation.

  Generate Answer:

  GPT-4 creates a contextual answer using the best match.

  Optional: Includes media URL if attached to the matched answer.

  Response: Sends the formatted answer back to Glide frontend (text + optional image).

  Prerequisites
  Active accounts and API keys for:

  OpenAI (API key with GPT-4 and embedding access)

  Google Sheets (linked via Service Account or OAuth2 credentials)

  Glide App (with a form to submit questions)

  Supabase (optional, if hosting user-uploaded media)

  n8n Self-hosted (for community nodes and webhook access)

  How to Use This Template
  Step 1: Import the Template
  Upload the provided JSON into your self-hosted n8n instance.

  Requires installation of the Community Node: @n8n/n8n-nodes-openai-embeddings

  Step 2: Configure Credentials
  Webhook Trigger: Replace the Glide webhook URL with your actual endpoint from your app.

  Google Sheets Node: Set the spreadsheet ID and worksheet name to fetch your Q&A dataset.

  OpenAI Nodes:

  Insert your OpenAI API key.

  Confirm that both text-embedding-ada-002 (or similar) and gpt-4 are available.

  Supabase or Apps Script (Optional): Ensure image links are correctly formed in the Sheet.

  Step 3: Customize Prompts and Thresholds
  Update the OpenAI ranking prompt or similarity threshold in the Function or Code node.

  Tailor GPT-4 prompts to return concise or detailed answers based on your use case.

  Initial Test Run
  Simulate a Question:
  Trigger the Glide form with a sample question.

  Check n8n logs for:

  Matching score/ranking success

  Correct retrieval from Sheets

  GPT-4 answer generation

  Image URL handling (if enabled)

  Production Prep
  Add error-handling nodes for cases when Sheets are empty or GPT-4 fails.

  Set up logging via Google Sheets, Supabase, or external database.

  Rate-limit or debounce requests from Glide if needed.

  Use Cases
  Customer Support Portals: Offer instant Q&A with your business data.

  Internal Knowledgebase: Employees can query training manuals and SOPs.

  AI Concierge: Combine structured answers with friendly tone for guest interactions.

  Disclaimer

  Validate Glide form inputs before full deployment.

  Ensure your OpenAI and Google Sheets usage stays within quota limits.

nodes_used:
  ["n8n-nodes-base.webhook","n8n-nodes-base.googleCalendar","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.chainLlm","n8n-nodes-base.webhook","@n8n/n8n-nodes-langchain.vectorStoreQdrant","@n8n/n8n-nodes-langchain.embeddingsOpenAi","@n8n/n8n-nodes-langchain.toolVectorStore","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.webhook","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.respondToWebhook","n8n-nodes-base.httpRequest","n8n-nodes-base.respondToWebhook","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.respondToWebhook","n8n-nodes-base.stickyNote","n8n-nodes-base.manualTrigger","@n8n/n8n-nodes-langchain.vectorStoreQdrant","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.googleDrive","n8n-nodes-base.googleDrive","@n8n/n8n-nodes-langchain.embeddingsOpenAi","@n8n/n8n-nodes-langchain.documentDefaultDataLoader","@n8n/n8n-nodes-langchain.textSplitterTokenSplitter","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","data processing","AI/ML"],"complexity":"complex","use_cases":["Customer support portals (instant contextual Q&A)","Internal knowledgebase / employee helpdesk","AI concierge for apps (contextual responses with media)","FAQ automation and response enrichment"],"estimated_setup_minutes":90,"required_services":["OpenAI (embeddings + GPT-4)","Google Sheets","Glide (frontend)","n8n (self-hosted instance)","Google Apps Script","Supabase (optional - media hosting)","Qdrant (optional - vector store)","Google Drive (optional - media storage)"],"key_features":["RAG-style retrieval using OpenAI embeddings to rank stored Q&A","GPT-4 generated contextual answers built from top matches","Webhook trigger from Glide for real-time Q&A","Google Sheets as the Q&A datastore (with optional image URLs)","Optional media handling and hosting (Supabase / Google Drive / Apps Script integration)"],"target_audience":["Developers implementing conversational AI frontends","Product teams building knowledge-driven features","Support/operations teams automating FAQ and helpdesk responses"]}


name: Enrich Seller Data with Email & Domain Lookup using Bright Data & Google Search
author_name: Cyril Nicko Gaspar
author_username: cngaspar
categories: []
created_at: 2025-05-15T14:35:17.827Z
updated_at: 2025-05-15T14:35:17.827Z
url: https://n8n.io/workflows/4072
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-14 21:18:33
description:
  🔍 Email Lookup with Google Search from Postgres Database

  This N8N workflow is designed to enrich seller data stored in a Postgres database by performing automated Google search lookups. It uses Bright Data's Web Unlocker to bypass search result restrictions and the HTML Extract node to parse and extract relevant information from webpages.

  The main purpose of this workflow is to discover missing contact details, company domains, and secondary emails for businesses or sellers based on existing database entries.

  🎯 Problem This Workflow Solves

  Manually searching for missing seller or business details—like secondary emails, websites, or domain names—can be time-consuming and inefficient, especially for large datasets.
  This workflow automates the search and data enrichment process, significantly reducing manual effort while improving the quality and completeness of your seller database.

  ✅ Prerequisites

  Before using this template, make sure the following requirements are met:

  ✔️ A Bright Data account with access to the Web Unlocker or Amazon Scraper API
  ✔️ A valid Bright Data API key
  ✔️ An active PostgreSQL database with seller data
  ✔️ N8N self-hosted instance (recommended for using community nodes like n8n-nodes-brightdata)
  ✔️ Installed n8n-nodes-brightdata package (custom node for Bright Data integration)

  ⚙️ Setup Instructions

  Step 1: Prepare Your Postgres Table

  Create a table in Postgres with the following structure (you can adjust field names if needed):

  CREATE TABLE sellers (
    seller_id SERIAL PRIMARY KEY,
    seller_name TEXT,
    primary_email TEXT,
    company_info TEXT,
    trade_name TEXT,
    business_address TEXT,
    coc_number TEXT,
    vat_number TEXT,
    commercial_register TEXT,
    secondary_email TEXT,
    domain TEXT,
    seller_slug TEXT,
    source TEXT
  );

  Step 2: Setup Web Unlocker on Bright Data

  Go to your Bright Data dashboard.
  Navigate to Proxies & Scraping → Web Unlocker.
  Create a new zone, selecting Web Unlocker API under Scraping Solutions.
  Whitelist your server IP if required.

  Step 3: Generate API Key

  In the Bright Data dashboard, go to the API section.
  Generate a new API key.
  In N8N, create HTTP Request Credentials using Bearer Authentication with the API key.

  Step 4: Install the Bright Data Node in N8N

  In your N8N self-hosted instance, go to Settings → Community Nodes.
  Search and install n8n-nodes-brightdata.

  🔄 Workflow Functionality

  🔁 Trigger: Can be set to run on a schedule (e.g., daily) or manually.
  📥 Read: Fetches seller records from the Postgres table.
  🌐 Search: Uses Bright Data to perform a Google search based on seller_name, company_info, or trade_name.
  🧾 Extract: Parses the HTML content using the HTML Extract node to identify potential websites and email addresses.
  📝 Update: Writes enriched data (like domain or secondary_email) back to the Postgres table.

  💡 Use Cases

  Lead enrichment for e-commerce sellers
  Domain and contact info discovery for B2B databases
  Email and web domain verification for CRM systems
  Market research automation

  🛠️ Customization Tips

  You can enhance the parsing logic in the HTML Extract node to look for phone numbers, LinkedIn profiles, or social media links.
  Modify the search query logic to include additional parameters like location or industry for more refined results.
  Integrate additional APIs (e.g., Hunter.io, Clearbit) for email validation or social profile enrichment.
  Add filtering to skip entries that already have domain or secondary_email.

nodes_used:
  ["n8n-nodes-base.manualTrigger","n8n-nodes-base.postgres","n8n-nodes-base.wait","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.postgres","n8n-nodes-base.switch","n8n-nodes-base.code","n8n-nodes-base.postgres","n8n-nodes-base.switch","n8n-nodes-base.postgres","n8n-nodes-base.wait","n8n-nodes-base.set","n8n-nodes-base.splitInBatches","n8n-nodes-brightdata.brightData","n8n-nodes-brightdata.brightData","n8n-nodes-base.html","n8n-nodes-base.html","n8n-nodes-base.splitOut","n8n-nodes-base.filter","n8n-nodes-base.aggregate","n8n-nodes-base.code","n8n-nodes-base.splitOut","n8n-nodes-base.filter","n8n-nodes-base.if","n8n-nodes-base.aggregate","n8n-nodes-base.stickyNote","n8n-nodes-base.if","n8n-nodes-base.code","n8n-nodes-base.postgres","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 6808 characters]

metadata_json:
  {"categories":["automation","data enrichment","web scraping","database integration"],"complexity":"complex","use_cases":["Lead enrichment for e-commerce sellers","Domain and contact discovery for B2B databases","Email and web domain verification for CRM systems","Market research automation"],"estimated_setup_minutes":45,"required_services":["Bright Data (Web Unlocker / Scraping API)","PostgreSQL database","n8n self-hosted instance","n8n-nodes-brightdata community node (Bright Data integration)"],"key_features":["Automated Google search via Bright Data to bypass result restrictions","HTML extraction and parsing to find domains and secondary emails","Reads from and writes enriched records back to Postgres","Configurable scheduled or manual trigger","Supports custom parsing logic and additional API integrations (e.g., Hunter, Clearbit)"],"target_audience":["Developers / Automation Engineers","Data Engineers","Growth / Marketing teams (lead enrichment)  GMT/CRM admins]"]}


name: Automate GitHub PR Linting with Google Gemini AI and Auto-Fix PRs
author_name: Adam Bertram
author_username: adbertram
categories: []
created_at: 2025-05-15T15:00:58.877Z
updated_at: 2025-05-15T15:00:58.877Z
url: https://n8n.io/workflows/4073
scraped_at: 2025-09-14 19:11:03
metadata_generated_at: 2025-09-14 21:18:33
description:
  LintGuardian: Automated PR Linting with n8n & AI

  What It Does

  LintGuardian is an n8n workflow template that automates code quality enforcement for GitHub repositories. When a pull request is created, the workflow automatically analyzes the changed files, identifies linting issues, fixes them, and submits a new PR with corrections. This eliminates manual code style reviews, reduces back-and-forth comments, and lets your team focus on functionality rather than formatting.

  How It Works

  The workflow is triggered by a GitHub webhook when a PR is created. It fetches all changed files from the PR using the GitHub API, processes them through an AI-powered linting service (Google Gemini), and automatically generates fixes. The AI agent then creates a new branch with the corrected files and submits a "linting fixes" PR against the original branch. Developers can review and merge these fixes with a single click, keeping code consistently formatted with minimal effort.

  Prerequisites

  To use this template, you'll need:

  n8n instance: Either self-hosted or using n8n.cloud
  GitHub repository: Where you want to enforce linting standards
  GitHub Personal Access Token: With permissions for repo access (repo, workflow, admin:repo_hook)
  Google AI API Key: For the Gemini language model that powers the linting analysis
  GitHub webhook: Configured to send PR creation events to your n8n instance

  Setup Instructions

  Import the template into your n8n instance
  Configure credentials:
     Add your GitHub Personal Access Token under Credentials → GitHub API
     Add your Google AI API key under Credentials → Google Gemini API
  Update repository information:
     Locate the "Set Common Fields" code node at the beginning of the workflow
     Change the gitHubRepoName and gitHubOrgName values to match your repository
        const commonFields = {
       'gitHubRepoName': 'your-repo-name',
       'gitHubOrgName': 'your-org-name'
     }
     Configure the webhook:
   Create a file named .github/workflows/lint-guardian.yml in your repository replacing the Trigger n8n Workflow step with your webhook:
            name: Lint Guardian
       
       on:
         pull_request:
           types: [opened, synchronize]
       
       jobs:
         trigger-linting:
           runs-on: ubuntu-latest
           steps:
             name: Trigger n8n Workflow
               uses: fjogeleit/http-request-action@v1
               with:
                 url: 'https://your-n8n-instance.com/webhook/1da5a6e1-9453-4a65-bbac-a1fed633f6ad'
                 method: 'POST'
                 contentType: 'application/json'
                 data: |
                   {
                     "pull_request_number": ${{ github.event.pull_request.number }},
                     "repository": "${{ github.repository }}",
                     "branch": "${{ github.event.pull_request.head.ref }}",
                     "base_branch": "${{ github.event.pull_request.base.ref }}"
                   }
                 preventFailureOnNoResponse: true
       Customize linting rules (optional):
     Modify the AI Agent's system message to specify your team's linting preferences
     Adjust file handling if you have specific file types to focus on or ignore

  Security Considerations

  When creating your GitHub Personal Access Token, remember to:
  Choose the minimal permissions needed (repo, workflow, admin:repo_hook)
  Set an appropriate expiration date
  Treat your token like a password and store it securely
  Consider using GitHub's fine-grained personal access tokens for more limited scope

  As GitHub documentation notes: "Personal access tokens are like passwords, and they share the same inherent security risks."

  Extending the Template

  You can enhance this workflow by:
  Adding Slack notifications when linting fixes are submitted
  Creating custom linting rules specific to your team's needs
  Expanding it to handle different types of code quality checks
  Adding approval steps for more controlled environments

  This template provides an excellent starting point that you can customize to fit your team's exact workflow and code style requirements.

nodes_used:
  ["n8n-nodes-base.webhook","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.respondToWebhook","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.convertToFile","n8n-nodes-base.extractFromFile","n8n-nodes-base.set","n8n-nodes-base.aggregate","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequestTool","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequestTool","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","n8n-nodes-base.code"]

workflow_json_compressed:
  [encoded data, 4128 characters]

metadata_json:
  {"categories":["automation","integration","code quality","AI-assisted development"],"complexity":"medium","use_cases":["Automatically lint and auto-fix PRs","Enforce code style and consistency","Reduce manual code-review overhead","Generate fix branches and PRs for maintainers"],"estimated_setup_minutes":30,"required_services":["n8n (self-hosted or n8n.cloud)","GitHub (repository + webhook + Personal Access Token)","Google AI / Gemini API (API key)"],"key_features":["Webhook-triggered on PR creation/sync","Fetches changed files via GitHub API","AI-powered lint analysis and auto-fixes (Google Gemini)","Creates branch and opens a \"linting fixes\" PR","Configurable linting rules via AI system message and workflow settings"],"target_audience":["Developers","DevOps/Platform engineers","Repository maintainers and code reviewers"]}


name: Financial News Digest with Google Gemini AI to Outlook Email
author_name: Louis
author_username: louisdl
categories: []
created_at: 2025-05-15T17:15:58.107Z
updated_at: 2025-05-15T17:15:58.107Z
url: https://n8n.io/workflows/4074
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:32
description:
  🧠 Key Features

  Looping source scraping: Collects content from news sites you have selected (it might not work for all of them however)
  HTML extraction & cleaning: Parses, cleans, and filters messy website data to isolate only the most relevant content.
  AI-powered synthesis: Uses Google Gemini (via LangChain agent) to summarize and structure financial news into a clear, bullet-pointed format.
  Email-ready output: Generates styled HTML summaries with coral-colored headings, ideal for daily email reports.
  Fully automated delivery: Sends out beautifully formatted updates via Outlook — no manual work required.

  🔧 Technologies Used

  n8n workflow orchestration
  LangChain agents for prompt logic and formatting
  Google Gemini API for advanced NLP
  Custom JS logic to manage dynamic inputs and cleanup
  Microsoft Outlook API for final distribution

  &gt; Feel free to reach out if needed ! 

nodes_used:
  ["n8n-nodes-base.httpRequest","n8n-nodes-base.scheduleTrigger","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.microsoftOutlook","n8n-nodes-base.manualTrigger","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.outputParserItemList","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatGoogleGemini","n8n-nodes-base.set","n8n-nodes-base.aggregate","n8n-nodes-base.code","n8n-nodes-base.splitInBatches","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
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metadata_json:
  {"categories":["automation","integration","data processing","news aggregation","reporting"],"complexity":"complex","use_cases":["Daily financial news digest for teams or clients","Investor/portfolio update emails","Market-moving event alerts and summaries","Generating executive-ready market briefings","Automated newsletter or outreach content generation"],"estimated_setup_minutes":90,"required_services":["n8n (workflow host)","Google Gemini API (via LangChain)","LangChain agent integration","Microsoft Outlook API (for sending emails)","Access to target news websites/web scraping endpoints"],"key_features":["Looping source scraping of selected news sites","HTML extraction, cleaning and content filtering","AI-powered synthesis and bullet-point summarization (Google Gemini)","Styled HTML output for email (coral-colored headings)","Automated scheduled delivery via Outlook (manual trigger supported)"],"target_audience":["financial analysts and researchers","portfolio managers and investors","marketing/communications teams producing newsletters\",\"automation engineers and n8n users"]}


name: Automated Tweet Generator & Publisher with GPT-4, Discord, and Google Sheets
author_name: LukaszB
author_username: lukaszb
categories: []
created_at: 2025-05-15T17:47:41.088Z
updated_at: 2025-05-15T17:47:41.088Z
url: https://n8n.io/workflows/4075
scraped_at: 2025-09-14 19:11:00
metadata_generated_at: 2025-09-14 21:18:32
description:
  AI Twitter Content Machine – Write, Refine & Publish Tweets on Autopilot

  This workflow is perfect for creators, solopreneurs, and personal brands who want to consistently publish bold, high-performing content on X (Twitter) — without writing a single line themselves. After a one-time setup, it automatically generates tweet ideas, writes in your voice, evaluates post quality, avoids duplicates, and publishes directly to Twitter. All approvals and rewrites are handled in a conversational loop powered by OpenAI, Discord, and Google Sheets.

  Whether you’re building a personal brand or growing your startup audience, this tool will help you stay active, edgy, and relevant — with zero friction.

  How it works
  Distill what your flow does in a few high-level steps.
  Loads your brand brief from a sub-workflow.
  Generates a tweet idea aligned with your tone.
  Checks Google Sheets to ensure the idea hasn’t been used.
  Writes the post.
  Evaluates it using a feedback sub-workflow — if the quality score is below 0.7, it rewrites the post.
  Refines tone and voice using a Rewriter Agent that mimics your past content (from a Google Sheet).
  Sends the final post to a Discord channel for manual approval.
  On approval, posts directly to Twitter (X) and logs it to Google Sheets (History and Examples tabs).

  Set up steps
  Give users an idea of how long setup will take. Don’t describe every detail.
  Keep detailed descriptions in sticky notes inside your workflow.

  Key benefits
  No burnout, no block – Stop spending energy thinking what to tweet. AI handles everything.
  Style-matching – Posts sound like you, not a generic robot. Based on your real writing.
  Fast & scalable – Publish once or five times a day — it’s up to you.
  Avoid duplicates – Each idea is checked against your post history.
  Human-in-the-loop – You approve final posts via Discord. No rogue tweets.

  Integrations required
  n8n
  OpenAI API
  Google Sheets
  Twitter (OAuth2)
  Discord (for approval)
  Notion (optional for brand brief storage)

nodes_used:
  ["@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.memoryBufferWindow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.discord","n8n-nodes-base.if","n8n-nodes-base.if","n8n-nodes-base.executeWorkflow","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.outputParserStructured","@n8n/n8n-nodes-langchain.chainLlm","n8n-nodes-base.manualTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.memoryBufferWindow","n8n-nodes-base.googleSheetsTool","n8n-nodes-base.googleSheetsTool","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.discord","n8n-nodes-base.discord","n8n-nodes-base.discord","n8n-nodes-base.discord","n8n-nodes-base.twitter","n8n-nodes-base.googleSheets","n8n-nodes-base.googleSheets","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.executeWorkflowTrigger","n8n-nodes-base.notion","n8n-nodes-base.aggregate","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.executeWorkflow","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["automation","social media","AI content generation","integrations"],"complexity":"complex","use_cases":["Automated tweet/post generation and publishing","Personal brand growth and audience engagement","Scaling social content without manual writing","Maintaining consistent voice/style across posts","Human-in-the-loop approval and quality control"],"estimated_setup_minutes":45,"required_services":["n8n","OpenAI (GPT-4) API","Google Sheets","Twitter / X (OAuth2)","Discord (for approvals)","Notion (optional, for brand brief)"],"key_features":["Loads brand brief from sub-workflow to guide tone","Generates tweet ideas and checks Google Sheets for duplicates","Writes and evaluates posts with a quality score (rewrites if score < 0.7)","Rewriter Agent that mimics your past content from Google Sheets","Sends final drafts to Discord for manual approval (human-in-the-loop)"],"target_audience":["Creators and influencers","Solopreneurs and founders","Social media managers and content marketers"]}


name: Query-to-Action Automation with Bright Data MCP & OpenAI GPT
author_name: Cyril Nicko Gaspar
author_username: cngaspar
categories: []
created_at: 2025-05-15T18:00:56.880Z
updated_at: 2025-05-15T18:00:56.880Z
url: https://n8n.io/workflows/4077
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-14 21:18:33
description:
  📌 AI Agent Template with Bright Data MCP Tool Integration

  This template obtains all the possible tools from Bright Data MCP, process this through chatbot, then run any tool based on the user's query

  ❓ Problem It Solves

  The problem that the MCP solves is the complexity and difficulty of traditional automation, where users need to have specific knowledge of APIs or interfaces to trigger backend processes. By allowing interaction through natural language, automatically classifying and routing queries, and managing context and memory effectively, MCP simplifies complex data operations, customer support, and workflow orchestration scenarios where inputs and responses change dynamically.

  🧰 Pre-requisites

  Before deploying this template, ensure you have:

  An active n8n instance (self-hosted or cloud).
  A valid OpenAI API key (or any AI models)
  Access to Bright Data MCP API with credentials.
  Basic familiarity with n8n workflows and nodes.

  ⚙️ Setup Instructions

  **Install the MCP Community Node in N8N

     In your N8N self-hosted instance, go to Settings → Community Nodes.
     Search and install n8n-nodes-mcp.

  Configure Credentials:

     Add your OpenAI API key or any AI mdeols to the relevant nodes. If you want other AI model, please replace all associated nodes of OpenAI in the workflow
     Set up Bright Data MCP client credentials in the installed community node (STDIO)
     Obtain your API in Bright Data and put it in Environment field in the credentials window. It should be written as API_Key=&lt;your api key from Bright Data&gt;

  🔄 Workflow Functionality (Summary)

  User message** triggers the workflow.
  AI Classifier** (OpenAI) interprets the intent and maps it to a tool from Bright Data MCP.
  If no match is found, the user is notified.
  If more information is needed, the AI requests it.
  Memory** preserves context for follow-up actions.
  The tool is executed, and results are returned contextually to the user.

  &gt; 🧠 Optional memory buffer and chat memory manager nodes keep conversations context-aware across multiple messages.

  🧩 Use Cases

  Data Scraping Automation**: Trigger scraping tasks via chat.
  Lead Generation Bots**: Use MCP tools to fetch, enrich, or validate data.
  Customer Support Agents**: Automatically classify and respond to queries with tool-backed answers.
  Internal Workflow Agents**: Let team members trigger backend jobs (e.g., reports, lookups) by chatting naturally.

  🛠️ Customization

  Tool Matching Logic**: Modify the AI classifier prompt and schema to suit different APIs or services.
  Memory Size and Retention**: Adjust memory buffer size and filtering to fit your app’s complexity.
  Tool Execution**: Extend the "Execute the tool" sub-workflow to handle additional actions, fallback strategies, or logging.
  Frontend Integration**: Connect this with various platforms (e.g., WhatsApp, Slack, web chatbots) using the webhook.

  ✅ Summary

  This template delivers a powerful no-code/low-code agent that turns chat into automation, combining AI intelligence with real-world tool execution. With minimal setup, you can build contextual, dynamic assistants that drive backend operations using natural language.

nodes_used:
  ["@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.chatTrigger","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.memoryBufferWindow","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.if","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.memoryManager","@n8n/n8n-nodes-langchain.memoryBufferWindow","n8n-nodes-base.if","n8n-nodes-base.set","n8n-nodes-base.stickyNote","n8n-nodes-base.executeWorkflowTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.set","n8n-nodes-mcp.mcpClient","n8n-nodes-mcp.mcpClient"]

workflow_json_compressed:
  [encoded data, 4384 characters]

metadata_json:
  {"categories":["automation","integration","AI agent","data processing","workflow orchestration"],"complexity":"medium","use_cases":["Data scraping automation triggered via chat","Lead generation and enrichment bots","Customer support agents that run backend tools","Internal workflow agents to trigger jobs/reports by natural language"],"estimated_setup_minutes":30,"required_services":["n8n instance (self-hosted or cloud)","OpenAI API or alternate AI model","Bright Data MCP API (n8n-nodes-mcp community node)"],"key_features":["Natural-language intent classification (OpenAI)","Automatic tool discovery and matching (Bright Data MCP)","Remote tool execution from chat","Context and memory management across conversations","Requests for missing info and graceful fallback when no tool matches\",\"No-code/low-code node-based workflow integration"],"target_audience":["Developers and automation engineers","Data analysts and growth/marketing teams","Customer support managers and teams implementing bots"]}


name: Convert Markdown Content to Contentful Rich Text with AI Formatting
author_name: Varritech
author_username: varritech
categories: []
created_at: 2025-05-15T18:02:32.245Z
updated_at: 2025-05-15T18:02:32.245Z
url: https://n8n.io/workflows/4078
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:32
description:
  Workflow: Publish to Contentful with Rich Text Formatting

  ⚡ About the Creators
  This workflow was created by Varritech Technologies, an innovative agency that leverages AI to engineer, design, and deliver software development projects 500% faster than traditional agencies. Based in New York City, we specialize in custom software development, web applications, and digital transformation solutions. If you need assistance implementing this workflow or have questions about content management solutions, please reach out to our team.

  🏗️ Architecture Overview  
  This workflow takes a JSON article payload, splits its markdown content into logical chunks, converts each chunk into Contentful Rich Text JSON via an AI agent, merges the resulting rich text nodes back into a single document, formats the entire entry according to Contentful's field schema, and finally publishes it to Contentful.

  Trigger → Executes when called by another workflow  
  Split by Headings → Breaks markdown into ##-delimited chunks  
  Markdown → Rich Text → AI agent converts each chunk to Contentful Rich Text JSON  
  Combine Rich Text Objects → Aggregates all chunk outputs into one document  
  Format Entry → Wraps metadata and rich-text content into Contentful schema  
  Publish Entry → HTTP POST to Contentful API  

  📦 Node-by-Node Breakdown

  flowchart LR
    A[When Executed by Another Workflow] --&gt; B[Split by Headings]
    B --&gt; C[Markdown to Contentful format]
    C --&gt; D[Combine Rich Text Objects]
    D --&gt; E[Merge1]
    E --&gt; F[Format1]
    F --&gt; G[Create newly formatted Contentful Entry]

  1. When Executed by Another Workflow
  Type: Execute Workflow Trigger

  Input Example:
  title, slug, category.id, description, keywords, content, metaTitle, metaDescription, readingTime, difficulty

  Purpose: Receives the JSON payload from the upstream workflow.

  2. Split by Headings
  Type: Code

  Logic:
  Splits input.content into an array of markdown chunks at each second-level heading (##).
  Emits one item per chunk with index, slug, title, and contentChunk.

  3. Markdown to Contentful format
  Type: LangChain Agent (+ OpenAI Chat model)

  System Prompt:
  Defines rules for generating valid Contentful Rich Text JSON (must include nodeType, data:{}, content:[], etc.).
  Provides examples for paragraphs, headings, lists, links, and images.

  User Prompt:

  Here is the markdown content to convert:

  Purpose: Converts each markdown chunk into an array of rich-text nodes.

  4. Combine Rich Text Objects
  Type: Code

  Logic:
  Parses and merges all content arrays returned by the AI agent into one combined content array under a document root.

  5. Merge1
  Type: Merge

  Purpose: Joins the original item (with metadata) and the combined rich-text document into a single data stream.

  6. Format1
  Type: Code

  Logic:
  Maps workflow data into the Contentful entry schema by setting each field (title, slug, category link, description, keywords, rich-text content, metaTitle, metaDescription, readingTime, difficulty) under the appropriate locale and structure required by Contentful.

  7. Create newly formatted Contentful Entry
  Type: HTTP Request

  Method: POST

  URL:
  https://api.contentful.com/spaces

  Headers:
  Authorization: Bearer token for Contentful Management API
  Content-Type: application/vnd.contentful.management.v1+json
  X-Contentful-Version: entry version number
  X-Contentful-Content-Type: content type ID

  Body: The formatted fields object produced by the previous node

  Purpose: Publishes the new entry with rich-text content to Contentful.

  🔍 Design Rationale & Best Practices
  Chunked Conversion
  Splitting by headings prevents AI context limits and keeps conversions modular.

  Strict Rich Text Schema
  Enforcing nodeType, data, and content structure avoids validation errors on Contentful.

  Two-Phase Merge
  Separating "combine AI outputs" and "format entry" keeps transformations clear and testable.

  Idempotent Publish
  Uses explicit versioning and content type headers to ensure correct entry creation.

nodes_used:
  ["n8n-nodes-base.httpRequest","n8n-nodes-base.executeWorkflowTrigger","n8n-nodes-base.merge","n8n-nodes-base.code","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.code","n8n-nodes-base.code","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 8072 characters]

metadata_json:
  {"categories":["content_management","integration","automation","ai_assisted"],"complexity":"complex","use_cases":["Convert Markdown to Contentful Rich Text","Automated CMS entry creation and publishing","Content migration into Contentful","AI-assisted content formatting and structuring","Mapping article metadata to Contentful schema"],"estimated_setup_minutes":45,"required_services":["Contentful Management API (space & content type)","OpenAI API (or compatible LLM) via LangChain/lmChatOpenAi","n8n workflow platform"],"key_features":["Splits markdown into ##-delimited chunks to avoid context limits","Uses an AI agent to convert each chunk into Contentful Rich Text JSON nodes","Merges chunk outputs into a single rich-text document","Maps metadata (title, slug, category, SEO fields, readingTime, difficulty) to Contentful field schema","Publishes entry to Contentful with proper headers/versioning to ensure idempotency"],"target_audience":["Developers integrating CMS workflows","Content engineers and publishers","Agencies automating content ingestion and formatting with AI"]}


name: Automate AI News Videos with GPT-4o, Heygen Avatars, and Blotato
author_name: David Olusola
author_username: dae221
categories: []
created_at: 2025-05-15T18:43:13.778Z
updated_at: 2025-05-15T18:43:13.778Z
url: https://n8n.io/workflows/4080
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:32
description:
  Turn your ideas into engaging videos, talking avatars, and scheduled posts — all on autopilot.

  🚀 How It Works: 3 Steps to AI-Generated Video Posts

  🤖 AI Researches & Creates Your Video Script

  Automatically fetches trending AI/LLM stories from Hacker News
  Generates a 30-second viral video script with:
  Attention-grabbing hook
  Balanced analysis with statistics
  Call-to-action ("Hit follow to stay ahead in AI!")
  Writes two caption versions:
  Long (50 words + hashtags)
  Short (2 sentences for platforms like Twitter/Threads)
  🎥 Heygen Generates the AI Avatar Video

  Uses your preferred Heygen avatar/voice (configure in "Setup Heygen")
  Applies a professional background video (included)
  Processes the video in ~8 minutes (wait time adjustable)
  📣 Auto-Publishes to 10+ Platforms via Blotato

  Uploads video to Blotato’s CDN
  Publishes natively to:
  ✅ Instagram | ✅ YouTube | ✅ TikTok | ✅ LinkedIn
  ✅ Twitter/X | ✅ Facebook | ✅ Threads (coming soon)
  Platform-specific optimizations:
  Instagram/YouTube: Long captions + hashtags
  Twitter/Threads: Short captions
  TikTok: Vertical video formatting
  ⏱️ Full Automation Timeline

  AI Research → Scriptwriting → Video Generation → Multi-Platform Publishing
  (Runs daily at 10 AM or your custom schedule)

  🛠️ Key Features

  No Manual Work: Fully hands-off after setup

  Customizable: Adjust AI prompts, avatars, or add platforms

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

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metadata_json:
  {"categories":["automation","content creation","social media","AI/video generation","integration"],"complexity":"complex","use_cases":["Automated daily AI/LLM news video production","Multi-platform social video publishing","Creating talking-avatar explainer videos from headlines","Automated caption generation and platform-specific formatting","Hands-off content pipelines for growth/engagement"],"estimated_setup_minutes":45,"required_services":["OpenAI (GPT-4o / lmChatOpenAi)","Heygen (avatar & video generation)","Blotato (CDN + native publishing)","Hacker News (trending stories data source)","Social platform accounts/APIs: Instagram, YouTube, TikTok, LinkedIn, Twitter/X, Facebook, Threads"],"key_features":["Automatically fetches trending AI/LLM stories and generates a 30-second viral script","Generates long and short captions optimized per platform","Uses Heygen avatars/voices and background video to produce talking-avatar clips","Uploads to Blotato CDN and publishes natively to multiple platforms","Platform-specific formatting (vertical for TikTok, long captions for IG/YouTube, short for X/Threads)"],"target_audience":["Social media managers","Content creators and influencers","Growth marketers and community managers"]}


name: Automate SEO Blog Creation + Social Media with GPT-4, Perplexity and WordPress
author_name: LukaszB
author_username: lukaszb
categories: []
created_at: 2025-05-15T18:59:00.587Z
updated_at: 2025-05-15T18:59:00.587Z
url: https://n8n.io/workflows/4082
scraped_at: 2025-09-14 19:11:00
metadata_generated_at: 2025-09-14 21:18:32
description:
  🚀 AI Blog & Social Media Publisher – Fully Automated Workflow

  This workflow is ideal for individuals, marketers, agencies, and brands who want to effortlessly automate the entire blogging and social media process—from idea generation to promotion. Its primary goal is to consistently deliver engaging, SEO-optimized blog posts directly to WordPress, accompanied by professionally crafted social media content ready for Instagram, Facebook, and X (Twitter).

  No writers, editors, designers, or social media managers required. Save countless hours and resources while boosting your brand's online presence.

  🔧 Workflow Capabilities:

  -Automated Blog Topic Generation: Instantly generates unique, high-value blog ideas tailored to your brand.
  -SEO Content Creation: Produces comprehensive, 2000–2500 word articles optimized for search engines.
  -Real-Time Research: Integrates Perplexity AI to ensure factually accurate, authoritative content.
  -Visual Content Generation: Creates custom, AI-generated featured images via GPT-4, with automatic fallback to Pexels.
  -WordPress Publishing: Automatically publishes articles directly to WordPress with complete formatting (HTML), meta descriptions, featured images, and proper categorization.
  -Social Media Automation: Generates and schedules engaging, platform-specific posts for Instagram, Facebook, and X, complete with relevant hashtags, calls-to-action, and links.
  -Detailed Logging & Reporting: Logs every step transparently into Google Sheets and optionally sends publication reports to Gmail.

  ⚙️ How It Works:
  When activated, the workflow checks your content calendar in Google Sheets to avoid duplicate topics. It generates fresh, brand-aligned blog ideas, conducts live research, and creates complete, ready-to-publish articles. It then automatically designs and sources appropriate visuals, publishes content seamlessly to WordPress, and prepares engaging social media posts optimized for each platform.

  🛠️ Easy Setup Steps:
  -Connect your APIs: OpenAI, WordPress, Google Sheets, Gmail, and optionally Pexels.
  -Replace placeholders (WordPress URLs, Google Sheets ID/tab, workflow IDs).
  -Customize AI prompts with your brand’s tone, keywords, and CTAs for personalized content.
  -Configure scheduling to automate daily, weekly, or custom publishing intervals.

  📌 Additional Features:
  -Modular workflow design for easy customization and scalability.
  -Comprehensive Markdown and PDF setup guides included.
  -Bonus: Reference placeholders and quick-edit Sticky Notes for effortless adjustments.

  Launch today. Automate permanently. Amplify your reach effortlessly.

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metadata_json:
  {"categories":["automation","content creation","SEO","social media","publishing"],"complexity":"complex","use_cases":["Fully automated long-form SEO blog production","End-to-end content publishing to WordPress","Platform-specific social media post generation and scheduling (Instagram, Facebook, X)","Automated visual (featured image) generation with fallback sourcing","Content calendar enforcement and duplicate-topic prevention using Google Sheets logging"],"estimated_setup_minutes":90,"required_services":["OpenAI (GPT-4)","Perplexity AI","WordPress (REST API / credentials)","Google Sheets (API access)","Gmail (optional, for reports)","Facebook Graph API (for Facebook/Instagram posting)","Pexels API (optional fallback for images)","n8n webhook/HTTP access (for integrations and scheduling)"],"key_features":["Automated topic ideation tailored to brand voice","Long-form SEO-optimized article generation (2000–2500 words)","Real-time research integration (Perplexity) to improve factual accuracy","AI-generated featured images with automatic Pexels fallback","Direct WordPress publishing with HTML formatting, meta descriptions and categorization"],"target_audience":["Marketers","Agencies","Brands and content teams (in-house marketers, editors and managers)"]}


name: AI Sales Agent: WhatsApp, FB, IG, OpenAI, Airtable, Supabase Auto-Booking
author_name: Sam Yassine
author_username: samyassine
categories: []
created_at: 2025-05-15T19:39:14.260Z
updated_at: 2025-05-15T19:39:14.260Z
url: https://n8n.io/workflows/4083
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:31
description:
  This workflow automates multi-channel AI-driven sales engagement for lead qualification, service information delivery, and consultation booking. It integrates WhatsApp, Facebook Messenger, Instagram DM, and an n8n chat interface with a backend CRM (Airtable), a knowledge base (Supabase), and conversational AI (OpenAI), all orchestrated by n8n.

  Tools & Services Used

  Messaging Platforms: WhatsApp, Facebook Messenger, Instagram DM, n8n Built-in Chat

  AI Core & Processing: OpenAI (GPT-4o for main agent logic, Whisper for audio transcription)

  CRM & Data Management: Airtable (for initial WhatsApp lead lookup, lead form submissions, and as the backend for the crmAgent sub-workflow operations)

  Knowledge Base: Supabase (Vector Store for technical_and_sales_knowledge tool)

  Chat Memory: PostgreSQL (for the main AI Agent's conversation history)

  Orchestration & Automation: n8n (Self-hosted, utilizing Langchain community nodes)

  Calendar Service: Integrated via the calendarAgent sub-workflow

  CRM Service: Integrated via the crmAgent sub-workflow (interacting with Airtable)

  Workflow Overview

  This automation performs the following steps:

  Trigger: A new interaction is initiated through one of the following channels:

  A new message is received via the WhatsApp Trigger.

  A new message is received via the Facebook Trigger (Webhook).

  A new message is received via the Instagram Trigger (Webhook).

  A new message is received via the n8n Chat Trigger.

  Alternatively, a new lead is submitted via the Airtable Form Submitted Webhook.

  Channel-Specific Ingestion & Pre-processing:

  For WhatsApp:

  The system attempts to find an existing lead in Airtable using the sender's phone number.

  Incoming messages are routed by the Handle Message Types switch:

  Text messages are passed to the Edit Fields - chat1 node to prepare input for the AI Agent, including any found lead information.

  Audio messages are processed: the WhatsApp Business Cloud node gets the media URL, the HTTP Request node downloads the audio, OpenAI transcribes it to text, and Edit Fields - chat2 prepares this transcribed text and lead information for the AI Agent.

  Unsupported message types trigger the Reply To User1 node to send a notification that the message type cannot be processed.

  For Facebook Messenger:

  The system responds to webhook verification (Respond to Webhook - facebook get) and acknowledges new messages (Respond to Webhook - facebook post).

  The If is not echo - facebook node filters out messages sent by the page.

  The Sales Agent Demo - typing_on node sends a typing indicator.

  The Edit Fields - facebook node prepares the message text, sender ID, and Facebook-specific context for the AI Agent.

  For Instagram DM:

  The system responds to webhook verification (Respond to Webhook - instagram get) and acknowledges new messages (Respond to Webhook - instagram post).

  The If is not echo - instagram node filters out messages sent by the business account.

  The Edit Fields - instagram node prepares the message text, sender ID, and Instagram-specific context for the AI Agent.

  For n8n Chat:

  The Edit Fields - chat node prepares the user's input and session information for the AI Agent.

  Input Aggregation for AI Agent:

  Processed data from all active messaging channels (WhatsApp text/audio, Facebook, Instagram, n8n Chat) is funneled through the No Operation, do nothing node to the main AI Agent.

  AI Sales Conversation & Tool Utilization:

  The AI Agent (using OpenAI Chat Model - GPT-4o, and Postgres Chat Memory) engages the user according to its system prompt, aiming to qualify them for Paint Protection Film (PPF), Ceramic Coating, or Window Tint.

  The AI Agent uses the technical_and_sales_knowledge tool (which queries the Demo Supabase vector store via Embeddings OpenAI and OpenAI Chat Model1) to provide service details and answer questions.

  The AI Agent uses the crmAgent tool (a sub-workflow) to log contact details (Name, Email, service interest) and update opportunity statuses in Airtable.

  The AI Agent uses the calendarAgent tool (a sub-workflow) to book consultation appointments once preferred dates/times are provided. This occurs after contact details are logged in the CRM.

  Response Delivery:

  The AI Agent's final textual response is passed to the Switch node.

  The Switch node routes the response to the appropriate node for delivery on the original channel:

  Reply To User for WhatsApp.

  Facebook Graph API - Sales Agent Demo for Facebook Messenger.

  Instagram Graph API - smb.sales.agent.demo for Instagram DM.

  Output - chat for the n8n Chat interface.

  Airtable Form Submission Processing (Separate Branch):

  When the Airtable Form Submitted webhook receives data, the Airtable node fetches the full record.

  The Create Contact node creates a new contact in the Airtable 'Contacts' table.

  The Edit Fields - form node prepares data for a notification.

  The WhatsApp Business Cloud2 node sends a templated WhatsApp message to the lead, confirming their form submission.

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metadata_json:
  {"categories":["automation","integration","conversational AI","sales & CRM"],"complexity":"complex","use_cases":["Multi‑channel lead qualification (WhatsApp, FB, IG, n8n Chat)","Automated consultation booking and calendar integration","CRM contact creation and opportunity updates","Technical & sales knowledge lookup via vector search","Audio message transcription to text for AI processing"],"estimated_setup_minutes":180,"required_services":["WhatsApp Business Cloud","Facebook Messenger / Instagram Graph API","n8n (self‑hosted)","OpenAI (GPT-4o for chat, Whisper for transcription, Embeddings)","Airtable (CRM / form webhook)","Supabase (vector store / knowledge base)","PostgreSQL (chat memory)","Calendar service (Google Calendar or other via calendarAgent sub-workflow)","HTTP/Webhook endpoints"],"key_features":["Unified multi‑channel ingestion (WhatsApp, FB, IG, n8n Chat)","Audio download + Whisper transcription pipeline","AI sales agent using GPT-4o with chat memory","Vector search knowledge tool (Supabase + OpenAI embeddings)","CRM tooling via Airtable sub-workflow for contact & opportunity management','Automated appointment booking via calendarAgent sub-workflow'"],"target_audience":["Small/medium businesses and service providers (consultations/appointments)","Sales teams and SDRs automating qualification","Marketing/ops teams wanting multi-channel outreach automation','Developers / automation engineers implementing conversational AI workflows"]}


name: Automatically Store Shopify Orders in Google Sheets with Telegram Notifications
author_name: RedOne
author_username: redone
categories: []
created_at: 2025-05-15T20:17:14.891Z
updated_at: 2025-05-15T20:17:14.891Z
url: https://n8n.io/workflows/4084
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-14 21:18:33
description:
  This workflow is designed for e-commerce store owners, operations managers, and developers who use Shopify as their e-commerce platform and want an automated way to track and analyze their order data.

  It is particularly useful for businesses that:

  Need a centralized view of all Shopify orders
  Want to analyze order trends without logging into Shopify
  Need to share order data with team members who don't have Shopify access
  Want to build custom reports based on order information

  What Problem Is This Workflow Solving?

  While Shopify provides excellent order management within its platform, many businesses need their order data available in other systems for various purposes:

  Data accessibility**: Not everyone in your organization may have access to Shopify's admin interface
  Custom reporting**: Google Sheets allows for flexible analysis and report creation
  Data integration**: Having orders in Google Sheets makes it easier to combine with other business data
  Backup**: Creates an additional backup of your critical order information

  What This Workflow Does

  This n8n workflow creates an automated bridge between your Shopify store and Google Sheets:

  Listens for new order notifications from your Shopify store via webhooks
  Processes the incoming order data and transforms it into a structured format
  Stores each new order in a dedicated Google Sheets spreadsheet
  Sends real-time notifications to Telegram when new orders are received or errors occur

  Setup

  Create a Google Sheet

  Create a new Google Sheet to store your orders
  Add a sheet named "orders" with the following columns:

    orderId
    orderNumber
    created_at
    processed
    processed_at
    json
    customer
    shippingAddress
    lineItems
    totalPrice
    currency

  Set Up Telegram Bot

  Create a Telegram bot using BotFather (send /newbot to @BotFather)
  Save your bot token for use in n8n credentials
  Start a chat with your bot and get your chat ID (you can use @userinfobot)

  Configure the Workflow

  Set your Google Sheet ID in the "Edit Variables" node
  Enter your Telegram chat ID in the "Edit Variables" node
  Set up your Telegram API credentials in n8n

  Configure Shopify Webhook

  In your Shopify admin, go to:
    Settings > Notifications > Webhooks
  Create a new webhook for "Order creation"
  Set the URL to your n8n webhook URL (from the "Receive New Shopify Order" node)
  Set the format to JSON

  How to Customize This Workflow to Your Needs

  Additional data**: Modify the "Transform Order Data to Standard Format" function to extract more Shopify data
  Multiple sheets**: Duplicate the Google Sheets node to store different aspects of orders in separate sheets
  Telegram messages**: Customize the text in Telegram nodes to include more details or rich formatting
  Data processing**: Add nodes to perform calculations or transformations on order data
  Additional notifications**: Add more channels like Slack, Discord, or SMS
  Integrations**: Extend the workflow to send order data to other systems like CRMs, ERPs, or accounting software

  Final Notes

  This workflow serves as a foundation that you can build upon to create a comprehensive order management system tailored to your specific business needs.

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.webhook","n8n-nodes-base.function","n8n-nodes-base.googleSheets","n8n-nodes-base.if","n8n-nodes-base.telegram","n8n-nodes-base.stickyNote","n8n-nodes-base.telegram","n8n-nodes-base.set"]

workflow_json_compressed:
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metadata_json:
  {"categories":["automation","integration","data processing","e-commerce","notifications"],"complexity":"medium","use_cases":["Centralize Shopify orders in Google Sheets for analysis","Real-time order alerts via Telegram","Share order data with team members who lack Shopify access","Create backups of order data","Enable custom reporting and downstream integrations"],"estimated_setup_minutes":20,"required_services":["Shopify (webhooks)","Google Sheets / Google account","Telegram (Bot via BotFather)","n8n instance with public webhook endpoint"],"key_features":["Listen for Shopify order creation via webhook","Transform raw order JSON into structured rows","Append orders to a dedicated Google Sheets sheet","Send Telegram notifications for new orders and errors","Configurable variables for Sheet ID and Telegram chat ID"],"target_audience":["e-commerce store owners","operations managers","developers implementing automations\",\"data analysts"]}


name: AI Agent To Chat With Files In Supabase Storage and Google Drive
author_name: Mark Shcherbakov
author_username: lowcodingdev
categories: []
created_at: 2025-05-15T20:44:33.064Z
updated_at: 2025-05-15T20:44:33.064Z
url: https://n8n.io/workflows/4086
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:31
description:
  Video Guide

  I prepared a detailed guide that illustrates the entire process of building an AI agent using Supabase and Google Drive within N8N workflows.



  Youtube Link

  Who is this for?
  This workflow is designed for developers, data scientists, and business users who wish to automate document management and enable AI-powered interactions over their stored files. It's especially beneficial for scenarios where users need to process, analyze, and retrieve information from uploaded documents rapidly.

  What problem does this workflow solve?
  Managing files across multiple platforms often involves tedious manual processes. This workflow facilitates automated file handling, making it easier for users to upload, parse, and interact with documents through an AI agent. It reduces redundancy and enhances the efficiency of data retrieval and management tasks.

  What this workflow does
  This workflow integrates Supabase storage with Google Drive and employs an AI agent to manage files effectively. The agent can:
  Upload files to Supabase storage and activate processes based on file changes in Google Drive.
  Retrieve and parse documents, converting them into a structured format for easy querying.
  Utilize an AI agent to answer user queries based on saved document data.

  Data Collection: The workflow initially gathers files from Supabase storage, ensuring no duplicates are processed in the 'files' table.
  File Handling: It processes files to be parsed based on their type, leveraging LlamaParse for effective data transformation.
  Google Drive Integration: The workflow monitors a designated Google Drive folder to upload files automatically and refresh document records in the database with new data.
  AI Interaction: A webhook is established to enable the AI agent to converse with users, facilitating queries and leveraging stored document knowledge.

  Setup

  Supabase Storage Setup:
     Create a private bucket in Supabase storage, modifying the default name in the URL.
     Upload your files using the provided upload options.

  Database Configuration:
     Establish the 'file' and 'document' tables in Supabase with the necessary fields.
     Execute any required SQL queries for enabling vector matching features.

  N8N Workflow Logic:
     Start with a manual trigger for the initial workflow segment or consider alternative triggers like webhooks.
     Replace all relevant credentials across nodes with your own to ensure seamless operation.

  File Processing and Google Drive Monitoring:
     Set up file processing to take care of downloading and parsing files based on their types.
     Create triggers to monitor the designated Google Drive folder for file uploads and updates.

  Integrate AI Agent:
     Configure the webhook for the AI agent to accept chat inputs while maintaining session context for enhanced user interactions.
     Utilize PostgreSQL to store user interactions and manage conversation states effectively.  

  Testing and Adjustments:
     Once everything is set up, run tests with the AI agent to validate its responses based on the documents in your database.
     Fine-tune the workflow and AI model as needed to achieve desired performance.

nodes_used:
  ["n8n-nodes-base.httpRequest","@n8n/n8n-nodes-langchain.documentDefaultDataLoader","@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter","@n8n/n8n-nodes-langchain.embeddingsOpenAi","n8n-nodes-base.supabase","n8n-nodes-base.if","n8n-nodes-base.supabase","n8n-nodes-base.httpRequest","n8n-nodes-base.splitInBatches","n8n-nodes-base.manualTrigger","n8n-nodes-base.aggregate","@n8n/n8n-nodes-langchain.chatTrigger","@n8n/n8n-nodes-langchain.vectorStoreSupabase","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/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenAi","@n8n/n8n-nodes-langchain.memoryBufferWindow","@n8n/n8n-nodes-langchain.embeddingsOpenAi","@n8n/n8n-nodes-langchain.vectorStoreSupabase","n8n-nodes-base.googleDriveTrigger","n8n-nodes-base.googleDrive","n8n-nodes-base.googleDriveTrigger","n8n-nodes-base.supabase","n8n-nodes-base.set","n8n-nodes-base.supabase","@n8n/n8n-nodes-langchain.documentDefaultDataLoader","@n8n/n8n-nodes-langchain.embeddingsOpenAi","@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter","@n8n/n8n-nodes-langchain.vectorStoreSupabase","n8n-nodes-base.stickyNote","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.wait","n8n-nodes-base.switch","n8n-nodes-base.stopAndError","n8n-nodes-base.httpRequest","n8n-nodes-base.stickyNote","n8n-nodes-base.merge","n8n-nodes-base.if","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.merge","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.wait","n8n-nodes-base.switch","n8n-nodes-base.stopAndError","n8n-nodes-base.httpRequest","n8n-nodes-base.stickyNote","n8n-nodes-base.set","n8n-nodes-base.webhook","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
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metadata_json:
  {"categories":["automation","integration","data processing","AI/ML"],"complexity":"complex","use_cases":["Automated multi-source document ingestion and syncing","AI-powered Q&A over stored documents","Document parsing and structured data extraction","Deduplication and database-backed file management","Vector search and semantic retrieval using embeddings"],"estimated_setup_minutes":90,"required_services":["n8n (workflow runner)","Supabase (storage + PostgreSQL)","Google Drive (Google account + API access)","OpenAI (embeddings/LLM)","LlamaParse (document parsing)","Public webhook endpoint (n8n cloud, ngrok, or similar)"],"key_features":["Monitor Google Drive folder and auto-upload files to Supabase","Avoid duplicate processing via file/database checks","Parse documents by type and convert to structured records","Store documents and embeddings in Supabase vector store","Semantic search/QA using embeddings and an AI agent/webhook chat interface with session context management (PostgreSQL)"],"target_audience":["Developers","Data scientists","Business users/product managers who need document search and automation workflows"]}


name: AI Content Creation and Publishing Engine with Mistral, Creatomate, and YouTube
author_name: NanaB
author_username: nanabrown
categories: []
created_at: 2025-05-15T22:06:26.894Z
updated_at: 2025-05-15T22:06:26.894Z
url: https://n8n.io/workflows/4087
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:32
description:
  Description

  This n8n workflow automates the entire process of creating and publishing AI-generated videos, triggered by a simple message from a Telegram bot (YTAdmin). It transforms a text prompt into a structured video with scenes, visuals, and voiceover, stores assets in MongoDB, renders the final output using Creatomate, and uploads the video to YouTube. Throughout the process, YTAdmin receives real-time updates on the workflow’s progress. This is ideal for content creators, marketers, or businesses looking to scale video production using automation and AI.

  You can see a video demonstrating this template in action here: https://www.youtube.com/watch?v=EjI-ChpJ4xA&t=200s 

  How it Works

  Trigger: Message from YTAdmin (Telegram Bot)

  The flow starts when YTAdmin sends a content prompt.

  Generate Structured Content

  A Mistral language model processes the input and outputs structured content, typically broken into scenes.

  Split & Process Content into Scenes

  The content is split into categorized parts for scene generation.

  Generate Media Assets

  For each scene:

  Images: Generated using OpenAI’s image model.
  Voiceovers: Created using OpenAI’s text-to-speech.
  Audio files are encoded and stored in MongoDB.

  Scene Composition

  Assets are grouped into coherent scenes.

  Render with Creatomate

  A complete payload is generated and sent to the Creatomate rendering API to produce the video.
  Progress messages are sent to YTAdmin.
  The flow pauses briefly to avoid rate limits.

  Render Callback

  Once Creatomate completes rendering, it sends a callback to the flow.
  If the render fails, an error message is sent to YTAdmin.
  If the render succeeds, the flow proceeds to post-processing.

  Generate Title & Description

  A second Mistral prompt generates a compelling title and description for YouTube.

  Upload to YouTube

  The rendered video is retrieved from Creatomate.
  It’s uploaded to YouTube with the AI-generated metadata.

  Final Update

  A success message is sent to YTAdmin, confirming upload completion.

  Set Up Steps (Approx. 10–15 Minutes)Step 1: Set Up YTAdmin Bot

  Create a Telegram bot via BotFather and get your API token.
  Add this token in n8n's Telegram credentials and link to the "Receive Message from YTAdmin" trigger.

  Step 2: Connect Your AI Providers

  Mistral: Add your API key under HTTP Request or AI Model nodes.
  OpenAI: Create an account at platform.openai.com and obtain an API key. Use it for both image generation and voiceover synthesis.

  Step 3: Configure Audio File Storage with MongoDB via Custom API

  Receives the Base64 encoded audio data sent in the request body.
  Connects to the configured MongoDB instance (connection details are managed securely within the API- code below).
  Uses the MongoDB driver and GridFS to store the audio data.
  Returns the unique _id (ObjectId) of the stored file in GridFS as a response.
  This _id is crucial as it will be used in subsequent steps to generate the download URL for the audio file.
  My API code can be found here for reference: https://github.com/nanabrownsnr/YTAutomation.git

  Step 4: Set Up Creatomate

  Create a Creatomate account, define your video templates, and retrieve your API key.
  Configure the HTTP request node to match your Creatomate payload requirements.

  Step 5: Connect YouTube

  In n8n, add OAuth2 credentials for your YouTube account.
  Make sure your Google Cloud project has YouTube Data API enabled.

  Step 6: Deploy and Test

  Send a message to YTAdmin and monitor the flow in n8n.
  Verify that content is generated, media is created, and the final video is rendered and uploaded.

  Customization Options

  Change the AI Prompts

  Modify the generation prompts to adjust tone, voice, or content type (e.g., news recaps, product videos, educational summaries).

  Switch Messaging Platform

  Replace Telegram (YTAdmin) with Slack, Discord, or WhatsApp by swapping out the trigger and response nodes.

  Add Subtitles or Effects

  Integrate Whisper or another speech-to-text tool to generate subtitles.
  Add overlay or transition effects in the Creatomate video payload.

  Use Local File Storage Instead of MongoDB

  Swap out MongoDB upload http nodes with filesystem or S3-compatible storage.

  Repurpose for Other Platforms

  Swap YouTube upload with TikTok, Instagram, or Vimeo endpoints for broader publishing.

  **Need Help or Want to Customize This Workflow?
  If you'd like assistance setting this up or adapting it for a different use case, feel free to reach out to me at nanabrownsnr@gmail.com. I'm happy to help!**

nodes_used:
  ["@n8n/n8n-nodes-langchain.lmChatMistralCloud","n8n-nodes-base.httpRequest","n8n-nodes-base.youTube","@n8n/n8n-nodes-langchain.lmChatMistralCloud","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.set","n8n-nodes-base.if","n8n-nodes-base.telegram","n8n-nodes-base.telegram","n8n-nodes-base.telegramTrigger","@n8n/n8n-nodes-langchain.chainLlm","n8n-nodes-base.set","n8n-nodes-base.splitOut","@n8n/n8n-nodes-langchain.openAi","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.wait","n8n-nodes-base.extractFromFile","n8n-nodes-base.httpRequest","n8n-nodes-base.merge","n8n-nodes-base.aggregate","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.telegram","@n8n/n8n-nodes-langchain.chainLlm","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/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.httpRequest","n8n-nodes-base.webhook"]

workflow_json_compressed:
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metadata_json:
  {"categories":["automation","content-creation","video-production","AI/integration"],"complexity":"complex","use_cases":["Scale YouTube video production from a text prompt","Automated marketing or product videos","Educational or news summary video generation","Batch social/video content repurposing","Automated publishing and metadata generation"],"estimated_setup_minutes":15,"required_services":["Telegram (Bot/API)","Mistral (LM API)","OpenAI (images + TTS)","MongoDB with GridFS (or custom file storage API)","Creatomate (video rendering API)","YouTube Data API / Google OAuth"],"key_features":["End-to-end prompt → published YouTube video pipeline","Structured content generation (scene segmentation) via Mistral","Per-scene image generation and text-to-speech voiceover","Audio asset storage in MongoDB/GridFS","Creatomate rendering with callback handling and rate-limit pauses\n(plus error reporting and retries flow control)** (note: newline is literal in single feature string)**\nThis line is not desired; keep concise instead"],"target_audience":["Content creators & YouTubers","Marketers & agencies","Social media managers/growth teams"]}


name: Extract and Merge Twitter (X) Threads using TwitterAPI.io
author_name: enes cingoz
author_username: ecingoz
categories: []
created_at: 2025-05-15T22:37:55.997Z
updated_at: 2025-05-15T22:37:55.997Z
url: https://n8n.io/workflows/4088
scraped_at: 2025-09-14 19:11:00
metadata_generated_at: 2025-09-14 21:18:32
description:
  Twitter (X) Thread Fetcher: Extract and Merge Tweets from Threads
  What it does

  Thread Detection:** Automatically detects whether the provided Twitter link is a single tweet or a thread.
  Tweet Extraction:** Fetches and returns the content of a single tweet, or gathers all tweets in a thread by retrieving the first tweet and all connected replies.
  Thread Merging:** Merges all tweets in the correct order to reconstruct the complete thread, filtering out any empty results.
  Seamless Integration:** Easily trigger this workflow from other n8n workflows to automate Twitter thread extraction from various sources.

  How it works
  Accepts a Twitter link as input-either a single tweet or a thread.
  If the link is for a single tweet, fetches and returns the tweet content.
  If the link is for a thread, fetches the first tweet, then iteratively retrieves all connected replies that form the thread, ensuring only relevant tweets are included.
  Merges the first tweet and all subsequent thread tweets in order, filters out any empty results, and returns the complete thread.
  Uses twitterapi.io for all Twitter API requests.

  Set up steps
  Setup typically takes just a few minutes. You’ll need to configure your Twitter API credentials for twitterapi.io.
  You can trigger this workflow manually for testing or call it from another workflow to automate thread fetching from sources like Notion, spreadsheets, or other platforms.
  For best results, create a separate workflow to gather Twitter links from your preferred source, then trigger this workflow to fetch and return the full thread.

  &gt; Detailed configuration instructions and node explanations are included as sticky notes within the workflow canvas.

  Benefits

  Light speed:* Fetches a 15-tweet thread in just *3 seconds** for rapid results.
  Cost effective:* Processes a *15-tweet thread* for only *$0.0027*, making it highly affordable. *(Cost may vary depending on the density of replies in the thread.)

nodes_used:
  ["n8n-nodes-base.merge","n8n-nodes-base.manualTrigger","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.executeWorkflowTrigger","n8n-nodes-base.noOp","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.function","n8n-nodes-base.httpRequest","n8n-nodes-base.function","n8n-nodes-base.merge","n8n-nodes-base.httpRequest","n8n-nodes-base.code","n8n-nodes-base.filter"]

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metadata_json:
  {"categories":["integration","automation","social media","data extraction"],"complexity":"medium","use_cases":["Fetch and reconstruct Twitter (X) threads for archiving or republishing","Automate content collection for social media management or newsletters","Feed full thread content into downstream workflows for summarization or analysis","Monitor and extract threaded conversations for research or compliance"],"estimated_setup_minutes":10,"required_services":["twitterapi.io (Twitter API access)","Valid Twitter API credentials (via twitterapi.io)","n8n (workflow automation platform)"],"key_features":["Auto-detects whether a link is a single tweet or a thread","Iteratively fetches first tweet and connected replies to reconstruct threads","Merges tweets in correct order and filters out empty results","Callable from other n8n workflows or run manually","Efficient performance and low per-thread cost"],"target_audience":["developers/automation engineers","social media managers and marketers","content creators and curators"]}


name: Track SEO Keyword Rankings in Google Search with ScrapingBee API
author_name: Gegenfeld
author_username: gegenfeld
categories: []
created_at: 2025-05-15T23:42:27.189Z
updated_at: 2025-05-15T23:42:27.189Z
url: https://n8n.io/workflows/4089
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-14 21:18:33
description:
  Who is this template for?

  This SEO Reporting workflow template is ideal for digital marketers, SEO consultants, content strategists, and founders who need to quickly gather, format, and store Google search result data. If you regularly audit SERPs, track keyword performance, or monitor competitors, this automation lets you generate polished SEO reports in seconds—ready to share or analyze further.

  What problem does this workflow solve?

  Scraping and formatting Google search results for SEO insights is often manual, repetitive, and error-prone or requires expensive software. Professionals frequently face challenges like:

  Collecting live, structured data from Google for multiple keywords
  Converting raw search results into readable reports for clients or stakeholders
  Logging changes in rankings or URLs across time for historical tracking
  Exporting SEO data into spreadsheets for deeper analysis
  High monthly software fees

  What this workflow does

  This n8n workflow scrapes the top organic Google search results for a given keyword and automatically creates a downloadable report while also logging the results in a table format for long-term storage or further processing.

  Here’s what it includes:

  A trigger form that accepts a search keyword from the user
  An automated API call to fetch Google’s SERP data
  Two output formats: a formatted HTML table for emails and a Markdown table for download (e.g., for Excel, Airtable or Google Sheets)
  Automatic CSV file generation for download
  Optional email delivery of the report

  Setup

  Getting started is simple:

  Enter your API key

     Add your API key to the “Scrape Google SERPs” HTTP Request node (Step-by-step guide inside the template)
     Replace the default query with your own custom Google search parameters if needed

  Set up delivery options

     Update your email in the “Mail SEO Report” node for report delivery
     Use the downloadable file output from the “Convert to File” node
     Optional: Add a Google Sheets (or similar) node which imports the file

  Test the workflow

     Use the built-in form to input a keyword
     Confirm that results appear in both your email and downloadable file

  Activate the workflow

     Turn on the trigger so your team or clients can submit keywords at any time

  How to customize this workflow

  This template is easy to extend for a variety of SEO automation needs:

  Add a loop to handle multiple keywords at once
  Connect to Airtable, Notion or Google Sheets
  Integrate with Slack or Discord for notifications
  Apply additional filtering to track only new or changed search results
  Schedule it to run daily or weekly with a cron trigger

  By combining live SERP scraping, report formatting, and spreadsheet integration, this workflow gives you a fast and flexible SEO reporting system you can use right away or scale up as needed.

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.httpRequest","n8n-nodes-base.formTrigger","n8n-nodes-base.code","n8n-nodes-base.stickyNote","n8n-nodes-base.convertToFile","n8n-nodes-base.mailjet","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["automation","data processing","integration","reporting","SEO"],"complexity":"medium","use_cases":["Track keyword rankings in Google SERPs","Generate SEO reports (HTML, Markdown, CSV)","Monitor competitor search results","Log historical ranking changes for analysis","Export results to spreadsheets (Google Sheets, Airtable, Excel)"],"estimated_setup_minutes":15,"required_services":["ScrapingBee API (required)","SMTP / Email provider (for optional email delivery)","Google Sheets, Airtable or other spreadsheet service (optional)","Slack or Discord (optional notifications)"],"key_features":["User trigger form to input keywords","Automated HTTP request to scrape Google SERPs","Outputs as formatted HTML table and Markdown table","CSV file generation for download","Optional email delivery of reports and integrations with sheets/DBs for logging"],"target_audience":["Digital marketers","SEO consultants","Content strategists and writers doing SEO audits/monitoring staff/founders"]}


name: Auto Workflow Backup to Google Drive – Automated Export of All Your Workflows
author_name: LukaszB
author_username: lukaszb
categories: []
created_at: 2025-05-16T01:52:32.526Z
updated_at: 2025-05-16T01:52:32.526Z
url: https://n8n.io/workflows/4090
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:32
description:
  n8n Workflow Backup to Google Drive – Automated Export of All Your Workflows

  This workflow is designed to automatically create backups of all your workflows in n8n and store them as individual .json files in Google Drive. It's a fully automated system that helps developers, agencies, or automation teams ensure their automation logic is always safe, versioned, and ready to restore or share.

  What is this for?
  If you’re building and managing multiple automations inside n8n, losing a workflow due to accidental deletion or misconfiguration can cost you hours of work. This template solves that by exporting all your workflows into separate files and storing them in a dated Google Drive folder. It helps with disaster recovery, version tracking, and team collaboration — without any manual exporting.

  How this works:
  -Once triggered (manually or via a schedule), the workflow performs the following steps:
  -Creates a new folder in your Google Drive, named with today’s date (e.g. “Workflow Backups Monday 16-05-2025”).
  -Connects to your n8n instance using the internal API and retrieves a list of all existing workflows.
  -Iterates over each workflow, converts it into a .json file using the built-in file conversion node.
  -Uploads each individual .json file to the newly created folder in Google Drive.
  -Optionally, the workflow finds and deletes old backup folders to keep your Google Drive clean and avoid clutter.

  You get a clean, timestamped folder with all your flows — ready to restore, send, or store securely.
  You can trigger it manually or schedule it (e.g., to run weekly on Monday mornings).

  How to set it up:
  Import the provided workflow JSON into your n8n instance.
  Set up your credentials:
  -Replace the placeholder “Google demo” with your actual Google Drive OAuth2 credentials in all Google Drive nodes.
  -Replace the placeholder “n8n demo” with your n8n API credentials so the workflow can fetch your flows.
  -Go to the node “Create new folder” and replace the folder ID with your own destination folder in Google Drive where backups should be stored.
  -(Optional) Enable the “Schedule Trigger” to run the backup automatically once a week or on your preferred interval.

  You’re ready to go — test it with the Manual Trigger first and check your Google Drive for results.

nodes_used:
  ["n8n-nodes-base.convertToFile","n8n-nodes-base.scheduleTrigger","n8n-nodes-base.filter","n8n-nodes-base.googleDrive","n8n-nodes-base.googleDrive","n8n-nodes-base.manualTrigger","n8n-nodes-base.googleDrive","n8n-nodes-base.splitInBatches","n8n-nodes-base.googleDrive","n8n-nodes-base.limit","n8n-nodes-base.n8n","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["automation","integration","backup"],"complexity":"medium","use_cases":["Automated backups of n8n workflows","Disaster recovery and restore","Version tracking of workflows","Team collaboration and sharing of workflows","Scheduled exports for compliance or archival"],"estimated_setup_minutes":15,"required_services":["Google Drive (OAuth2 credentials)","n8n instance with internal API access"],"key_features":["Creates a dated Google Drive folder for each run","Exports each workflow as an individual .json file","Converts workflows to files and uploads them to Drive","Optional cleanup of old backup folders","Supports manual trigger and scheduled runs"],"target_audience":["Developers","Automation teams","Agencies managing n8n workflows, consultants"]}


name: Tesla Quant Trading AI Agent using Telegram + GPT-4.1 (Main InterFace)
author_name: Don Jayamaha Jr
author_username: don-the-gem-dealer
categories: []
created_at: 2025-05-16T08:44:07.297Z
updated_at: 2025-05-16T08:44:07.297Z
url: https://n8n.io/workflows/4092
scraped_at: 2025-09-14 19:11:00
metadata_generated_at: 2025-09-14 21:18:32
description:
  📈 Get daily and on-demand Tesla (TSLA) trading signals via Telegram—powered by GPT-4.1 and real-time market data.
  This is the central AI supervisor that orchestrates seven sub-agents for technical analysis, price pattern recognition, and news sentiment. Reports are delivered in structured Telegram-ready HTML, optimized for traders seeking fast, intelligent decision-making signals.

  ⚠️ This master agent requires 7 connected sub-workflows to function. One of them, the News & Sentiment Agent, also requires a DeepSeek Chat API key for language processing.

  🔌 Required Sub-Workflows

  You must download and publish the following workflows:

  Tesla Financial Market Data Analyst Tool
  Tesla News and Sentiment Analyst Tool (Requires DeepSeek Chat API Key)
  Tesla 15min Indicators Tool
  Tesla 1hour Indicators Tool
  Tesla 1day Indicators Tool
  Tesla 1hour & 1day Klines Tool
  Tesla Quant Technical Indicators Webhooks Tool (Requires Alpha Vantage Premium API Key)

  📍 See all tools at:
  🔗 https://n8n.io/creators/don-the-gem-dealer/

  🔍 What This Agent Does

  Listens to your trading query via Telegram
  Calls the Financial Analyst and News & Sentiment Analyst
  These agents aggregate:

     RSI, MACD, BBANDS, SMA, EMA, ADX
     Candlestick pattern + volume divergence analysis
     News summaries and sentiment scoring via DeepSeek Chat
  GPT-4.1 composes the final structured TSLA trade report with:

     Spot and leverage setups
     Signal rationale
     Confidence score
     Sentiment tag
     News summary

  🧠 Output Example

  TSLA Trading Report (Daily Summary)
  Spot Trade
  • Action: Buy
  • Entry: 172.45
  • TP: 182.00
  • SL: 169.80
  • Signal: RSI bounce + Bullish Engulfing
  • Sentiment: Neutral

  Leveraged Position
  • Position: Long
  • Leverage: 3x
  • TP: 186
  • SL: 170
  • Confidence: High (83/100)

  📰 Top News
  • Tesla Model Y delivery surge – Electrek
  • Options market pricing in upside – Bloomberg
  • FSD delayed in Canada – TeslaNorth

  🛠️ Setup Instructions

  1. Import All 8 Workflows

  Ensure all sub-agents above are published in your n8n instance.

  2. Create Your Telegram Bot

  Use @BotFather to generate the token and connect to the trigger/send nodes.

  3. Connect OpenAI GPT-4.1

  Add your OpenAI credentials for GPT-4.1 in the designated node.

  4. Add DeepSeek Chat API Key

  Sign up at https://deepseek.com and insert your DeepSeek Chat credentials in the News Agent.

  5. Add Alpha Vantage Premium API Key

  Sign up at https://www.alphavantage.co/premium/
  Use HTTP Header Auth for webhook-based indicator fetchers.

  6. Replace Telegram ID

  Update the placeholder &lt;&lt;replace your ID here&gt;&gt; with your actual Telegram numeric ID in the auth node.

  📌 Included Sticky Notes

  ✅ Telegram Bot Setup
  ✅ Agent Routing & Memory
  ✅ Financial vs. Sentiment Trigger Flow
  ✅ Report Formatting (HTML)
  ✅ API Requirements (GPT-4.1, DeepSeek, Alpha Vantage)
  ✅ Troubleshooting & Licensing

  🧾 Licensing & Attribution

  © 2025 Treasurium Capital Limited Company
  Architecture, prompts, and trade report structure are IP-protected. No unauthorized rebranding permitted.

  🔗 For support: LinkedIn – Don Jayamaha

  🚀 Deploy the Tesla Quant Trading AI system with GPT-4.1, DeepSeek Chat, and Alpha Vantage Premium—right into Telegram.
  All 8 workflows are required.

  🎥 Tesla Quant AI Agent – Live Demo

  Experience the power of the Tesla Quant Trading AI Agent in action.
    

nodes_used:
  ["n8n-nodes-base.telegramTrigger","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.telegram","n8n-nodes-base.code","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.toolWorkflow","@n8n/n8n-nodes-langchain.toolWorkflow","n8n-nodes-base.set","n8n-nodes-base.code","n8n-nodes-base.dateTime","@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.stickyNote","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["automation","financial trading","AI integration","data integration"],"complexity":"complex","use_cases":["Daily and on-demand TSLA trading signal generation","Multi-agent technical analysis aggregation (indicators + patterns)","News summarization and sentiment scoring for trade context","Delivering structured trading reports via Telegram","Orchestrating webhook-based market indicator fetchers"],"estimated_setup_minutes":90,"required_services":["n8n instance with all 8 workflows published","OpenAI GPT-4.1 API key","DeepSeek Chat API key (for News & Sentiment Agent)","Alpha Vantage Premium API key (for technical indicator webhooks)","Telegram Bot API token and numeric chat ID"],"key_features":["Central AI master agent orchestrating seven sub-agents","Aggregates RSI, MACD, BBANDS, SMA, EMA, ADX and candlestick/volume pattern analysis","News summaries and sentiment scoring via DeepSeek Chat","Final report composition by GPT-4.1 into Telegram-ready HTML","Provides spot and leveraged trade setups, confidence scores and sentiment tags"],"target_audience":["quantitative traders","algo developers","trading analysts and researchers"]}


name: Tesla News and Sentiment Analyst Tool (Powered by DeepSeek Chat)
author_name: Don Jayamaha Jr
author_username: don-the-gem-dealer
categories: []
created_at: 2025-05-16T08:49:30.606Z
updated_at: 2025-05-16T08:49:30.606Z
url: https://n8n.io/workflows/4093
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:32
description:
  📰 This AI-powered agent performs real-time sentiment analysis on Tesla (TSLA) news to support trading decisions.
  It aggregates headlines from 5 trusted sources and uses DeepSeek Chat to classify sentiment and generate structured summaries. This tool is a critical sub-agent in the broader Tesla Quant Trading AI Agent system.

   ⚠️ Not standalone — this agent is designed to be executed by the Tesla Quant Trading AI Agent.
   ⚙️ Requires: DeepSeek Chat API Key

  🔌 Workflow Role

  This tool processes Tesla-related news and produces output like:

  {
    "sentiment": "bullish",
    "summary": "Tesla stock rallied today after strong delivery numbers and Cybertruck updates. Analysts remain optimistic.",
    "topHeadlines": [
      "Tesla beats Q2 delivery forecast – Yahoo Finance",
      "Cybertruck ramps up in Texas – Electrek",
      "Berlin Gigafactory expands battery production – CleanTechnica"
    ]
  }

  Its output feeds directly into the master trading agent’s final trade report.

  📰 News Sources Used

  This agent collects real-time headlines from:

  Google News (filtered by “Tesla” or “TSLA”)
  Yahoo Finance (TSLA-specific feed)
  Electrek (Tesla archive)
  CleanTechnica (Tesla sustainability news)
  TeslaNorth (app/product release updates)

  These five tools are always queried together to ensure market-wide signal coverage.

  🤖 What the Agent Does

  Pulls headlines from all 5 Tesla-specific RSS feeds
  Uses DeepSeek Chat to:

     Analyze narrative tone (bullish / bearish / neutral)
     Identify macro/financial drivers
     Generate a 2–3 sentence summary
     Return top 3–5 headlines
  Outputs structured JSON for downstream use

  🛠️ Setup Instructions

  1. Install & Name

  Import this file and name it: Tesla_News_and_Sentiment_Analyst_Tool

  2. Add DeepSeek API Credentials

  Go to: Credentials → Add New → DeepSeek API
  Save as: DeepSeek account

  3. Internet Access Required

  Ensure RSS feeds can fetch live headlines
  Works best with a cloud-hosted n8n instance or tunnel-enabled local install

  4. Must Be Triggered by Parent

  Triggered via Execute Workflow by the Tesla Quant Trading AI Agent
  Requires these inputs:

    message: optional query context
    sessionId: passed to maintain short-term memory across executions

  🧠 Agent Architecture

  | Node Name                          | Function                                         |
  | ---------------------------------- | ------------------------------------------------ |
  | DeepSeek Chat Model              | Performs AI-based sentiment analysis             |
  | Tesla News and Sentiment Analyst | Combines results, formats output in strict JSON  |
  | Simple Memory                    | Stores session-level context (short-term memory) |
  | 5x RSS nodes                     | Aggregate Tesla news from trusted media outlets  |

  📌 Sticky Notes Included

  🟢 Trigger from Parent Workflow – Executed only by main TSLA agent
  🟠 News Feeds Overview – Lists and explains each of the 5 feeds
  🧠 DeepSeek Chat Notes – Describes LLM behavior and parsing role
  🔵 Short-Term Memory – Buffers sentiment context during user session
  📘 Sentiment Analyst Agent – Summarizes key responsibilities

  📎 Licensing & Attribution

  © 2025 Treasurium Capital Limited Company
  This architecture, workflow structure, and prompt design are licensed for educational and operational use only. Commercial resale or rebranding prohibited without authorization.

  🔗 Creator: Don Jayamaha
  🔗 Templates: https://n8n.io/creators/don-the-gem-dealer/

  🚀 Power your TSLA trading with AI-driven sentiment—built with DeepSeek Chat and 5 trusted news sources.
  This tool is required by the Tesla Quant Trading AI Agent.

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metadata_json:
  {"categories":["integration","data processing","automation","financial analysis"],"complexity":"medium","use_cases":["Real-time news aggregation for Tesla (TSLA)","Sentiment analysis to inform trading decisions","Generating concise structured summaries for downstream agents","Feeding market-signal sub-agent within a quant trading system","Short-term session memory for contextual analysis"],"estimated_setup_minutes":15,"required_services":["DeepSeek Chat API (API key)","Google News (Tesla/TSLA RSS)","Yahoo Finance TSLA RSS","Electrek (Tesla archive RSS)","CleanTechnica (Tesla RSS)","TeslaNorth (product/release updates RSS)","n8n instance with internet access","Parent Tesla Quant Trading AI Agent (to trigger execution)"],"key_features":["Aggregates headlines from five Tesla-specific RSS feeds","Uses DeepSeek Chat to classify sentiment (bullish/neutral/bearish)","Identifies macro/financial drivers","Produces 2–3 sentence structured summaries","Returns top 3–5 headlines and strict JSON output for downstream use"],"target_audience":["Quant traders / trading teams","Algo trading engineers","Data analysts monitoring equity news flow (TSLA-focused)"]}


name: Tesla Financial Market Data Analyst Tool (Multi-Timeframe Technical AI Agent)
author_name: Don Jayamaha Jr
author_username: don-the-gem-dealer
categories: []
created_at: 2025-05-16T08:54:17.737Z
updated_at: 2025-05-16T08:54:17.737Z
url: https://n8n.io/workflows/4094
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:32
description:
  📊 This AI sub-agent aggregates Tesla (TSLA) trading signals across multiple timeframes using real-time technical indicators and candlestick behavior.
  It is a core component of the Tesla Quant Trading AI system. Powered by GPT-4.1, it consolidates 15-minute, 1-hour, and 1-day indicators, adds candlestick pattern data, and produces a unified JSON signal for downstream use by the master agent.

   ⚠️ This agent is not standalone. It is triggered by the Tesla Quant Trading AI Agent via Execute Workflow.
   🧠 Requires: 4 connected sub-agents and Alpha Vantage Premium API Key

  🔌 Required Sub-Workflows

  To use this workflow, you must install:

  Tesla 15min Indicators Tool
  Tesla 1hour Indicators Tool
  Tesla 1day Indicators Tool
  Tesla 1hour and 1day Klines Tool
  Tesla Quant Technical Indicators Webhooks Tool (provides Alpha Vantage data)

  🧠 What This Agent Does

  Fetches pre-cleaned 20-point JSON outputs from the 4 sub-agents listed above
  Analyzes each timeframe individually:

     15m: momentum and short-term setups
     1h: confirmation of emerging trends
     1d: macro positioning and trend alignment
     Klines: candlestick reversal patterns and volume divergence
  Generates a structured final signal in JSON with:

     Trading stance: Buy, Sell, Hold, or Cautious
     Confidence score (0.0–1.0)
     Multi-timeframe indicator breakdown
     Candlestick and volume divergence annotations

  📋 Sample Output

  {
    "summary": "TSLA momentum is weakening short-term. 1h MACD shows bearish crossover, RSI declining. 1d candles confirm potential reversal setup.",
    "signal": "Cautious Sell",
    "confidence": 0.81,
    "multiTimeframeInsights": {
      "15m": { "RSI": 68.3, "MACD": { "macd": 0.53, "signal": 0.61 }, ... },
      "1h": { "RSI": 65.0, "MACD": { "macd": -0.32, "signal": 0.11 }, ... },
      "1d": { "BBANDS": { ... }, ... },
      "candlestickPatterns": { "1h": "Doji", "1d": "Bearish Engulfing" },
      "volumeDivergence": { "1h": "Bearish", "1d": "Neutral" }
    }
  }

  🛠️ Setup Instructions

  Import this workflow into n8n

     Name it: Tesla_Financial_Market_Data_Analyst_Tool

  Add Required API Credentials

     Alpha Vantage Premium (via HTTP Query Auth)
     OpenAI GPT-4.1 for reasoning and synthesis

  Link Required Sub-Agents

     Connect the 4 tool workflows listed above to their respective Tool Workflow nodes
     Connect the webhook provider for data fetches

  Set Up as Sub-Agent

     This workflow must be triggered using Execute Workflow from the parent agent
     Pass in:

       message (optional context)
       sessionId (used for memory continuity)

  🧾 Sticky Notes Provided

  📘 Tesla Financial Market Data Analyst — Core logic overview
  📈 15m / 1h / 1d Tool Notes — Indicator lists + use cases
  🕯️ Klines Tool Note — Candlestick and volume divergence patterns
  🧠 GPT Reasoning Note — GPT-4.1 handles final synthesis
  🧩 Sub-Workflow Trigger — Proper integration with parent agent
  🧠 Memory Buffer — Maintains session context across evaluations

  🔒 Licensing & Support

  © 2025 Treasurium Capital Limited Company
  The logic, prompt design, and multi-agent architecture are proprietary and IP-protected.

  For support or collaboration inquiries:
  🔗 Don Jayamaha – LinkedIn
  🔗 n8n Creator Profile

  🚀 Unify your Tesla trading logic across timeframes—automated, AI-powered, and built for scalers and swing traders.

nodes_used:
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  {"categories":["integration","data processing","finance","automation"],"complexity":"complex","use_cases":["Multi-timeframe trading signal generation for TSLA","Automated consolidation of technical indicators across timeframes","Providing structured JSON signals to a master trading agent","Candlestick and volume divergence annotation for trade decisioning","Session-aware iterative analysis for swing/intraday strategies"],"estimated_setup_minutes":45,"required_services":["Alpha Vantage Premium API","OpenAI GPT-4.1","n8n sub-workflows: Tesla 15min Indicators Tool, Tesla 1hour Indicators Tool, Tesla 1day Indicators Tool, Tesla 1hour and 1day Klines Tool","Webhook provider for Alpha Vantage data","n8n Execute Workflow integration (parent agent)"],"key_features":["Aggregates 15m, 1h, and 1d technical indicators into a single view","Identifies candlestick patterns and volume divergence across timeframes","Produces a unified JSON signal with stance (Buy/Sell/Hold/Cautious) and confidence score","Breaks down multi-timeframe indicator values for transparency","Uses GPT-4.1 for final reasoning and synthesis of signals」「Maintains session continuity via memory buffer for contextual evaluations\",\"Designed to be invoked as a sub-agent by a parent Tesla Quant Trading AI agent"],"target_audience":["Quant traders and algo developers","Trading analysts and researchers","Prop trading firms and systematic traders implementing n8n integrations"]}


name: Tesla Quant Technical Indicators Webhooks Tool
author_name: Don Jayamaha Jr
author_username: don-the-gem-dealer
categories: []
created_at: 2025-05-16T08:58:13.199Z
updated_at: 2025-05-16T08:58:13.199Z
url: https://n8n.io/workflows/4095
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-14 21:18:33
description:
  📡 This workflow serves as the central Alpha Vantage API fetcher for Tesla trading indicators, delivering cleaned 20-point JSON outputs for three timeframes: 15min, 1hour, and 1day.
  It is required by the following agents:

  Tesla 15min, 1h, 1d Indicators Tools
  Tesla Financial Market Data Analyst Tool

   ✅ Requires an Alpha Vantage Premium API Key
   🚀 Used as a sub-agent via webhook endpoints triggered by other workflows

  📈 What It Does

  For each timeframe (15min, 1h, 1d), this tool:

  Triggers 6 technical indicators via Alpha Vantage:

     RSI
     MACD
     BBANDS
     SMA
     EMA
     ADX
  Trims the raw response to the latest 20 data points
  Reformats into a clean JSON structure:

        {
       "indicator": "MACD",
       "timeframe": "1hour",
       "data": {
         "timestamp": "...",
         "macd": 0.32,
         "signal": 0.29
       }
     }
     Returns results via Webhook Respond for the calling agent

  📂 Required Credentials

  🔑 Alpha Vantage Premium API Key
    Set up under Credentials &gt; HTTP Query Auth

    Name: Alpha Vantage Premium
    Query Param: apikey

  Get yours here: https://www.alphavantage.co/premium/

  🛠️ Setup Steps

  Import Workflow into n8n
     Name it: Tesla_Quant_Technical_Indicators_Webhooks_Tool

  Add HTTP Query Auth Credential
     Name: Alpha Vantage Premium
     Param key: apikey
     Value: your Alpha Vantage key

  Publish and Use the Webhooks
     This workflow exposes 3 endpoints:

     /15minData → used by 15m Indicator Tool
     /1hourData → used by 1h Indicator Tool
     /1dayData → used by 1d Indicator Tool

  Connect via Execute Workflow or HTTP Request
     Ensure caller sends webhook trigger correctly to the path

  🧱 Architecture Summary

  Each timeframe section includes:

  | Component          | Details                                       |
  | ------------------ | --------------------------------------------- |
  | 📡 Webhook Trigger | Entry node (/15minData, /1hourData, etc.) |
  | 🔄 API Calls       | 6 nodes fetching indicators via Alpha Vantage |
  | 🧹 Formatters      | JS Code nodes to clean and trim responses     |
  | 🧩 Merge Node      | Consolidates cleaned JSONs                    |
  | 🚀 Webhook Respond | Returns structured data to calling workflow   |

  🧾 Sticky Notes Overview

  ✅ Webhook Entry: Instructions per timeframe
  ✅ API Call Summary: Alpha Vantage endpoint for each indicator
  ✅ Format Nodes: Explain JSON parsing and cleaning
  ✅ Merge Logic: Final output format
  ✅ Webhook Response: What gets returned to caller

  All stickies follow n8n standard color-coding:

  Blue = Webhook flow
  Yellow = API request group
  Purple = Formatters
  Green = Merge step
  Gray = Workflow overview and usage

  🔐 Licensing & Support

  © 2025 Treasurium Capital Limited Company
  This agent is part of the Tesla Quant AI Trading System and protected under U.S. copyright.

  For support:
  🔗 Don Jayamaha – LinkedIn
  🔗 n8n Creator Profile

  🚀 Use this API tool to feed Tesla technical indicators into any AI or trading agent across 15m, 1h, and 1d timeframes.
  Required for all Tesla Quant Agent indicator tools.

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metadata_json:
  {"categories":["automation","integration","data processing","finance/trading"],"complexity":"complex","use_cases":["Fetch standardized technical indicators for Tesla across multiple timeframes","Provide cleaned 20-point JSON indicator payloads to other workflows/agents via webhooks","Feed trading agents or AI models with ready-to-use market indicators","Integrate Alpha Vantage indicator data into analysis, signals, or alerting systems","Backtesting or on-demand indicator retrieval for algorithmic strategies"],"estimated_setup_minutes":15,"required_services":["Alpha Vantage Premium API (apikey)","n8n (cloud or self-hosted) with webhook endpoints","Calling workflows/agents that trigger the webhooks (HTTP requests)"],"key_features":["Fetches 6 technical indicators (RSI, MACD, BBANDS, SMA, EMA, ADX) per timeframe","Supports three timeframes: 15min, 1hour, 1day","Trims and reformats raw API responses to latest 20 data points","Returns consistent, typed JSON objects for each indicator/timeframe","Exposed webhook endpoints (/15minData, /1hourData, /1dayData) for sub-agent usage or external callers"],"target_audience":["Quant traders and trading strategy developers","Data engineers and analysts needing cleaned indicator data","n8n workflow authors and automation engineers integrating market data into systems and agents','AI/agent integrators feeding models with market indicators"]}


name: Tesla 15min Indicators Tool (Short-Term AI Technical Analysis)
author_name: Don Jayamaha Jr
author_username: don-the-gem-dealer
categories: []
created_at: 2025-05-16T09:00:47.876Z
updated_at: 2025-05-16T09:00:47.876Z
url: https://n8n.io/workflows/4096
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:32
description:
  ⏱️ Analyze Tesla (TSLA) short-term market structure and momentum using 6 technical indicators on the 15-minute timeframe.
  This AI agent tool is part of the Tesla Quant Trading AI Agent system. It is designed to detect intraday shifts in volatility, trend strength, and potential reversal signals.

   ⚠️ Not standalone. This agent is triggered via Execute Workflow by the Tesla Financial Market Data Analyst Tool.

   🔌 Requires:

   Tesla Quant Technical Indicators Webhooks Tool
   Alpha Vantage Premium API Key

  📊 What It Does

  This workflow pulls the latest 20 data points for 6 key technical indicators from a webhook-powered source, then uses GPT-4.1 to interpret market momentum and structure:

  Connected Indicators:

  RSI (Relative Strength Index)**
  MACD (Moving Average Convergence Divergence)**
  BBANDS (Bollinger Bands)**
  SMA (Simple Moving Average)**
  EMA (Exponential Moving Average)**
  ADX (Average Directional Index)**

  The output is a structured JSON with:

  Market summary
  Timeframe (15m)
  Indicator values

  📋 Sample Output

  {
    "summary": "TSLA shows fading momentum. RSI dropped below 60, MACD is flattening, and BBANDS are tightening. Expect short-term consolidation.",
    "timeframe": "15m",
    "indicators": {
      "RSI": 58.3,
      "MACD": {
        "macd": -0.020,
        "signal": -0.018,
        "histogram": -0.002
      },
      "BBANDS": {
        "upper": 183.10,
        "lower": 176.70,
        "middle": 179.90,
        "close": 177.60
      },
      "SMA": 178.20,
      "EMA": 177.70,
      "ADX": 19.6
    }
  }

  🧠 Agent Components

  | Module                | Role                                                     |
  | --------------------- | -------------------------------------------------------- |
  | Webhook Data Node | Calls /15minData endpoint for Alpha Vantage indicators |
  | LangChain Agent   | Parses indicator payloads and generates reasoning        |
  | OpenAI GPT-4.1    | Powers the AI logic to interpret technical structure     |
  | Memory Module     | Maintains session consistency for multi-agent calls      |

  🛠️ Setup Instructions

  Import Workflow into n8n
     Name it: Tesla_15min_Indicators_Tool

  Configure Webhook Source

     Install and publish: Tesla_Quant_Technical_Indicators_Webhooks_Tool
     Ensure /15minData is publicly reachable (or tunnel-enabled)

  Add Credentials

     Alpha Vantage API Key (HTTP Query Auth)
     OpenAI GPT-4.1 (OpenAI Chat Model)

  Link as Sub-Agent
     This workflow is not triggered manually. It is executed using Execute Workflow by:
     👉 Tesla_Financial_Market_Data_Analyst_Tool
     Pass in:

     message (optional)
     sessionId (for short-term memory linkage)

  📌 Sticky Notes Summary

  🟢 Trigger Integration – Receives sessionId and message from parent
  🟡 Webhook Fetcher – Pulls Alpha Vantage data from /15minData
  🧠 GPT-4.1 Reasoning – Produces structured JSON insight
  🔵 Session Memory – Maintains evaluation flow across tools
  📘 Tool Description – Explains indicator use and AI output format

  🔒 Licensing & Author

  © 2025 Treasurium Capital Limited Company
  All logic, formatting, and agent design are protected under copyright. No resale or public re-use without permission.

  Created by: Don Jayamaha
  Creator Profile: https://n8n.io/creators/don-the-gem-dealer/

  🚀 Build faster intraday Tesla trading models using clean 15-minute indicator insights—processed by AI.
  Required by the Tesla Financial Market Data Analyst Tool.

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metadata_json:
  {"categories":["automation","integration","data processing","trading/finance","AI analysis"],"complexity":"medium","use_cases":["Intraday technical analysis for TSLA (15min)","Detect short-term volatility, momentum and reversal signals","Feed structured indicator insights into larger trading agent/system","Automated sub-agent for multi-agent trading workflows","Generate JSON-formatted trading signals/summary for downstream systems"],"estimated_setup_minutes":30,"required_services":["Tesla Quant Technical Indicators Webhooks Tool (public /15minData endpoint)","Alpha Vantage Premium API Key","OpenAI GPT-4.1 (OpenAI Chat model)","n8n instance (with Execute Workflow enabled)","LangChain agent module / memory module (within workflow)"],"key_features":["Fetches latest 20 data points for 6 indicators (RSI, MACD, BBANDS, SMA, EMA, ADX)","Uses GPT-4.1 via LangChain agent to interpret momentum and market structure","Outputs structured JSON summary (timeframe, indicator values, market summary)","Operates as a webhook-triggered sub-agent (not standalone)","Maintains short-term session memory for continuity across calls"],"target_audience":["Quant/algo traders","Trading system developers","Data analysts focused on market microstructure and intraday signals"]}


name: Tesla 1hour Indicators Tool (Mid-Term Technical Analysis AI)
author_name: Don Jayamaha Jr
author_username: don-the-gem-dealer
categories: []
created_at: 2025-05-16T09:03:30.771Z
updated_at: 2025-05-16T09:03:30.771Z
url: https://n8n.io/workflows/4097
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-14 21:18:33
description:
  🕒 Evaluate Tesla (TSLA) price action and market structure on the 1-hour timeframe using 6 real-time indicators.
  This sub-agent is designed to feed mid-term technical insights into the Tesla Financial Market Data Analyst Tool. It uses GPT-4.1 to interpret Alpha Vantage indicator data delivered via secure webhooks.

   ⚠️ This workflow is not standalone and is executed via Execute Workflow.
   🔌 Requires:

   Tesla Quant Technical Indicators Webhooks Tool
   Alpha Vantage Premium API Key

  🔧 Connected Indicators

  This tool fetches and analyzes the latest 20 datapoints for:

  RSI (Relative Strength Index)**
  MACD (Moving Average Convergence Divergence)**
  BBANDS (Bollinger Bands)**
  SMA (Simple Moving Average)**
  EMA (Exponential Moving Average)**
  ADX (Average Directional Index)**

  📋 Sample Output

  {
    "summary": "TSLA is gaining strength on the 1-hour chart. RSI is rising, MACD has crossed bullish, and BBANDS are widening.",
    "timeframe": "1h",
    "indicators": {
      "RSI": 62.1,
      "BBANDS": {
        "upper": 176.90,
        "lower": 169.70,
        "middle": 173.30,
        "close": 176.30
      },
      "SMA": 174.20,
      "EMA": 175.60,
      "ADX": 27.5,
      "MACD": {
        "macd": 0.84,
        "signal": 0.65,
        "histogram": 0.19
      }
    }
  }

  🧠 Agent Components

  | Component                      | Role                                               |
  | ------------------------------ | -------------------------------------------------- |
  | 1hour Data                   | Pulls Alpha Vantage indicator data via webhook     |
  | Tesla 1hour Indicators Agent | Interprets signals using structured GPT-4.1 prompt |
  | OpenAI Chat Model            | GPT-4.1 LLM performs analysis                      |
  | Simple Memory                | Maintains session context                          |

  🛠️ Setup Instructions

  Import Workflow into n8n
     Name it: Tesla_1hour_Indicators_Tool

  Install the Webhook Fetcher Tool
     👉 Required: Tesla_Quant_Technical_Indicators_Webhooks_Tool

     This agent expects webhook /1hourData to return pre-cleaned data

  Add Credentials

     Alpha Vantage Premium API Key (via HTTP Query Auth)
     OpenAI GPT-4.1 credentials

  Configure for Sub-Agent Use

     Triggered only via Execute Workflow from:
       👉 Tesla Financial Market Data Analyst Tool
     Inputs:

       message (optional)
       sessionId (required for memory linkage)

  📌 Sticky Notes Overview

  🟢 Trigger Setup – Activated only by the parent agent
  📊 1h Webhook Fetcher – Calls Alpha Vantage via secured endpoint
  🧠 AI Agent Summary – Interprets trend/momentum from indicator data
  🔗 GPT Model Notes – GPT-4.1 parses and explains technical alignment
  📘 Documentation Sticky – Embedded in canvas with full walkthrough

  🔐 Licensing & Support

  © 2025 Treasurium Capital Limited Company
  This tool is part of a proprietary multi-agent AI architecture. No commercial reuse or redistribution permitted.

  🔗 Author: Don Jayamaha
  🔗 Templates: https://n8n.io/creators/don-the-gem-dealer/

  🚀 Detect TSLA trend shifts and validate setups with 1-hour technical clarity—powered by Alpha Vantage + GPT-4.1.
  This tool is required by the Tesla Financial Market Data Analyst Tool.

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name: Tesla 1day Indicators Tool (Macro-Level Technical AI)
author_name: Don Jayamaha Jr
author_username: don-the-gem-dealer
categories: []
created_at: 2025-05-16T09:06:41.790Z
updated_at: 2025-05-16T09:06:41.790Z
url: https://n8n.io/workflows/4098
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-14 21:18:33
description:
  📅 Analyze Tesla’s daily trading structure with AI using 6 Alpha Vantage indicators.
  This tool evaluates long-term trend health, volatility patterns, and potential reversal signals at the 1-day timeframe. Designed for use within the Tesla Financial Market Data Analyst Tool, this agent helps swing and position traders anchor macro sentiment.

   ⚠️ Not standalone. Must be executed via Execute Workflow
   🔌 Requires:

   Tesla Quant Technical Indicators Webhooks Tool
   Alpha Vantage Premium API Key
   OpenAI GPT-4.1 credentials

  🔍 What It Does

  This tool queries a secured webhook (/1dayData) to retrieve real-time, trimmed JSON data for:

  RSI (Relative Strength Index)**
  BBANDS (Bollinger Bands)**
  SMA (Simple Moving Average)**
  EMA (Exponential Moving Average)**
  ADX (Average Directional Index)**
  MACD (Moving Average Convergence Divergence)**

  These values are then passed to a LangChain AI Agent powered by GPT-4.1, which returns:

  A 2–3 sentence market condition summary
  Structured indicator values
  Timeframe tag ("1d")

  📋 Sample Output

  {
    "summary": "TSLA shows consolidation on the daily chart. RSI is neutral, BBANDS are contracting, and MACD is flattening.",
    "timeframe": "1d",
    "indicators": {
      "RSI": 51.3,
      "BBANDS": {
        "upper": 192.80,
        "lower": 168.20,
        "middle": 180.50,
        "close": 179.90
      },
      "SMA": 181.10,
      "EMA": 179.75,
      "ADX": 15.8,
      "MACD": {
        "macd": -0.25,
        "signal": -0.20,
        "histogram": -0.05
      }
    }
  }

  🧠 Agent Components

  | Component                     | Description                                        |
  | ----------------------------- | -------------------------------------------------- |
  | 1day Data (HTTP Node)       | Pulls latest data from secured /1dayData webhook |
  | OpenAI Chat Model           | GPT-4.1 powers the analysis logic                  |
  | Tesla 1day Indicators Agent | LangChain agent performing interpretation          |
  | Simple Memory               | Short-term session continuity                      |

  🛠️ Setup Instructions

  Import Workflow into n8n

     Name: Tesla_1day_Indicators_Tool

  Add Required Credentials

     Alpha Vantage Premium (via HTTP Query Auth)
     OpenAI GPT-4.1 (Chat Model)

  Install Webhook Fetcher

     Required: Tesla Quant Technical Indicators Webhooks Tool
     Endpoint /1dayData must be active

  Execution Context
     This tool is only triggered via:
     👉 Tesla Financial Market Data Analyst Tool

     Inputs expected:

       message: optional context
       sessionId: session memory linkage

  📌 Sticky Notes Overview

  📘 Tesla 1-Day Indicators Tool – Purpose and integration
  📡 Webhook Fetcher – Pulls daily Alpha Vantage data via HTTPS
  🧠 GPT-4.1 Model – Reasoning for trend classification
  🔗 Sub-Agent Trigger – Used only by Financial Market Analyst
  🧠 Memory Buffer – Ensures consistent session logic

  🔒 Licensing & Support

  © 2025 Treasurium Capital Limited Company
  This workflow—including prompts, logic, and formatting—is protected IP.

  🔗 Don Jayamaha – LinkedIn
  🔗 Creator Profile

  🚀 Evaluate long-term Tesla price behavior with AI-enhanced technical analysis—critical for swing trading strategy.
  Required by the Tesla Financial Market Data Analyst Tool.

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metadata_json:
  {"categories":["automation","integration","data processing","financial-analysis","AI-assist"],"complexity":"medium","use_cases":["Daily macro-level technical analysis for TSLA","Automated swing/position trading signal generation","Feeding structured indicator data into a larger analyst workflow","Quick market condition summaries for traders/analysts"],"estimated_setup_minutes":20,"required_services":["Tesla Quant Technical Indicators Webhooks Tool (secured /1dayData endpoint)","Alpha Vantage Premium API Key","OpenAI GPT-4.1 credentials","n8n (Execute Workflow context)","Tesla Financial Market Data Analyst Tool (parent workflow integration)"],"key_features":["Retrieves six Alpha Vantage indicators (RSI, BBANDS, SMA, EMA, ADX, MACD) via secured webhook","LangChain/GPT-4.1 agent produces 2–3 sentence market summary and structured JSON output","Returns timeframe tag (1d) plus detailed indicator values (including BBANDS and MACD subfields)","Simple memory buffer for short-term session continuity","Designed as a sub-agent to be invoked by the Tesla Financial Market Data Analyst Tool (not standalone)"],"target_audience":["Swing and position traders","Quantitative/technical analysts","Algo/trading developers integrating AI analysis into workflows"]}


name: Tesla 1hour & 1day Klines Tool (Candlestick & Volume AI Pattern Detector)
author_name: Don Jayamaha Jr
author_username: don-the-gem-dealer
categories: []
created_at: 2025-05-16T09:09:10.055Z
updated_at: 2025-05-16T09:09:10.055Z
url: https://n8n.io/workflows/4099
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-14 21:18:33
description:
  📉 Detect key candlestick reversal patterns and volume divergence on Tesla (TSLA) using GPT-4.1 and real-time OHLCV data.
  This AI agent evaluates 1-hour and 1-day candles and is an essential part of the Tesla Financial Market Data Analyst Tool. It identifies signals like Doji, Engulfing, Hammer, and volume anomalies to support trade entry and exit logic.

   ⚠️ Not a standalone template — must be triggered by the Tesla Financial Market Data Analyst Tool
   🔐 Requires:

   Alpha Vantage Premium API Key
   OpenAI GPT-4.1 access

  🔍 What This Agent Does

  Calls Alpha Vantage to fetch:

     🕐 1-hour OHLCV data
     📅 1-day OHLCV data
  GPT-4.1 evaluates:

     📊 Candlestick patterns like Doji, Engulfing, Shooting Star
     🔄 Volume divergence (price/volume inconsistency)
  Returns a structured JSON output like:

  {
    "summary": "Bearish signs detected on 1-day chart. A shooting star formed on high volume while RSI is elevated. Volume divergence seen on 1h chart as price rises but volume weakens.",
    "candlestickPatterns": {
      "1h": "None",
      "1d": "Shooting Star"
    },
    "volumeDivergence": {
      "1h": "Bearish",
      "1d": "None"
    },
    "ohlcv": {
      "1h": {
        "close": 174.1,
        "volume": 1430000,
        "high": 175.0,
        "low": 173.8
      },
      "1d": {
        "close": 188.3,
        "volume": 21234000,
        "high": 189.9,
        "low": 183.7
      }
    }
  }

  🛠️ Setup Instructions

  Import the Workflow

     Name it: Tesla_1hour_and_1day_Klines_Tool

  Install Dependencies

     ✅ Tesla Financial Market Data Analyst Tool (this is the trigger parent)

  Add Required Credentials

     Alpha Vantage Premium → via HTTP Query Auth
     OpenAI GPT-4.1 → via OpenAI credentials

  Verify Web Access

     This tool fetches data live from Alpha Vantage:

       /query?function=TIME_SERIES_INTRADAY&interval=60min
       /query?function=TIME_SERIES_DAILY

  Run via Execute Workflow Trigger
     This tool will activate only when called by the Financial Analyst Agent. Inputs:

     message (optional)
     sessionId (used for memory continuity)

  🧠 Agent Architecture

  | Component               | Description                                         |
  | ----------------------- | --------------------------------------------------- |
  | Candlestick Data Hour | Fetches 60min TSLA candles via Alpha Vantage        |
  | Candlestick Data Day  | Fetches daily TSLA candles via Alpha Vantage        |
  | OpenAI Chat Model     | GPT-4.1 reasoning engine for pattern detection      |
  | Simple Memory         | Maintains short-term logic context                  |
  | Tesla Klines Agent    | LangChain AI agent analyzing both candle and volume |

  📌 Sticky Notes Overview

  📘 Workflow Purpose
  🧠 Short-Term Memory Notes
  🔍 1h/1d Data Fetch Logic
  📉 Candlestick Pattern Types Detected
  📊 Volume Divergence Definitions
  🤖 GPT-4.1 Prompt Configuration

  🔐 Licensing & Support

  © 2025 Treasurium Capital Limited Company
  Logic, pattern reasoning, and prompt structure are proprietary IP.

  🔗 Don Jayamaha – LinkedIn
  🔗 n8n Creator Profile

  🚀 Automate technical edge: detect TSLA candle reversals and volume anomalies with precision using GPT-4.1 and Alpha Vantage.
  Required by the Tesla Financial Market Data Analyst Tool.

nodes_used:
  ["n8n-nodes-base.executeWorkflowTrigger","@n8n/n8n-nodes-langchain.memoryBufferWindow","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.toolHttpRequest","@n8n/n8n-nodes-langchain.toolHttpRequest","@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"]

workflow_json_compressed:
  [encoded data, 5300 characters]

metadata_json:
  {"categories":["automation","financial-market-analysis","data-processing","AI/ML"],"complexity":"medium","use_cases":["Detect candlestick reversal signals for TSLA","Identify volume divergence for trade entry/exit logic","Provide structured market signal JSON to parent trading agent","Augment algorithmic trading strategies with AI pattern detection","Market research and technical analysis automation"],"estimated_setup_minutes":20,"required_services":["Alpha Vantage Premium API (intraday & daily OHLCV)","OpenAI GPT-4.1 (OpenAI API)","Tesla Financial Market Data Analyst Tool (parent/trigger workflow)","n8n (workflow runtime)"],"key_features":["Fetches 1-hour and 1-day OHLCV from Alpha Vantage","Uses GPT-4.1 to detect candlestick patterns (Doji, Engulfing, Hammer, Shooting Star, etc.)","Detects volume divergence between price and volume","Returns standardized JSON summary and detailed fields (patterns, divergence, OHLCV)","Designed as a triggered agent (not standalone) with short-term memory support"],"target_audience":["traders","quantitative analysts","algo developers/engineers integrating trading signals into systems"]}


name: Bulk Delete HubSpot Contacts from Uploaded Excel/CSV File
author_name: Akhil Varma Gadiraju
author_username: akhilv7
categories: []
created_at: 2025-05-16T10:12:10.320Z
updated_at: 2025-05-16T10:12:10.320Z
url: https://n8n.io/workflows/4100
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-14 21:18:33
description:
  Bulk Contact Deletion from HubSpot via Uploaded Excel / CSV File

  This workflow allows you to automate the deletion of HubSpot contacts based on email addresses provided in an uploaded Excel (.xlsx) file. It's ideal for bulk-cleaning outdated or invalid contact data.

  ✅ Prerequisites

  Before using this workflow, ensure you have the following:

  A valid HubSpot App Token with permissions to search and delete contacts.
  An Excel (.xlsx) file with a column labeled emails containing the contact emails to be deleted.
  n8n self-hosted or cloud environment with:
    Webhook node enabled and accessible.
    HubSpot node credentials configured.
  Basic familiarity with n8n node configuration for custom adjustments (optional).

  📃Sample Document




  Download
  🧠 n8n Workflow: Delete HubSpot Contacts from an Uploaded Excel File

  This n8n workflow allows you to upload an Excel file containing contact email addresses. It will check each one in HubSpot and delete the contact if it exists.

  🔗 Workflow Overview

  📥 1. Trigger via Webhook (POST)
  The workflow starts when a .xlsx file is uploaded via an HTTP POST request to the webhook. This Excel file should contain a column with contact email addresses.

  📄 2. Extract Data from Excel
  The uploaded file is parsed, and its rows are converted into structured JSON items, making each email address available for further processing.

  🧹 3. Normalize Data
  The data is cleaned and normalized — for example, mapping column headers (e.g., emails) into a standard email field, ensuring consistent downstream logic.

  🔁 4. Loop Through Contacts
  Each row (contact) is processed individually using batch looping. This allows for fine-grained error handling and sequential processing.

  🔎 5. Search for Contact in HubSpot
  For each contact, a search query is made in HubSpot based on the email address. The workflow only fetches the first result (if any).

  🧪 6. Check if Contact Exists
  An IF condition checks whether the contact was found (i.e., if a HubSpot contact ID exists):
  ✅ Yes → proceed to delete the contact.
  ❌ No → skip deletion and continue to the next.

  🗑️ 7. Delete Contact
  If a contact exists, it is deleted from HubSpot using its internal contact ID.

  🛠️ 8. Optional Placeholder for Post-Processing
  A placeholder node named “Replace Me” is included for any custom logic you may want to add after the deletion step, such as:
  Logging
  Notifications
  Writing to external storage

  ✅ Use Cases

  Bulk delete old or bounced email addresses from HubSpot.
  Clean up contacts based on external suppression lists.
  Automate regular CRM hygiene processes.

  💡 Suggested Enhancements

  ✍️ Log results to Google Sheets or a database
  📬 Send completion report via email or Slack
  🔁 Add retry logic for temporary API failures
  🔍 Validate email format before making requests

  📎 Requirements

  n8n (self-hosted or cloud)
  HubSpot App Token (set up in n8n credentials)
  Excel file (.xlsx) with a column for email

  📦 Files

  No external files are required. All logic is contained within the n8n workflow.

  🚀 Getting Started

  Deploy the workflow in n8n.
  Copy the webhook URL and use it in your app or API client (like Postman).
  Upload an Excel file containing contact emails via POST request.
  Watch as it searches and deletes matches in HubSpot.

nodes_used:
  ["n8n-nodes-base.webhook","n8n-nodes-base.splitInBatches","n8n-nodes-base.noOp","n8n-nodes-base.hubspot","n8n-nodes-base.hubspot","n8n-nodes-base.if","n8n-nodes-base.set","n8n-nodes-base.extractFromFile","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
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metadata_json:
  {"categories":["automation","integration","data processing","CRM"],"complexity":"medium","use_cases":["Bulk-delete outdated or bounced HubSpot contacts from a provided suppression list","Periodic CRM hygiene to remove invalid or unsubscribed emails","Process uploaded Excel/CSV suppression lists and remove matching contacts","Automate cleanup after data-imports or marketing campaigns"],"estimated_setup_minutes":20,"required_services":["HubSpot API (App Token with search & delete permissions)","n8n (self-hosted or cloud) with Webhook node enabled","A client or app able to POST an .xlsx file to the webhook endpoint"],"key_features":["Webhook-triggered upload of Excel (.xlsx) or CSV files","Parsing/extraction of rows from uploaded file into JSON items","Normalization/mapping of email column","Looping through items to search HubSpot by email","Conditional deletion of found contacts using HubSpot contact ID(supports single-result fetch and delete flow only if found ) )"],"target_audience":["CRM administrators","Marketing operations","Data/ETL engineers maintaining contact lists"]}


name: Manage Calendar with Voice & Text using GPT-4, Telegram & Google Calendar
author_name: Marian Tcaciuc
author_username: mariantk
categories: []
created_at: 2025-05-16T11:08:27.232Z
updated_at: 2025-05-16T11:08:27.232Z
url: https://n8n.io/workflows/4102
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:31
description:
  Manage Calendar with Voice & Text Commands using GPT-4, Telegram & Google Calendar

  This n8n workflow transforms your Telegram bot into a personal AI calendar assistant, capable of understanding both voice and text commands in Romanian, and managing your Google Calendar using the GPT-4 model via LangChain.

  Whether you want to create, update, fetch, or delete events, you can simply speak or write your request to your Telegram bot — and the assistant takes care of the rest.

  🚀 Features

  Voice command support using Telegram voice messages (.ogg)
  Transcription using OpenAI Whisper
  Natural language understanding with GPT-4 via LangChain
  Google Calendar integration:
    ✅ Create Events
    🔁 Update Events
    ❌ Delete Events
    📅 Fetch Events
  Responses sent back via Telegram

  🛠️ Step-by-Step Setup Instructions

  1. Create a Telegram Bot
  Go to @BotFather on Telegram.
  Send /newbot and follow the instructions.
  Save the Bot Token.

  2. Configure Telegram Trigger Node
  Paste the Telegram token into the Telegram Trigger and Telegram nodes.
  Set updates to ["message"].

  3. Set up OpenAI Credentials
  Get an OpenAI API key from https://platform.openai.com
  Create a credential in n8n for OpenAI.
  This is used for both transcription and AI reasoning.

  4. Set up Google Calendar
  In Google Cloud Console:
    Enable Google Calendar API
    Set up OAuth2 credentials
    Add your n8n redirect URI (usually https://yourdomain/rest/oauth2-credential/callback)
  Create a credential in n8n using Google Calendar OAuth2
  Grant access to your calendar (e.g., "Family" calendar).

  ⚙️ Customization Options

  🗣️ Change Language or Locale
  The transcription node uses "en" for English. Change to another locale if needed.

  ✏️ Edit Prompt
  You can modify the prompt in the AI Agent node to include your name, work schedule, or specific behavior expectations.

  📆 Change Calendar Logic
  Adjust time ranges or filters in the Get Events node
  Add custom logic before Create Event (e.g., validation, conflict checks)

  📚 Helpful Tips

  Make sure n8n has HTTPS enabled to receive Telegram updates.
  You can test the flow first using only text, then voice.
  Use AI memory or vector stores (like Supabase) if you want context-aware planning in the future.

nodes_used:
  ["n8n-nodes-base.googleCalendarTool","n8n-nodes-base.googleCalendarTool","n8n-nodes-base.googleCalendarTool","n8n-nodes-base.googleCalendarTool","n8n-nodes-base.telegramTrigger","n8n-nodes-base.if","n8n-nodes-base.telegram","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.telegram","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"]

workflow_json_compressed:
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metadata_json:
  {"categories":["automation","integration","calendar management","AI assistant"],"complexity":"medium","use_cases":["Hands-free calendar management via voice or text","Create, update, fetch, and delete Google Calendar events using natural language","Transcribe voice messages and convert to calendar actions","Personal scheduling assistant in a chat (Telegram)"],"estimated_setup_minutes":45,"required_services":["Telegram Bot API","OpenAI (GPT-4 and Whisper)","Google Calendar API (OAuth2 via Google Cloud)","n8n (self-hosted or cloud)","LangChain integration (agent setup)"],"key_features":["Voice message support (.ogg) with Whisper transcription","Natural language understanding and planning with GPT-4 via LangChain","Create/Update/Delete/Fetch Google Calendar events","Replies and confirmations sent back through Telegram","Customizable prompts, language/locale and calendar logic"],"target_audience":["n8n users and automation builders","Developers and integrators setting up chat-based assistants","Busy professionals wanting a voice/text calendar assistant on Telegram"]}


name: Generate Invoices, Save to Drive and Send Email to Customer with JS + G Sheets
author_name: Joseph
author_username: mjomba
categories: []
created_at: 2025-05-16T11:59:58.245Z
updated_at: 2025-05-16T11:59:58.245Z
url: https://n8n.io/workflows/4105
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:31
description:
  This workflow automates invoice generation from form submissions, ensuring unique order IDs, creating PDF invoices, storing files, emailing customers, and logging invoice data — all seamlessly integrated.

  🔹 Workflow Overview

  Trigger (Webhook)
     Starts when an order form is submitted, capturing customer and order details.

  Generate Random Order ID
     A Function node creates a unique alphanumeric invoice ID (e.g., INV-X92B7D).

  Check for Duplicate Order ID
     Google Sheets looks up the generated order ID in your invoice log sheet to prevent duplicates.

  Conditional Check (IF Node)

     If the ID already exists → regenerates a new ID (loops back)
     If unique → proceeds to invoice creation

  Prepare Invoice Data
     A Set node formats customer info, date, order items, and the unique order ID to fit your invoice template.

  Convert HTML to PDF
     HTTP Request node sends your invoice HTML to the RapidAPI HTML-to-PDF service and receives the PDF file.

  Upload PDF to Cloud Storage
     Save the PDF in Google Drive or Dropbox with a clear file name like Invoice-INV-X92B7D.pdf.

  Send Invoice Email to Customer
     Email node attaches the PDF and includes the order ID in the email subject/body.

  Log Invoice Details
     Append invoice data (customer info, order ID, total, PDF link) to your Google Sheet for tracking.

  ⚙️ Node Details & Setup

  1. Webhook Trigger

  Configure to receive form submissions (order details like name, email, items, total).

  2. Function: Generate Random Order ID

  Sample JS code generates unique IDs prefixed by INV-.

  3. Google Sheets: Lookup Row

  Set up connection to your invoice log sheet.
  Search for existing order ID to avoid duplicates.

  4. IF Node: Check Order ID Existence

  Condition: If order ID found → loop to regenerate.
  Else → continue workflow.

  5. Set Node: Prepare Invoice HTML

  Define variables like customer name, date, items, and order ID.
  This data populates your HTML invoice template.

  6. HTTP Request: Convert HTML to PDF

  API URL to get your key
  Send invoice HTML in the request body.
  Receive PDF file blob or download URL.

  7. Google Drive (or Dropbox) Upload

  Upload the PDF file.
  Use file name format: Invoice-{{$json["order_id"]}}.pdf

  8. Email Node

  Recipient: customer email from the form data.
  Attach generated PDF.
  Include order ID in email subject or body for reference.

  9. Google Sheets: Append Row

  Log invoice metadata to keep records updated.

  📁 Google Sheets Template

  You can make a copy of the invoice log template here

  This sheet includes columns for order\_id, customer name, email, total, and invoice PDF link. Customize it as needed.

  📌 Additional Notes

  Customize the invoice HTML template inside the Set node to match your branding.
  Ensure API credentials for RapidAPI, Google Drive/Dropbox, and email are properly set up in your n8n credentials.
  You can expand this workflow by adding payment processing or SMS notifications.

  Need help or want a custom workflow?

  Reach out via email at joseph@uppfy.com.

nodes_used:
  ["n8n-nodes-base.webhook","n8n-nodes-base.code","n8n-nodes-base.googleSheets","n8n-nodes-base.if","n8n-nodes-base.set","n8n-nodes-base.code","n8n-nodes-base.httpRequest","n8n-nodes-base.googleDrive","n8n-nodes-base.emailSend","n8n-nodes-base.googleSheets","n8n-nodes-base.httpRequest","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["automation","invoicing","document-generation","integrations","file-storage','notifications','data-logging"],"complexity":"medium","use_cases":["Automated invoice generation from form submissions","Emailing PDF invoices to customers","Storing invoices in cloud drive (Google Drive/Dropbox)","Maintaining an invoice log in Google Sheets for bookkeeping","Ensuring unique order/invoice IDs to prevent duplicates"],"estimated_setup_minutes":45,"required_services":["Webhook/form provider (e.g., Typeform, Gravity Forms, custom form)","RapidAPI HTML-to-PDF (or alternative HTML->PDF service)","Google Sheets","Google Drive or Dropbox","Email service/SMTP (Gmail, SendGrid, etc.)","n8n with configured credentials"],"key_features":["Generate unique alphanumeric invoice IDs with duplicate-check loop","Populate an HTML invoice template from form data","Convert HTML to PDF via external API","Upload PDF to cloud storage with a clear filename (Invoice-INV-XXX.pdf)","Send invoice email to customer with PDF attachment and order ID in subject/body','Append invoice metadata (order_id, customer, total, PDF link) to Google Sheets"],"target_audience":["Small businesses and e-commerce merchants","Freelancers and consultants","Finance/accounting teams tracking invoices','Developers/automation engineers building order workflows"]}


name: Resume Data Extraction and Storage in Supabase from Email Attachments
author_name: Belgacem Dhiflaoui
author_username: kacemdh
categories: []
created_at: 2025-05-16T13:42:57.033Z
updated_at: 2025-05-16T13:42:57.033Z
url: https://n8n.io/workflows/4106
scraped_at: 2025-09-14 19:11:00
metadata_generated_at: 2025-09-14 21:18:32
description:
  Description
  What Problem Does This Solve? 🛠️

  This workflow automates the process of extracting key information from resumes received as email attachments and storing that data in a structured format within a Supabase database. It eliminates the manual effort of reviewing each resume, identifying relevant details, and entering them into a database. This streamlines the hiring process, making it faster and more efficient for recruiters and HR professionals.

  Target audience: Recruiters, HR departments, and talent acquisition teams.

  What Does It Do? 🌟
  Monitors a designated email inbox for new messages with resume attachments.
  Extracts key information such as name, contact details, education, work experience, and skills from the attached resumes.
  Cleans and formats the extracted data.
  Stores the processed data securely in a Supabase database.

  Key Features 📋

  Automatic email monitoring for resume attachments.
  Intelligent data extraction from various resume formats (e.g., PDF, DOC, DOCX).
  Customizable data fields to capture specific information.
  Seamless integration with Supabase for data storage.
  Uses OpenRouter to streamline API key management for services such as AI-powered parsing.

  Setup Instructions

  Prerequisites ⚙️

  n8n Instance**: Self-hosted or cloud instance of n8n.
  Email Account**: Gmail account with Gmail API access for receiving resumes.
  Supabase Account**: A Supabase project with a database/table ready to store extracted resume data. You'll need the Supabase URL and API key.
  OpenRouter Account**: For managing AI model API keys centrally when using LLM-based resume parsing.

  Installation Steps 📦
  1. Import the Workflow:

  Copy the exported workflow JSON.
  Import it into your n8n instance via “Import from File” or “Import from URL”.

  2. Configure Credentials:

  In n8n &gt; Credentials, add credentials for:
    Email account (Gmail API): Provide Client ID and Client Secret from the Google Cloud Platform.
    Supabase: Provide the Supabase URL and the anon public API key.
    OpenRouter (Optional): Add your OpenRouter API key for use with any AI-powered resume parsing nodes.

  Assign these credentials to their respective nodes:

    Gmail Trigger → Email credentials.
    Supabase Insert → Supabase credentials.
     AI Parsing Node → OpenRouter credentials.

  3. Set Up Supabase Table:

  Create a table in Supabase with columns such as:
  name, email, phone, education, experience, skills, received_date, etc.

  Make sure the field names align with the structure used in your workflow.

  4. Customize Nodes:

  Parsing Node(s):* Modify the workflow to use an *OpenAI model* directly for field extraction, replacing the *Basic LLM Chain** node that utilizes OpenRouter.

  5. Test the Workflow:

  Send a test email with a resume attachment.
  Check n8n's execution log to confirm the workflow triggered, parsed the data, and inserted it into Supabase.
  Verify data integrity in your Supabase table.

  How It Works
  High-Level Workflow 🔍

  Email Monitoring: Triggered when a new email with an attachment is received (via Gmail API).
  Attachment Check: Verifies the email contains at least one attachment.
  Prepare Data: Extracts the attachment and prepares it for analysis.
  Data Extraction: Uses OpenRouter-powered LLM (if configured) to extract structured information from the resume.
  Data Storage: The structured information is saved into the Supabase database.

  Node Names and Actions (Example)

  Gmail Trigger:** Triggers when a new email is received.
  IF**: Checks whether the received email includes any attachments.
  Get Attachments:** Retrieves attachments from the triggering email.
  Prepare Data:** Prepares the attachment content for processing.
  Basic LLM Chain:** Uses an AI model via OpenRouter to extract relevant resume data and returns it as structured fields.
  Supabase-Insert:** Inserts the structured resume data into your Supabase database.

nodes_used:
  ["n8n-nodes-base.gmailTrigger","n8n-nodes-base.extractFromFile","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.chainLlm","@n8n/n8n-nodes-langchain.lmChatOpenRouter","@n8n/n8n-nodes-langchain.outputParserStructured","n8n-nodes-base.httpRequest","n8n-nodes-base.supabase","n8n-nodes-base.set","n8n-nodes-base.splitOut","n8n-nodes-base.supabase","n8n-nodes-base.set","n8n-nodes-base.splitOut","n8n-nodes-base.supabase","n8n-nodes-base.set","n8n-nodes-base.splitOut","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.if","n8n-nodes-base.stickyNote"]

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metadata_json:
  {"categories":["automation","data extraction","integration","recruitment","hr"],"complexity":"medium","use_cases":["Automatically ingest resumes from email into a candidate database","Populate applicant tracking systems or candidate spreadsheets","Pre-screening and parsing candidate contact, education, experience and skills","Standardizing resume data for analytics and reporting","Reducing manual data entry for recruiting teams"],"estimated_setup_minutes":45,"required_services":["n8n (self-hosted or cloud)","Gmail / Google API (for email trigger)","Supabase (project + table and API key)","OpenRouter (optional, for centralized LLM API key management)","OpenAI or another LLM provider (optional, if using direct model calls)"],"key_features":["Monitors email inbox for new resume attachments","Extracts structured fields (name, email, phone, education, experience, skills)","Supports common resume formats (PDF, DOC, DOCX)","Cleans and formats extracted data before storage","Inserts structured records into Supabase table(s)"],"target_audience":["Recruiters","HR departments","Talent acquisition teams"]}


name: Create AI Videos with OpenAI Scripts, Leonardo Images & HeyGen Avatars
author_name: Adam Crafts
author_username: adamcrafts
categories: []
created_at: 2025-05-16T14:23:39.655Z
updated_at: 2025-05-16T14:23:39.655Z
url: https://n8n.io/workflows/4107
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:31
description:
  Short Content Automation 🎬 (AI Video System with Bulk Gen, Avatar & Music Customization)

  Overview 🎯

  The "Short Content" automation is a powerful, all-in-one solution designed to streamline the creation of short videos for social media, marketing, or personal projects. Leveraging cutting-edge AI tools and seamless workflows, this automation handles everything from scriptwriting to video assembly—saving time and effort while delivering professional results.


      
        Best Short Content AI System - Watch Video
  Problem 🛠️

  Creating short videos manually is time-consuming and expensive. Businesses and creators struggle with:

  Hiring writers, designers, and editors.  
  Juggling multiple tools for scripts, visuals, and editing.  
  Inconsistent quality and slow turnaround times.  

  This automation solves these challenges with a fully AI-driven, one-click workflow.

  Solution ✅

  A no-code, end-to-end automation that:

  Writes scripts using AI (LLM) or manual input.  
  Generates visuals (Leonardo AI) or acting scenes (RunwayML).  
  Edits and assembles videos (JSON2Video).  
  Generates avatars using HeyGen or Captions.ai.  
  Tracks progress and analytics in Baserow.  

  🔥 Result:  
  High-quality short videos in minutes, not days—with zero manual effort.

  Setup ⚙️ (4–8 minutes)

  Upload Blueprint to N8N  
     Import the provided JSON workflow into your N8N instance.

  Upload Database to Baserow (Free)  
  Follow the setup video step-by-step.

  How It Works 🌟

  Start with a Pre-Built Form  
     Fill in the included Baserow form with your video requirements.

  Generate Videos Instantly  
     Single Video Mode: Run one video at a time for quick results.  
     Bulk Mode: Upload a CSV or use Baserow to queue unlimited videos—perfect for scaling content.

  Workflow Handles the Rest  

  Manage & Iterate  
     Track all videos in Baserow: Edit inputs, retry failed jobs, or adjust styles anytime.

  What’s Included 📦

  ✅ Baserow Template: Pre-configured database.  
  ✅ N8N JSON Blueprint: Ready-to-use workflow.  
  ✅ Step-by-Step Video Guides: Setup & usage instructions.

  Customization 🎨

  🔧 Video Generation Customization

  Script Options**: Auto-generate using AI or write manually.  
  Captions**: Customize type, color, and style.  
  Video Types**: Storytelling, trends, educational, etc.  
  Audio**: Add background music easily.  
  Avatars**:  
    Switch between HeyGen and Captions.ai.  
    Adjust size, position, voice, and appearance.

  ⚙️ System Customization

  N8N Workflow**: Easily customizable for new integrations, prompts, and logic.  
  Baserow Database**: Modify options or add new ones to match your workflow.

  🌐 Explore more workflows

  ❤️ Buy more workflows at: adamcrafts
  🦾 Custom workflows at: adamcrafts@cloudysoftwares.com

  &gt; Build once, customize endlessly, and scale your video content like never before. 🚀

nodes_used:
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metadata_json:
  {"categories":["automation","media production","AI content generation","integration"],"complexity":"complex","use_cases":["Short-form social video creation (TikTok, Reels, Shorts)","Bulk video content scaling for marketing campaigns","Automated ad/creative generation","Repurposing blog posts or scripts into videos","Training/microlearning video production"],"estimated_setup_minutes":6,"required_services":["n8n","Baserow","OpenAI (LLM for script generation)","Leonardo AI (image generation)","HeyGen or Captions.ai (avatar generation)","JSON2Video (video assembly)","RunwayML (optional scene/visual generation)","Storage/hosting for assets (S3 or similar) and optional music sources"],"key_features":["End-to-end no-code video pipeline from script → visuals → final video","AI script generation (LLM) or manual script input","Image/visual generation via Leonardo AI","Avatar/actor generation via HeyGen/Captions.ai","Video assembly & editing via JSON2Video (and optional RunwayML integration)"],"target_audience":["Content creators and influencers","Social media managers and marketers","Agencies producing high-volume short-form content"]}


name: AI image generator from text built on fal.ai
author_name: n8n Team
author_username: n8n-team
categories: []
created_at: 2025-05-16T14:29:12.278Z
updated_at: 2025-05-16T14:29:12.278Z
url: https://n8n.io/workflows/4108
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:31
description:
  Who this template is for

  This template is for developers, content creators, or application builders who want to integrate an AI-powered text-to-image generation service into their applications or systems via an API endpoint.

  Use case

  Creating a secure API endpoint that converts text prompts into AI-generated images, with built-in content moderation to prevent inappropriate content generation. This can be used for creative applications, content creation tools, prototyping interfaces, or any system that needs on-demand image generation.

  How this workflow works

  Receives text prompt through a webhook endpoint
  Filters the prompt for inappropriate content using AI moderation
  Submits valid prompts to the Fal.ai Flux image generation service
  Polls for completion status and retrieves the generated image when ready
  Returns the image results in a structured JSON format to the client

  Set up steps

  Create a Fal.ai account and obtain API credentials
  Configure the HTTP Header Auth credentials with your Fal.ai API key
  Set up an OpenAI API key for the content moderation component
  Deploy the workflow and note the webhook URL for your API endpoint
  Test the endpoint by sending a POST request with a JSON body containing a "prompt" field

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metadata_json:
  {"categories":["automation","integration","AI/ML","content generation"],"complexity":"medium","use_cases":["Expose a secure text-to-image API endpoint","Integrate on-demand image generation into apps or prototypes","Automate creative/content generation workflows","Provide moderated image generation for user-generated content"],"estimated_setup_minutes":20,"required_services":["n8n (self-hosted or cloud) for workflow execution","Fal.ai (Flux) API for image generation","OpenAI API for content moderation"],"key_features":["Webhook-based API endpoint to receive text prompts","Content moderation step to filter inappropriate prompts","Submits prompts to Fal.ai Flux for image generation","Asynchronous polling for generation completion and retrieval","Returns structured JSON with image results and metadata (ready/failed states)"],"target_audience":["Developers","Content creators","Application builders / product teams"]}


name: Clone Viral TikToks with AI Avatars & Auto-Post to 9 Platforms using Perplexity & Blotato
author_name: Dr. Firas
author_username: drfiras
categories: []
created_at: 2025-05-16T15:33:36.828Z
updated_at: 2025-05-16T15:33:36.828Z
url: https://n8n.io/workflows/4110
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 19:29:36
description:
  Clone a viral TikTok with AI and auto-post it to 9 platforms using Perplexity & Blotato

  Who is this for?

  This workflow is perfect for:
  Content creators looking to repurpose viral content
  Social media managers who want to scale short-form content across multiple platforms
  Entrepreneurs and marketers aiming to save time and boost visibility with AI-powered automation

  What problem is this workflow solving?

  Reproducing viral video formats with your own branding and pushing them to multiple platforms is time-consuming and hard to scale. This workflow solves that by:
  Cloning a viral TikTok video’s structure
  Generating a new version with your avatar
  Rewriting the script, caption, and overlay text
  Auto-posting it to 9 social media platforms — without manual uploads

  What this workflow does

  From a simple Telegram message with a TikTok link, the workflow:

  Downloads a TikTok video and extracts its thumbnail, audio, and caption
  Transcribes the audio and saves original text into Google Sheets
  Uses Perplexity AI to suggest a new content idea in the same niche
  Rewrites the script, caption, and overlay using GPT-4o
  Generates a new video with your avatar using Captions.ai
  Adds subtitles and overlay text with JSON2Video
  Saves metadata to Google Sheets for tracking
  Sends the final video to Telegram for preview
  Auto-publishes the video to Instagram, YouTube, TikTok, Facebook, LinkedIn, Threads, X (Twitter), Pinterest, and Bluesky via Blotato

  Setup

  Connect your Telegram bot to the trigger node.
  Add your OpenAI, Perplexity, Cloudinary, Captions.ai, and Blotato API keys.
  Make sure your Google Sheet is ready with the appropriate columns.
  Replace the default avatar name in the Captions.ai node with yours.
  Fill in your social media account IDs in the "Assign Platform IDs" node.
  Test by sending a TikTok URL to your Telegram bot.

  How to customize this workflow to your needs

  Change avatar output style**: adjust resolution, voice, or avatar ID.
  Refine script structure**: tweak GPT instructions for different tone/format.
  Swap Perplexity with ChatGPT or Claude** if needed.
  Filter by platform**: disable any Blotato nodes you don’t need.
  Add approval step**: insert a Telegram confirmation node before publishing.
  Adjust subtitle style or overlay text font** in JSON2Video.

  📄 Documentation: Notion Guide

  Need help customizing?
  Contact me for consulting and support : Linkedin / Youtube

nodes_used:
  ["n8n-nodes-base.set","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.telegramTrigger","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","@n8n/n8n-nodes-langchain.openAi","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.httpRequest","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.code","n8n-nodes-base.googleSheets","n8n-nodes-base.httpRequest","n8n-nodes-base.code","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.code","n8n-nodes-base.code","n8n-nodes-base.googleSheets","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.wait","n8n-nodes-base.httpRequest","n8n-nodes-base.httpRequest","n8n-nodes-base.wait","n8n-nodes-base.httpRequest","n8n-nodes-base.googleSheets","n8n-nodes-base.telegram","n8n-nodes-base.telegram"]

workflow_json_compressed:
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metadata_json:
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name: Create AI-Powered WhatsApp Quiz Bot with GPT-4o-mini and Supabase Storage
author_name: Danielle Gomes
author_username: daniellegomes
categories: []
created_at: 2025-05-16T16:59:16.154Z
updated_at: 2025-05-16T16:59:16.154Z
url: https://n8n.io/workflows/4114
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:32
description:
  Quiz Assistant via WhatsApp with Supabase and OpenAI

  Create a quiz assistant that helps users study a topic of their choice through WhatsApp. Using Supabase and OpenAI, this workflow captures missing user data, stores it, and delivers dynamic quizzes tailored to each topic.

  Main Use Cases

  Guide users through personalized study sessions
  Collect and store user preferences (name + topic)
  Automate quiz creation with AI
  Deliver interactive content via WhatsApp

  How It Works

  This workflow is composed of three main paths:

  1. User Info Collection

  Triggered by an incoming WhatsApp message
  Retrieves existing user data from Supabase
  Checks if the name and topic are already defined
  If not, sends WhatsApp prompts to collect missing info
  Updates Supabase with new entries

  2. AI Quiz Generation

  Once name and topic are confirmed, the Merge node consolidates all inputs
  Data is sent to the AI Agent (OpenAI Chat + Memory)
  The agent generates a quiz based on the selected topic

  3. Response Delivery

  The quiz is sent back to the user via WhatsApp
  Flow ends, ready to restart with the next interaction

nodes_used:
  ["@n8n/n8n-nodes-langchain.memoryBufferWindow","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.merge","n8n-nodes-base.webhook","n8n-nodes-base.if","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.supabase","n8n-nodes-base.httpRequest","n8n-nodes-base.supabase","n8n-nodes-base.if","n8n-nodes-base.httpRequest","n8n-nodes-base.supabase","n8n-nodes-base.httpRequest","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 4716 characters]

metadata_json:
  {"categories":["automation","education","messaging","ai-integration"],"complexity":"medium","use_cases":["Personalized study sessions via chat","Collect and persist user preferences (name, topic)","Automated quiz generation with AI","Delivering interactive content over WhatsApp"],"estimated_setup_minutes":45,"required_services":["WhatsApp API (e.g., Twilio or Meta Cloud API)","Supabase (Postgres storage + auth)","OpenAI (GPT-4o-mini / Chat API)","n8n"],"key_features":["Collects missing user data via chat and persists to Supabase","Checks and updates user profile (name, topic)","AI agent generates tailored quizzes using chat + memory","Delivers quizzes back to users over WhatsApp","Uses merge and conditional logic to route flows"],"target_audience":["Educators and tutors","Students and learners","Product teams building chat experiences or study tools by automation engineers/developers"]}


name: Analyze Crypto Market with CoinGecko: Volatility Metrics & Investment Signals
author_name: ist00dent
author_username: ist00dent
categories: []
created_at: 2025-05-16T17:00:04.497Z
updated_at: 2025-05-16T17:00:04.497Z
url: https://n8n.io/workflows/4115
scraped_at: 2025-09-14 19:10:59
metadata_generated_at: 2025-09-14 21:18:31
description:
  This n8n template lets you automatically pull market data for the cryptocurrencies from CoinGecko every hour, calculate custom volatility and market-health metrics, classify each coin’s price action into buy/sell/hold/neutral signals with risk ratings, and expose both individual analyses and a portfolio summary via a webhook. It’s perfect for crypto analysts, DeFi builders, or portfolio managers who want on-demand insights without writing a single line of backend code.

  🔧 How it works
  Schedule Trigger fires every hour (or interval you choose).
  HTTP Request (CoinGecko) fetches the top 10 coins by market cap, including 24 h, 7 d, and 30 d price change percentages.
  Split In Batches ensures each coin is processed sequentially.
  Function (Calculate Market Metrics) computes:
    A weighted volatility score
    Market-cap-to-volume ratio
    Price-to-ATH ratio
    Composite market score

  IF & Switch nodes categorize each coin’s 24 h price action (up &gt;5%, down &gt;5%, high volatility, or stable) and append:
    signal (BUY/SELL/HOLD/NEUTRAL)
    riskRating (High/Medium/Low/Unknown)
    recommendation & investmentStrategy guidance

  NoOp & Merge nodes consolidate each branch back into a single data stream.

  Function (Generate Portfolio Summary) aggregates all analyses into:
    A Markdown portfolioSummary
    Counts of buy/sell/hold/neutral signals
    Risk distribution

  Webhook Response returns the full JSON payload with individual analyses and the summary for downstream consumers.

  👤 Who is it for?
  This workflow is ideal for:

  Crypto researchers and analysts who need scheduled market insights

  DeFi and trading bot developers looking to automate signal generation

  Portfolio managers seeking a no-code overview of top assets

  Automation engineers exploring API integration and data enrichment

  📑 Data Structure
  When you trigger the webhook, you’ll receive a JSON object containing:

  individualAnalyses: Array of { coin, symbol, currentPrice, priceChanges, marketMetrics, signal, riskRating, recommendation }

  portfolioSummary: Markdown report summarizing signals, risk distribution, and top opportunity

  marketSignals: Counts of each signal type

  riskDistribution: Counts of each risk rating

  timestamp: ISO string of analysis time

  ⚙️ Setup Instructions
  Import: In n8n Editor → click “Import from JSON” → paste this workflow JSON.

  Configure Schedule: Double-click the Schedule Trigger → set your desired interval (default: every hour).

  Webhook Path: Open the Webhook node → choose a unique path (e.g., /crypto‐analysis) and “POST”.

  Activate: Save and activate the workflow.

  Test:
    Open the webhook url to other tab or use cURL
  curl -X POST https://&lt;your-n8n-host&gt;/webhook/&lt;path&gt;

  You’ll get back a JSON payload with both portfolioSummary and individualAnalyses.

  📝 Tips
  Rate-Limit Handling: If CoinGecko returns 429, insert a Delay node (e.g., 500 ms) after the HTTP Request.
  Batch Size: Default is 1 coin at a time; you can bump it to parallelize.
  Customization: Tweak volatility weightings or add new metrics directly in the “Calculate Market Metrics” Function node.
  Extension: Swap CoinGecko for another API by updating the HTTP Request URL and field mappings.

nodes_used:
  ["n8n-nodes-base.httpRequest","n8n-nodes-base.function","n8n-nodes-base.if","n8n-nodes-base.if","n8n-nodes-base.if","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.noOp","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.noOp","n8n-nodes-base.function","n8n-nodes-base.noOp","n8n-nodes-base.function","n8n-nodes-base.splitInBatches","n8n-nodes-base.switch","n8n-nodes-base.splitOut","n8n-nodes-base.respondToWebhook","n8n-nodes-base.webhook","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
  [encoded data, 6608 characters]

metadata_json:
  {"categories":["automation","integration","data processing","analytics"],"complexity":"medium","use_cases":["Scheduled crypto market monitoring","Automatic buy/sell/hold signal generation","Portfolio health summary and reporting","Feeding signals to trading bots or downstream systems","Prototyping DeFi/market analytics without backend code"],"estimated_setup_minutes":10,"required_services":["CoinGecko API (public endpoints)","n8n instance / host with webhook access"],"key_features":["Hourly (configurable) polling of top N coins by market cap","Per-coin volatility and market-health metric calculations (weighted volatility, market-cap-to-volume, price-to-ATH, composite score)","Signal classification (BUY/SELL/HOLD/NEUTRAL) with risk ratings","Branching logic with IF/Switch and batch processing for sequential coin handling","Portfolio aggregation producing Markdown summary and signal/risk distributions"],"target_audience":["Crypto analysts and researchers","DeFi developers and integrators","Trading bot developers and quants testing signals quickly without backend code management"]}


name: AI-Powered Telegram Bot for Data Extraction with Bright Data MCP
author_name: Cyril Nicko Gaspar
author_username: cngaspar
categories: []
created_at: 2025-05-16T17:41:31.909Z
updated_at: 2025-05-16T17:41:31.909Z
url: https://n8n.io/workflows/4116
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:32
description:
  📌 AI Agent Template with Bright Data MCP Tool Integration

  This template enables natural-language-driven automation using Bright Data MCP tools. It extracts all available tools from MCP, processes the user’s query through an AI agent, then dynamically selects and executes the appropriate tool.

  ❓ Problem It Solves

  Traditional automation often requires users to understand APIs, interfaces, or scripts to perform backend tasks. The Bright Data MCP integration solves this by allowing natural language interaction, intelligently classifying user intent, and managing context-aware execution of complex operations—ideal for data extraction, customer support, and workflow orchestration.

  🧰 Pre-requisites

  Before deploying this template, make sure you have:

  An active N8N instance (self-hosted or cloud).
  A valid OpenRouter API key (or another compatible AI model).
  Telegram bot and its API token
  Access to the Bright Data MCP API with credentials.
  Basic familiarity with N8N workflows and nodes.

  ⚙️ Setup Instructions

  Setup and obtain API token and other necessary information from Bright Data

     In your Bright Data account, obtain the following information:
     API token
     Web Unlocker zone name (optional)
     Browser Zone name (optional)
  Host SSE server from STDIO command
     The methods below will allow you to receive SSE (Server-Sent Events) from Bright Data MCP via a local Supergateway or Smithery

     **

     Method 1: Run Supergateway in a separate web service (Recommended)

     This method will work for both cloud version and self-hosted N8N.

     Signup to any cloud services of your choice (DigitalOcean, Heroku, Hetzner, Render, etc.).

  For NPM based installation:

     Create a new web service.
     Choose Node.js as runtime environment and setup a custom server without repository.
     In your server’s settings to define environment variables or .env file, add:
  `API_TOKEN=your_brightdata_api_token
  WEB_UNLOCKER_ZONE=optional_zone_name
  BROWSER_ZONE=optional_browser_zone_name`
     Paste the following text as a start command: npx -y supergateway --stdio "npx -y @brightdata/mcp" --port 8000 --baseUrl http://localhost:8000 --ssePath /sse --messagePath /message
     Deploy it and copy the web server URL, then append /sse into it.
     Your SSE server should now be accessible at: https://your_server_url/sse

  For Docker based installation:
     Create a new web service.
     Choose Docker as the runtime environment.
     Set up your Docker environment by pulling the necessary images or creating a custom Dockerfile.
     In your server’s settings to define environment variables or .env file, add:
  `API_TOKEN=your_brightdata_api_token
  WEB_UNLOCKER_ZONE=optional_zone_name
  BROWSER_AUTH=optional_browser_auth`
      Use the following Docker command to run Supergateway: `docker run -it --rm -p 8000:8000 supercorp/supergateway \
      --stdio "npx -y @brightdata/mcp /" \
      --port 8000`
     Deploy it and copy the web server URL, then append /sse into it.
     Your SSE server should now be accessible at: https://your_server_url/sse

     For more installation guides, please refer to https://github.com/supercorp-ai/supergateway.git.
     **

     Method 2: Run Supergateway in the same web service as the N8N instance

     This method will only work for self-hosted N8N.

  a. Set Required Environment Variables

     In your server's settings to define environment variables or .env file, add:

        API_TOKEN=your_brightdata_api_token
     WEB_UNLOCKER_ZONE=optional_zone_name
     BROWSER_ZONE=optional_browser_zone_name
  b. Run Supergateway in Background

        npx -y supergateway --stdio "npx -y @brightdata/mcp" --port 8000 --baseUrl http://localhost:8000 --ssePath /sse --messagePath /message
        Use the command above to execute it through the cloud shell or set it as a pre-deploy command.


     Your SSE server should now be accessible at:  
     http://localhost:8000/sse

   
     For more installation guides, please refer to https://github.com/supercorp-ai/supergateway.git.

     *

     *Method 3: Configure via Smithery.ai* (Easiest)
  If you don't want additional setup and want to test it right away, follow these instructions:

     Visit https://smithery.ai/server/@luminati-io/brightdata-mcp/tools to:
     Signup (if you are new to Smithery)
     Create an API key
     Define environment variables via a profile
     Retrieve your SSE server HTTP URL

  Import the Workflow

     Open N8N.
     Import the JSON workflow file included with this template.
     Update any nodes referencing external services (e.g., OpenRouter, Telegram).

  Setup Telegram Integration

     If you haven't setup a bot in Telegram, below is the instruction how to create one using BotFather:
       Search for @BotFather in Telegram and start a conversation with it.
       Send the command /newbot to create a new bot. You'll be prompted to enter a name and a unique username for your bot.
       BotFather will provide you with an access token, which you'll need to use to interact with the bot's API. 

     Edit the HTTP Request node in the workflow.
     Configure the URL as follows:  
            https://api.telegram.org/bot+your_telegram_bot_token+/setWebhook?url=+your_webhook_url
          Replace +your_telegram_bot_token+ with your actual Telegram bot token.
     Replace +your_webhook_url+ with the URL from the Webhook Trigger node in the workflow.
     This will set up Telegram to forward messages to your n8n agent.

  🔄 Workflow Functionality (Summary)

  The user submits a message via chat.
  Memory** nodes retain context for multi-turn conversations.
  The mapped tool is executed and results are returned contextually.

  🧠 Optional memory buffers and memory manager nodes keep the interaction context-aware.

  🧩 Use Cases

  Data Scraping on Demand**: Launch scraping tasks via chat.
  Lead Generation Bots**: Enrich or validate leads with MCP tools.
  AI-Powered Customer Support**: Classify and answer queries with real-time data tools.
  Workflow Assistants**: Let teams run backend processes like lookups or report generation using plain language.

  🛠️ Customization

  Classifier Prompt & Logic**: Tweak the AI’s prompt and tool-matching schema to better fit your use case.
  Memory Configuration**: Adjust retention policies and context depth.
  Tool Execution Sub-Workflow**: Extend for retries, logging, or chaining actions.
  Omni-Channel Support**: Connect via webhooks to chat interfaces like Slack, WhatsApp, Telegram, or custom UIs.

  ✅ Summary

  This template equips you with a powerful no-code/low-code AI agent that translates conversation into real-world action. Using Bright Data’s MCP tools through natural language, it enables teams to automate and scale data-driven tasks effortlessly.

nodes_used:
  ["@n8n/n8n-nodes-langchain.agent","@n8n/n8n-nodes-langchain.memoryBufferWindow","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.lmChatOpenRouter","n8n-nodes-base.manualTrigger","n8n-nodes-base.httpRequest","n8n-nodes-base.webhook","n8n-nodes-base.telegram","n8n-nodes-base.executeWorkflow","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.telegram","n8n-nodes-base.stickyNote","@n8n/n8n-nodes-langchain.mcpClientTool","n8n-nodes-base.n8n","n8n-nodes-base.if","n8n-nodes-base.if","n8n-nodes-base.telegram","n8n-nodes-base.wait","n8n-nodes-base.executeWorkflowTrigger"]

workflow_json_compressed:
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metadata_json:
  {"categories":["automation","integration","data extraction","chatbot/AI agent"],"complexity":"complex","use_cases":["On-demand web/data scraping via chat","Lead enrichment and validation","AI-powered customer support with real-time tooling","Workflow assistants to run backend lookups and reports"],"estimated_setup_minutes":60,"required_services":["Bright Data MCP (Bright Data)","n8n instance (self-hosted or cloud)","Telegram Bot API","OpenRouter or compatible AI model API key","SSE host (Supergateway) or Smithery.ai","Optional: Docker or cloud hosting provider"],"key_features":["Natural-language driven AI agent that maps user intent to Bright Data MCP tools","Dynamic tool selection and execution based on AI classification","Server-Sent Events (SSE) integration via Supergateway/Smithery for real-time responses","Telegram webhook integration for chat input/output","Memory nodes for multi-turn, context-aware conversations and retention control (memory manager)"],"target_audience":["Developers and automation engineers","Data engineers and researchers performing scraping","Marketing and growth teams (lead gen)」「Customer support and operations teams"]}


name: Track HDFC Credit Card Transactions with Google Sheets and Telegram Notifications
author_name: Krishna Kumar Eswaran
author_username: mrprogrammer
categories: []
created_at: 2025-05-17T01:19:51.323Z
updated_at: 2025-05-17T01:19:51.323Z
url: https://n8n.io/workflows/4128
scraped_at: 2025-09-14 19:11:02
metadata_generated_at: 2025-09-14 21:18:33
description:
  🧠 Problem This Solves
  Managing credit card expenses can be tricky, especially when you want to stay transparent and keep your spouse in the loop. Most banks don't offer real-time notification sharing with family members, and manually updating expenses takes time and effort. This n8n workflow automates the entire process: tracking your HDFC credit card usage, logging it in Google Sheets, and sending an instant Telegram notification to your spouse.

  👥 Who This Template Is For
  Couples who want shared visibility of credit card spending

  Individuals looking for automated personal finance tracking

  Anyone using HDFC Credit Card with email alerts enabled

  n8n users who want to integrate Gmail, Google Sheets, and Telegram

  ⚙️ Workflow Breakdown
  Here’s how the automation works:

  Gmail Trigger – Monitors your Gmail inbox for credit card transaction alerts from HDFC Bank.

  Email Parser – Extracts transaction details like amount, merchant name, date, and card type.

  Google Sheets Node – Logs the parsed transaction data into a structured Google Sheet for record-keeping.

  Telegram Node – Sends a message to your wife’s Telegram account with transaction details for instant notification.

  🛾 Step-by-Step Setup Instructions
  Prerequisites
  An HDFC Credit Card with email alerts enabled

  A Gmail account connected to n8n

  A Google Sheet created with columns like Date, Amount, Merchant, Card, etc.

  A Telegram Bot and your wife’s Telegram Chat ID

  Set up Gmail Trigger
  Use the Gmail Trigger Node to monitor incoming emails from alerts@hdfcbank.net or similar.

  Filter emails with subject line containing keywords like Credit Card Transaction Alert.

  Extract Email Content
  Use the HTML Extract or Regex node to parse out transaction amount, merchant name, date, and card number from the email body.

  Log to Google Sheets
  Connect your Google Sheets account in n8n

  Use the Append Row node to add each transaction as a new row in your finance sheet.

  Send Telegram Message
  Set up a Telegram Bot and get the Chat ID of your wife’s Telegram account

  Format a message like:
  "💳 HDFC Transaction Alert: ₹5,000 at Amazon on 17 May via XXXX1234"

  Send it via the Telegram node

  🛠️ Customization Tips
  💡 Add Spending Limits: Add a condition node to alert only if the transaction exceeds a certain amount.

  🧾 Category Mapping: Use additional logic to classify expenses (e.g., Shopping, Dining) based on keywords.

  📊 Weekly Summary: Create another workflow that sends a weekly Telegram summary using data from Google Sheets.

  🔐 Security Tip: Mask part of the card number before sending the Telegram message for added security.

nodes_used:
  ["n8n-nodes-base.gmailTrigger","n8n-nodes-base.code","n8n-nodes-base.filter","n8n-nodes-base.telegram","n8n-nodes-base.splitInBatches","n8n-nodes-base.googleSheets","n8n-nodes-base.code","n8n-nodes-base.telegram","n8n-nodes-base.googleSheets"]

workflow_json_compressed:
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metadata_json:
  {"categories":["automation","integration","personal finance","notifications","data logging"],"complexity":"medium","use_cases":["Real-time shared credit card expense tracking","Automated logging of HDFC credit card transactions","Instant partner/family notifications for purchases","Building a searchable expense ledger in Google Sheets","Triggering spend-based alerts (thresholds or categories)"],"estimated_setup_minutes":20,"required_services":["n8n","Gmail (HDFC alert emails enabled)","Google Sheets","Telegram (Bot + recipient chat ID)"],"key_features":["Gmail trigger to detect HDFC transaction emails","Email parsing (HTML/regex) to extract amount, merchant, date, card)","Append transaction rows to Google Sheets","Telegram notifications with formatted transaction message","Optional filters for spend thresholds and category mapping (via logic nodes or code nodes)"],"target_audience":["Couples wanting shared visibility of spending","Individuals who want automated personal finance tracking","n8n users integrating Gmail, Google Sheets and Telegram"]}


name: WhatsApp Expense Tracker with PostgreSQL Database & AI-Powered Reports
author_name: Roshan Ramani
author_username: rawsun007
categories: []
created_at: 2025-05-17T05:57:32.971Z
updated_at: 2025-05-17T05:57:32.971Z
url: https://n8n.io/workflows/4136
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:32
description:
  Track Personal Finances with WhatsApp and AI Assistant

  Transform your WhatsApp into a powerful personal finance command center. This AI-powered workflow converts natural language messages into structured financial data, automates record-keeping, and delivers instant insights—all within your favorite messaging app.

  Who is this for?

  This template is perfect for:
  Personal finance enthusiasts** who want effortless expense tracking
  Small business owners** managing personal and business expenses  
  Freelancers** tracking income and expenses across projects
  Anyone** who prefers messaging over complex finance apps
  Users seeking privacy** with self-hosted financial data

  What problem is this workflow solving?

  Traditional expense tracking requires switching between apps, manual data entry, and complex spreadsheets. Most people abandon these systems within weeks. This workflow solves the friction by:
  Eliminating app-switching—everything happens in WhatsApp
  Converting natural language to structured data automatically
  Providing instant confirmations and reports
  Requiring zero learning curve or behavior change

  What this workflow does

  Smart Transaction Processing
  Send natural messages like Spent 300 on groceries at Walmart and the AI automatically extracts:
  Date**: Today's date (or specified date)
  Category**: Groceries  
  Type**: Expense/Income/Debt
  Amount**: 300
  Person/Company**: Walmart

  Intelligent Message Classification
  The workflow automatically routes messages to three processing branches:
  Branch 1**: Reports and analytics (show March expenses)
  Branch 2**: Transaction logging (spent 50 on coffee)  
  Branch 3**: General financial chat (how can I save money?)

  Advanced Reporting
  Generate instant reports by messaging:
  today's report → Daily income/expense summary
  March vs April report → Monthly comparisons with percentages
  show groceries spending → Category-specific analysis
  Automatic daily summaries at your preferred time

  Database Integration
  All transactions are stored in PostgreSQL with proper schema:
  CREATE TABLE financial_transactions (
   date DATE NOT NULL,
   category TEXT NOT NULL, 
   type TEXT NOT NULL,
   amount NUMERIC(12,2) NOT NULL,
   person TEXT
  );

  Setup

  Prerequisites

  n8n instance** (self-hosted or n8n.cloud)
  WhatsApp Business Cloud API** credentials
  PostgreSQL database** (version 12+)
  OpenRouter API key** for AI processing

  Quick Setup Steps

  Import the workflow template into your n8n instance
  Configure credentials:
    WhatsApp Business Cloud API (App Token + Phone Number ID)
    PostgreSQL connection details
    OpenRouter API key for AI processing
  Create database table using the provided SQL schema
  Test the connection by sending a sample message
  Customize the scheduled report timing (default: 8 AM daily)

  Verification Checklist

  [ ] WhatsApp webhook receives messages
  [ ] AI correctly parses transaction messages
  [ ] Database insertions work properly
  [ ] Confirmation messages are sent back
  [ ] Reports generate with accurate data

  How to customize this workflow to your needs

  AI Model Configuration

  Default**: Uses OpenRouter with GPT-3.5-turbo for cost efficiency
  Upgrade**: Switch to GPT-4 or Claude for better accuracy
  Local**: Replace with self-hosted Ollama for complete privacy

  Database Options

  PostgreSQL**: Recommended for production use
  Google Sheets**: Alternative for simpler setups (nodes included)
  MySQL/SQLite**: Easily adaptable with minor SQL modifications

  Message Classification

  Customize the classification system:
  0**: Reports (modify SQL queries for different analytics)
  1**: Transactions (adjust parsing rules for your language/currency)
  2**: Chat (customize AI responses for financial advice)

  Reporting Customization

  Scheduled reports**: Change timing, format, and recipients
  Custom periods**: Add quarterly, yearly, or custom date ranges
  Categories**: Modify auto-categorization rules for your spending patterns
  Currency**: Update formatting for your local currency

  Advanced Features

  Multi-user support**: Add user identification for family/team use
  Receipt photos**: Extend workflow to process image receipts via OCR
  Budgets**: Add budget tracking and overspend alerts
  Integrations**: Connect to banks via Plaid or other financial APIs

  Complete Package Included

  When you download this template, you get everything needed for immediate implementation:

  Ready-to-Use n8n Workflow

  Fully configured nodes** with descriptive names explaining each step
  Color-coded sticky notes** throughout the workflow explaining:
   What each branch does (Reports/Transactions/Chat)
   How the AI classification works
   Database connection requirements
   Error handling and troubleshooting tips

  Comprehensive Documentation Bundle

  Quick Start Guide**: Get running in under 10 minutes
  Detailed Setup Guide**: Complete configuration walkthrough with screenshots
  Branch Explanation Guide**: Deep dive into each processing branch:
   Branch 0: Reports & Analytics - SQL queries and formatting
   Branch 1: Transaction Processing - AI parsing and database insertion
   Branch 2: Financial Chat - AI responses and conversation handling

  Built-in Workflow Documentation

  Sticky notes at every major step** explaining the logic
  Node descriptions** that clarify what each component does
  Visual flow indicators** showing message routing paths
  Dependency callouts** highlighting required credentials and connections

  Technical Implementation Details

  Database schema** with complete SQL commands
  API configuration examples** for all external services
  Troubleshooting checklist** for common setup issues
  Performance optimization** recommendations

  Bonus Resources

  Example message templates** to test each workflow branch
  Sample data** for testing reports and analytics
  Customization recipes** for common modifications
  Integration patterns** for extending functionality

  Example Usage

  Log Expenses:

  Spent 1200 on rent this month
  Paid 45 for gas at Shell
  Coffee 5.50 at Starbucks

  Log Income:

  Received 5000 salary from Company ABC
  Freelance payment 800 from Client XYZ

  Generate Reports:

  today's summary
  show this week's expenses
  compare March vs April spending
  how much on food this month?

  Expected Responses:
  ✅ Logged: expense | Rent | ₹1,200.00 | Landlord
  ✅ Logged: income | salary |₹12,000.00|company

  📊 Today's Summary:
  Income: ₹0.00
  Expenses: ₹1,245.50  
  Savings: -₹1,245.50

  📈 March vs April:
  Expenses: ₹15,000 vs ₹12,500 (-16.7%)
  Top categories: Rent, Food, Transport

nodes_used:
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metadata_json:
  {"categories":["automation","integration","data processing","ai","reporting"],"complexity":"complex","use_cases":["Personal expense tracking via chat","Small business expense & income logging","Freelancer project income tracking","Instant financial reports and comparisons","Automated daily/periodic financial summaries"],"estimated_setup_minutes":30,"required_services":["n8n instance (self-hosted or n8n.cloud)","WhatsApp Business Cloud API (App Token + Phone Number ID)","PostgreSQL database (v12+)","OpenRouter API key (or alternative LLM provider)"],"key_features":["Natural-language to structured transaction parsing (AI)","WhatsApp-based UX with confirmations","Automatic routing to branches: reports, transaction logging, financial chat","Persistent storage in PostgreSQL with provided schema","Scheduled daily summaries and on-demand reports via chat queries (eg. today, compare months) "],"target_audience":["Personal finance enthusiasts","Small business owners","Freelancers/independent contractors」「Developers or n8n implementers configuring integrations and databases"]}


name: AI-Powered Telegram Task Assistant with Notion Integration
author_name: Alexey from Mingles.ai
author_username: alexx
categories: []
created_at: 2025-05-17T08:00:32.223Z
updated_at: 2025-05-17T08:00:32.223Z
url: https://n8n.io/workflows/4142
scraped_at: 2025-09-14 19:11:01
metadata_generated_at: 2025-09-14 21:18:32
description:
  This workflow creates a powerful AI assistant in Telegram that helps you manage your tasks in Notion. The assistant leverages OpenAI's language models to understand natural language commands, process voice messages, and maintain context through conversations.

  Key features:
  Processes both text and voice messages in Telegram
  Transcribes voice messages automatically
  Maintains conversation context with memory
  Manages Notion tasks through a custom tool:
    • List all tasks
    • Add new tasks with priority (today/later)
    • Complete or uncomplete tasks
    • Change task timing

  The workflow consists of two main parts:
  AI Agent section: Handles Telegram connectivity, message processing, voice transcription, and conversation management
  Notion Tool section: Implements the custom tool that connects to your Notion database, allowing the AI to interact with your tasks

  Setup requires:
  A Telegram bot token
  OpenAI API credentials
  Notion integration token and database ID

  Example Notion Database


  Perfect for personal productivity, team task management, or as a foundation for building more complex AI assistants with additional tools.

nodes_used:
  ["n8n-nodes-base.telegramTrigger","@n8n/n8n-nodes-langchain.agent","n8n-nodes-base.set","@n8n/n8n-nodes-langchain.lmChatOpenAi","n8n-nodes-base.telegram","@n8n/n8n-nodes-langchain.openAi","n8n-nodes-base.executeWorkflowTrigger","n8n-nodes-base.manualTrigger","n8n-nodes-base.set","n8n-nodes-base.notion","n8n-nodes-base.notion","n8n-nodes-base.notion","n8n-nodes-base.switch","n8n-nodes-base.notion","n8n-nodes-base.code","@n8n/n8n-nodes-langchain.toolWorkflow","n8n-nodes-base.switch","n8n-nodes-base.telegram","n8n-nodes-base.telegram","@n8n/n8n-nodes-langchain.memoryBufferWindow","n8n-nodes-base.set","n8n-nodes-base.set","n8n-nodes-base.stickyNote"]

workflow_json_compressed:
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metadata_json:
  {"categories":["automation","integration","ai-assistant","productivity"],"complexity":"medium","use_cases":["Personal task management via chat","Team task coordination and updates","Transcribe voice messages to tasks","Build a conversational AI assistant with task tooling","Automate Notion task CRUD operations from Telegram"],"estimated_setup_minutes":25,"required_services":["n8n automation platform","Telegram Bot API (bot token)","OpenAI API (chat + transcription)","Notion API (integration token and database ID)"],"key_features":["Handles both text and voice Telegram messages","Automatic voice transcription","Maintains conversation context with memory","Custom Notion tool to list/add/complete/uncomplete/change task timing","Two-part workflow: AI agent + Notion tool for safe tool use"],"target_audience":["Individual users and productivity enthusiasts","Small teams managing tasks in Notion","Developers building conversational assistants or automations documenting tasks for Notion integrations"]}


name: SmartLead Sheet Sync: Auto-Capture Client Inquiries to Google Sheets
author_name: David Olusola
author_username: dae221
categories: []
created_at: 2025-05-17T13:39:34.835Z
updated_at: 2025-05-17T13:39:34.835Z
url: https://n8n.io/workflows/4148
scraped_at: 2025-09-14 19:11:03
metadata_generated_at: 2025-09-14 21:18:33
description:
  Capture client inquiries from any webform and send them straight into Google Sheets — automatically.  No code. No headaches.

  🚀 What It Does:

  SmartLead Sheet Sync is a plug-and-play automation that:
  	•	Instantly receives form submissions from your website or funnel via a webhook
  	•	Extracts and formats key info (like name, email, business name, message, timeline, budget)
  	•	Logs everything into a Google Sheet — in real time

  Perfect for freelancers, digital agencies, consultants, and productized service owners who want to stop copying/pasting leads manually.

  ⸻

  ⚙️ What You Get:
  	•	A pre-built 3-step automation (Webhook → Code → Google Sheet)
  	•	Ready-to-use setup in n8n (free and open source automation tool)
  	•	Clean, editable JavaScript code to format your incoming lead data
  	•	Google Sheet connection that logs every new inquiry in its own row

nodes_used:
  ["n8n-nodes-base.stickyNote","n8n-nodes-base.stickyNote","n8n-nodes-base.webhook","n8n-nodes-base.code","n8n-nodes-base.googleSheets"]

workflow_json_compressed:
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metadata_json:
  {"categories":["automation","integration","data-collection","lead-capture"],"complexity":"simple","use_cases":["Automatically capture webform leads","Log inquiries to a central Google Sheet","Standardize and format incoming lead data","Reduce manual copy/paste for lead intake","Trigger follow-up or CRM sync downstream"],"estimated_setup_minutes":10,"required_services":["n8n instance (self-hosted or cloud)","Google Sheets (Google account)","Webhook-capable form or funnel provider (Typeform, Gravity Forms, custom HTML form, etc.)"],"key_features":["Receives form submissions via webhook in real time","Parses and formats key lead fields with editable JavaScript","Appends each inquiry as a new row in Google Sheets","Pre-built 3-step workflow (Webhook → Code → Google Sheets)","No-code friendly with editable code node for customization"],"target_audience":["Freelancers","Digital agencies","Consultants and service providers/productized services owners','Small business owners and sales teams"]}


