Workflow Templates

Startup Funding Research Automation with Claude, Perplexity AI, and Airtable How it works This intelligent workflow automatically discovers and analyzes recently funded startups by: Monitoring multiple news sources (TechCrunch and VentureBeat) for funding announcements Using AI to extract key funding details (company name, amount raised, investors) Conducting automated deep research on each company through perplexity deep research or jina deep search. Organizing all findings into a structured Airtable database for easy access and analysis Set up steps (10-15 minutes) Connect your news feed sources (TechCrunch and VentureBeat). Could be extended. These were easy to scrape and this data can be expensive. Set up your AI service credentials (Claude and Perplexity or jina which has generous free tier) Connect your Airtable account and create a base with appropriate fields (can be imported from my base) or see structure below. Airtable Base Structure Funding Round Base | Field Name | Data Type | Description | |------------|-----------|-------------| | website_url | String | URL of the company website | | company_name | String | Name of the company | | funding_round | String | The funding stage or round (e.g., Series A, Seed, etc.) | | funding_amount | Number | The amount of funding received | | lead_investor | String | The primary investor leading the funding round | | market | String | The market or industry sector the company operates in | | participating_investors | String | List of other investors participating in the funding round | | press_release_url | String | URL to the press release about the funding | | evaluation | Number | The company's valuation | Structure Company Deep Research Base | Field Name | Data Type | Description | |------------|-----------|-------------| | website_url | String | URL of the company website | | company_name | String | Name of the company | | funding_round | String | The funding stage or round (e.g., Series A, Seed, etc.) | | funding_amount | Number | The amount of funding received | | currency | String | Currency of the funding amount | | announcement_date | String | Date when the funding was announced | | lead_investor | String | The primary investor leading the funding round | | participating_investors | String | List of other investors participating in the funding round | | industry | String | The industry sectors the company operates in | | company_description | String | Description of the company's business | | hq_location | String | Company headquarters location | | founding_year | Number | Year the company was founded | | founder_names | String | Names of the company founders | | ceo_name | String | Name of the company CEO | | employee_count | Number | Number of employees at the company | | total_funding | Number | Total funding amount received to date | | total_funding_currency | String | Currency of total funding | | funding_purpose | String | Purpose or use of the funding | | business_model | String | Company's business model | | valuation | Object | Company valuation information | | previous_rounds | Object | Information about previous funding rounds | | source_urls | String | Source URLs for the funding information | | original_report | String | Original report text about the funding | | market | String | The market the company operates in | | press_release_url | String | URL to the press release about the funding | | evaluation | Number | The company's valuation | Notes I found that by using perplexity via open router, we lose access to the sources, as they are not stored in the same location as the report itself so I opted to use perplexity API via HTTP node. For using perplexity and or jina you have to configure header auth as described in Header Auth - n8n Docs What you can learn How to scrape data using sitemaps How to extract strucutred data from unstructured text How to execute parts of the workflow as subworkflow How to use deep research in a practical scenario How to define more complex JSON schemas

Introduction The "Automatic Weekly Digital PR Stories Suggestions" workflow is a sophisticated automated system designed to identify trending news stories on Reddit, analyze public sentiment through comment analysis, extract key information from source articles, and generate strategic angles for potential digital PR campaigns. This workflow leverages the power of social media trends, natural language processing, and AI-driven analysis to deliver curated, sentiment-analyzed news opportunities for PR professionals. Operating on a weekly schedule, the workflow searches Reddit for posts related to specified topics, filters them based on engagement metrics, and performs a deep analysis of both the content and public reaction. It then generates comprehensive reports that include story opportunities, audience insights, and strategic recommendations. These reports are automatically compiled, stored in Google Drive, and shared with team members via Mattermost for immediate collaboration. This workflow solves the time-consuming process of manually monitoring social media for trending stories, analyzing public sentiment, and identifying PR opportunities. By automating these tasks, PR professionals can focus on strategy development and execution rather than spending hours on research and analysis. Who is this for? This workflow is designed for digital PR professionals, content marketers, communications teams, and media relations specialists who need to stay on top of trending stories and public sentiment to develop timely and effective PR campaigns. It's particularly valuable for: PR agencies managing multiple clients across different industries In-house PR teams needing to identify media opportunities quickly Content marketers looking for trending topics to create timely content Communications professionals monitoring public perception of industry news Users should have basic familiarity with n8n workflows and the PR strategy development process. While technical knowledge of the integrated APIs is not required to use the workflow, some understanding of Reddit, sentiment analysis, and PR campaign development would be beneficial for interpreting and acting on the generated reports. What problem is this workflow solving? Digital PR professionals face several challenges that this workflow addresses: Information Overload: Manually monitoring social media platforms for trending stories is time-consuming and often results in missed opportunities. Sentiment Analysis Complexity: Understanding public perception of news stories requires reading through hundreds of comments and identifying patterns, which is labor-intensive and subjective. Content Extraction: Visiting multiple news sources to read and analyze articles takes significant time. Strategic Angle Development: Identifying unique PR angles that leverage trending stories and public sentiment requires synthesizing large amounts of information. Team Collaboration: Sharing findings and insights with team members in a structured format can be cumbersome. By automating these processes, the workflow enables PR professionals to quickly identify trending stories with PR potential, understand public sentiment, and develop strategic angles based on comprehensive analysis, all while maintaining a structured approach to team collaboration. What this workflow does Overview The workflow automatically identifies trending posts on Reddit related to specified topics, analyzes both the content of linked articles and public sentiment from comments, and generates comprehensive PR strategy reports. These reports include story opportunities, audience insights, and strategic recommendations based on the analysis. The final reports are compiled, stored in Google Drive, and shared with team members via Mattermost. Process Topic Selection and Reddit Search: The workflow starts with a list of topics specified in the "Set Data" node It searches Reddit for posts related to these topics Posts are filtered based on upvotes and other criteria to focus on trending content Comment Analysis: For each post, the workflow retrieves comments It extracts the top 30 comments based on score Using Claude AI, it analyzes the comments to understand: Overall sentiment Dominant narratives Audience insights PR implications Content Analysis: The workflow extracts the content of the linked article using Jina AI It analyzes the content to identify: Core story elements Technical aspects Narrative opportunities Viral elements PR Strategy Development: Based on the combined analysis of comments and content, the workflow generates: First-mover story opportunities Trend-amplifier story ideas Priority rankings Execution roadmap Strategic recommendations Report Generation and Distribution: The workflow compiles comprehensive reports for each post Reports are converted to text files All files are compressed into a ZIP archive The archive is uploaded to Google Drive A link to the archive is shared with team members via Mattermost Setup To set up this workflow, follow these steps: Import the Workflow: Download the workflow JSON file Import it into your n8n instance Configure API Credentials: Reddit: Add a new credential "Reddit OAuth2 API" by following the guide at https://docs.n8n.io/integrations/builtin/credentials/reddit/ Anthropic: Add a new credential "Anthropic Account" by following the guide at https://docs.n8n.io/integrations/builtin/credentials/anthropic/ Google Drive: Add a new credential "Google Drive OAuth2 API" by following the guide at https://docs.n8n.io/integrations/builtin/credentials/google/oauth-single-service/ Configure the "Set Data" Node: Set your interested topics (one per line) Add your Jina API key (obtain from https://jina.ai/api-dashboard/key-manager) Configure the Mattermost Node: Update your Mattermost instance URL Set your Webhook ID and Channel Follow the guide at https://developers.mattermost.com/integrate/webhooks/incoming/ for webhook setup Adjust the Schedule (Optional): The workflow is set to run every Monday at 6am Modify the "Schedule Trigger" node if you need a different schedule Test the Workflow: Run the workflow manually to ensure all connections are working properly Check the output to verify the reports are being generated correctly How to customize this workflow to your needs This workflow can be customized in several ways to better suit your specific requirements: Topic Selection: Modify the topics in the "Set Data" node to focus on industries or subjects relevant to your PR strategy Add multiple topics to cover different client interests or market segments Filtering Criteria: Adjust the "Upvotes Requirement Filtering" node to change the minimum upvotes threshold Modify the filtering conditions to include or exclude certain types of posts Analysis Parameters: Customize the prompts in the "Comments Analysis," "News Analysis," and "Stories Report" nodes to focus on specific aspects of the content or comments Adjust the temperature settings in the Anthropic Chat Model nodes to control the creativity of the AI responses Report Format: Modify the "Set Final Report" node to change the structure or content of the final reports Add or remove sections based on your specific reporting needs Distribution Method: Replace or supplement the Mattermost notification with email notifications, Slack messages, or other communication channels Add additional storage options beyond Google Drive Schedule Frequency: Change the "Schedule Trigger" node to run the workflow more or less frequently Set up multiple triggers for different topics or clients Integration with Other Systems: Add nodes to integrate with your CRM, content management system, or project management tools Create connections to automatically populate content calendars or task management systems

Awork currently does not support a check for open subtasks or open dependencies when setting a task status to done. This workflow offers you a simple workaround to add this functionality to Awork and notifies users when triggered. Multiple configuration options available. How it works Triggered via Awork Webhook call on status change of tasks If task is marked as done, subtasks and/or dependent tasks are checked for their status If unfinished tasks are found, a status rollback to previous status is performed and user gets notified Set up steps Add webhook call to Awork Configure Awork API credentials Set up workflow configuration via setup node, e.g. user notification text, restrict to subtasks/dependency checks etc.

Note: Now includes an Apify alternative for Rapid API (Some users can't create new accounts on Rapid API, so I have added an alternative for you. But immediately you are able to get access to Rapid API, please use that option, it returns more detailed data). *Scroll to bottom for APify setup guide* This n8n workflow automates LinkedIn lead generation, enrichment, and activity analysis using Apollo.io, RapidAPI, Google Sheets and Mail.so. Perfect for sales teams, founders, B2B marketers, and cold outreach pros who want personalized lead insights to drive better conversion rates. ⚙️ How This Workflow Works The workflow is broken down into several key steps, each designed to help you build and enrich a valuable list of LinkedIn leads: 1. 🔑 Lead Discovery (Keyword Search via Apollo) Pulls leads using Apollo.io's API based on keywords, industries, or job titles. Saves lead name, title, company, and LinkedIn URL to your Google Sheet. You can replace the trigger node from the form node to a webhook, whatsapp, telegram, etc, any way for you to send over your query variables over to initiate the workflow. 2. 🧠 Username Extraction (from LinkedIn URL) Extracts the LinkedIn username from profile URLs using a simple script node. This is required for further enrichment via RapidAPI. 3. ✉️ Email Lookup (via Apollo User ID) Uses the Apollo User ID to retrieve the lead’s verified work email. Ensures high-quality leads with reliable contact info. To double check that the email is currently valid, we use the mail.so api and filter out emails that fail deliverability and mx-record check. We don't wanna risk sending emails to no longer existent addresses, right? 4. 🧾 Profile Summary Enrichment (via RapidAPI) Queries the LinkedIn Data API to fetch a lead’s profile summary/bio. Gives you a deeper understanding of their background and expertise. 5. 📰 Recent Activity Collection (Posts & Reposts) Retrieves recent posts or reposts from each lead’s profile. Great for tailoring outreach with reference to what they’re currently talking about. 6. 🗂️ Leads Database Update All enriched data is written to the same Google Sheet. New columns are filled in without overwriting existing data. ✅ Smart Retry & Row Status Logic Every subworkflow includes a fail-safe mechanism to ensure: ✅ Each row has status columns (e.g., done, failed, pending). 🕒 A scheduled retry workflow resets failed rows to pending after 2 weeks (customizable). 💬 This gives failed enrichments another chance to be processed later, reducing data loss. 📋 Google Sheets Setup Template 1: Apollo Leads Scraping & Enrichment Template 2: Enriched Leads Database Make a copy to your Drive and use. Columns will be filled as each subworkflow runs (email, summary, interests, etc.) 🔐 Required API Keys To use this workflow, you’ll need the following credentials: 🧩 Apollo.io Sign up and get your key here: Apollo.io API Keys ⚠️ Important: Toggle the “Master API Key” option to ON when generating your key. This ensures the same key can be used for all Apollo endpoints in this workflow. 🌐 RapidAPI (LinkedIn Data API) Subscribe to the API here: LinkedIn Data API on RapidAPI Use the key in the x-rapidapi-key header in the relevant nodes. ✉️ Mail.so Sign up and get your key here: Mail.so API > 💡 For both APIs, set up the credentials in n8n as “Generic Credential” types. This way, you won’t need to reconfigure the headers in each node. 🛠️ Customization Options Modify the Apollo filters (location, industry, seniority) to target your ideal customers. Change retry interval in the scheduler (e.g., weekly instead of 2 weeks). Connect the database to your email campaign tool like Mailchimp or Instantly.ai. Replace the AI nodes with your desired AI agents and customize the system messages further to get desired results. 🆕 Apify Update Guide To use this workflow, you’ll need the following credentials: Login to Apify, then open this link; https://console.apify.com/actors/2SyF0bVxmgGr8IVCZ/ Click on integrations and scroll down to API Solutions and select "Use API endpoints". Scroll to "Run Actor synchronously and get dataset items" and copy the actor endpoint url then paste it in the placeholder inside the http node of Apify alternative flow "apify-actor-endpoint". That's it, you are set to go. I am available for custom n8n workflows, if you like my work, please get in touch with me on email at joseph@uppfy.com

Complete MCP server exposing 1 Buy Marketing API operations to AI agents. ⚡ Quick Setup Need help? Want access to more workflows and even live Q&A sessions with a top verified n8n creator.. All 100% free? Join the community Import this workflow into your n8n instance Credentials Add Buy Marketing API credentials Activate the workflow to start your MCP server Copy the webhook URL from the MCP trigger node Connect AI agents using the MCP URL 🔧 How it Works This workflow converts the Buy Marketing API into an MCP-compatible interface for AI agents. • MCP Trigger: Serves as your server endpoint for AI agent requests • HTTP Request Nodes: Handle API calls to https://api.ebay.com/buy/marketing/v1_beta • AI Expressions: Automatically populate parameters via $fromAI() placeholders • Native Integration: Returns responses directly to the AI agent 📋 Available Operations (1 total) 🔧 Merchandised_Product (1 endpoints) • GET /merchandised_product: Fetch Merchandised Products 🤖 AI Integration Parameter Handling: AI agents automatically provide values for: • Path parameters and identifiers • Query parameters and filters • Request body data • Headers and authentication Response Format: Native Buy Marketing API responses with full data structure Error Handling: Built-in n8n HTTP request error management 💡 Usage Examples Connect this MCP server to any AI agent or workflow: • Claude Desktop: Add MCP server URL to configuration • Cursor: Add MCP server SSE URL to configuration • Custom AI Apps: Use MCP URL as tool endpoint • API Integration: Direct HTTP calls to MCP endpoints ✨ Benefits • Zero Setup: No parameter mapping or configuration needed • AI-Ready: Built-in $fromAI() expressions for all parameters • Production Ready: Native n8n HTTP request handling and logging • Extensible: Easily modify or add custom logic > 🆓 Free for community use! Ready to deploy in under 2 minutes.

This workflow leverages n8n to perform automated Google Maps API queries and manage data efficiently in Google Sheets. It's designed to extract specific location data based on a given list of ZIP codes and categories. Features Queries the Google Maps API for location data using predefined ZIP codes and subcategories. Filters, de-duplicates, and organizes data into structured rows in Google Sheets. Implements exponential backoff retries to handle API rate limits. Logs and updates statuses directly in Google Sheets for easy tracking. Prerequisites Google OAuth Credentials: A configured Google Cloud project for Google Maps API and Sheets API access. Google Sheets: A sheet with ZIP codes and categories defined (e.g., "AZ Zips"). n8n Setup: A running instance of n8n with credentials configured for Google OAuth. Setup Instructions 1. Prepare Google Sheets Add the ZIP codes to the "AZ Zips" sheet. Define subcategories in another sheet (e.g., "Google Maps Categories"). Provide the sheet's URL in the Settings node of the workflow. 2. Configure API Access Set up Google OAuth credentials for Maps and Sheets APIs in n8n. Ensure your API key has access to the places.searchText endpoint. 3. Workflow Customization Modify textQuery parameters in the GMaps API node to match your query needs. Adjust trigger intervals as required (e.g., manual or scheduled execution). 4. Run the Workflow Execute the workflow manually or schedule periodic runs to keep your data updated. Notes This workflow includes robust error handling to retry failed API calls with exponential backoff. All data is organized and logged directly in Google Sheets for easy reference and updates. For more information or issues, feel free to reach out!

👥 Who Is This For? Content creators, marketing teams, and channel managers who need to streamline video publishing with optimized metadata and scheduled releases across multiple videos. 🛠 What Problem Does This Solve? Manual YouTube video publishing is time-consuming and often results in inconsistent descriptions, tags, and scheduling. This workflow fully automates: Extracting video transcripts via Apify for metadata generation Creating SEO-optimized descriptions and tags for each video Setting videos to private during initial upload (critical for scheduling) Implementing scheduled publishing at strategic times Maintaining consistent branding and formatting across all content 🔄 Node-by-Node Breakdown | Step | Node Purpose | |------|--------------| | 1 | Every Day (Scheduler) | Trigger workflow on a regular schedule | | 2 | Get Videos to Harmonize | Retrieve videos requiring metadata enhancement | | 3 | Get Video IDs (Unpublished) | Filter for videos that need publishing | | 4 | Loop over Video IDs | Process each video individually | | 5 | Get Video Data | Retrieve metadata for the current video | | 6 | Loop over Videos with Parameter IS | Set parameters for processing | | 7 | Set Videos to Private | Ensure videos are private (required for scheduling) | | 8 | Apify: Get Transcript | Extract video transcript via Apify | | 9 | Fetch Latest Videos | Get most recent channel content | | 10 | Loop Over Items | Process each video item | | 11 | Generate Description, Tags, etc. | Create optimized metadata from transcript | | 12 | AP Clean ID | Format identifiers | | 13 | Retrieve Generated Data | Collect the enhanced metadata | | 14 | Adjust Transcript Format | Format transcript for better processing | | 15 | Update Video's Metadata | Apply generated description and tags to video | ⚙️ Pre-conditions / Requirements n8n with YouTube API credentials configured Apify account with API access for transcript extraction YouTube channel with upload permissions Master templates for description formatting Videos must be initially set to private for scheduling to work ⚙️ Setup Instructions Import this workflow into your n8n instance. Configure YouTube API credentials with proper channel access. Set up Apify integration with appropriate actor for transcript extraction. Define scheduling parameters in the Every Day node. Configure description templates with placeholders for dynamic content. Set default tags and customize tag generation rules. Test with a single video before batch processing. 🎨 How to Customize Adjust prompt templates for description generation to match your brand voice. Modify tag selection algorithms based on your channel's SEO strategy. Create multiple publishing schedules for different content categories. Integrate with analytics tools to optimize publishing times. Add notification nodes to alert when videos are successfully scheduled. ⚠️ Important Notes Videos MUST be uploaded as private initially - the Publish At logic only works for private videos that haven't been published before. Publishing schedules require videos to remain private until their scheduled time. Transcript quality affects metadata generation results. Consider YouTube API quotas when scheduling large batches of videos. 🔐 Security and Privacy API credentials are stored securely within n8n. Transcripts are processed temporarily and not stored permanently. Webhook URLs should be protected to prevent unauthorized triggering. Access to the workflow should be limited to authorized team members only.

Overview The Docker NextCloud WHMCS module leverages a sophisticated workflow for n8n, designed to automate the comprehensive deployment, configuration, and management processes for NextCloud and NextCloud Office services. Through its intuitive API interface, the workflow securely receives commands and orchestrates predefined tasks via SSH on your Docker-hosted server, ensuring streamlined operations and efficient management. Prerequisites You must deploy your own dedicated n8n server to manage workflows effectively. Alternatively, you may opt for the official n8n cloud-based solutions accessible via: n8n Official Site Your Docker server must be accessible via SSH with necessary permissions. Installation Steps Install the Required Workflow on n8n You can select from two convenient installation options: Option 1: Use the Latest Version from the n8n Marketplace The latest workflow templates are continuously updated and available on the n8n marketplace. Explore all templates provided by PUQcloud directly here: PUQcloud on n8n Option 2: Manual Installation Each module version includes a bundled workflow template file. Import this workflow file directly into your n8n server manually. n8n Workflow API Backend Setup for WHMCS Configure API Webhook and SSH Access Create a secure Basic Auth Credential for Webhook API interactions within n8n. Create an SSH Credential within n8n to securely communicate with the Docker host. Modify Template Parameters Adjust and update the following critical parameters to match your deployment specifics: server_domain – Set this to the domain of your WHMCS Docker server. clients_dir – Specify the directory where user data and related resources will be stored. mount_dir – The standard mount point for container storage (recommended to remain unchanged). Do not alter the following technical parameters to avoid workflow disruption: screen_left, screen_right. Deploy-docker-compose Configuration Fine-tune Docker Compose configurations tailored specifically for these critical operational scenarios: Initial service provisioning and setup Service suspension and subsequent unlocking Service configuration updates Routine service maintenance tasks nginx Configuration Management Enhance and customize proxy server configurations using the dedicated nginx workflow element: main**: Define specialized parameters within the server configuration block. main_location**: Set custom headers, caching policies, and routing rules for the root location. Bash Script Automation Automate Docker container management and related server tasks through dynamically generated Bash scripts within n8n. Scripts execute securely via SSH and provide responses in JSON or plain text formats for easy parsing and logging. Scripts are conveniently linked directly to the SSH action elements. You retain complete flexibility to adapt or extend these scripts as necessary to meet your precise operational requirements.

This n8n workflow automates lead extraction from Google Maps, enriches data with AI, and stores results for cold outreach. It uses the Bright Data community node and Bright Data MCP for scraping and AI message generation. How it works Form Submission User provides Google Maps starting location, keyword and country. Bright Data Scraping Bright Data community node triggers a Maps scraping job, monitors progress, and downloads results. AI Message Generation Uses Bright Data MCP with LLMs to create a personalized cold call script and talking points for each lead. Database Storage Enriched leads and scripts are upserted to Supabase. How to use Set up all the credentials, create your Postgres table and submit the form. The rest happens automatically. Requirements LLM account (OpenAI, Gemini…) for API usage. Bright Data account for API and MCP usage. Supabase account (or other Postgres database) to store information.

📡 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 > 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.

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 >5%, down >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://<your-n8n-host>/webhook/<path> 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.

Workflow documentation updated on 21 May 2025 This workflow keeps track of your brand mentions across different Facebook groups and provides an analysis of the posts as positive, negative or neutral and updates this to Googe sheets for further analysis This is useful and relevants for brands looking to keep track of what people are saying about their brands and guage the customer satisfaction or disatisfaction based on what they are talking about Who is this template for? This workflow is for you if You Need to keep track of your brand sentiments across different niche facebook groups Own a saas and want to monitor it across different local facebook Groups Are looking to do some competitor research to understand what others dont like about their products Are testing the market on different market offerings and products to get best results Are looking for sources other that review sites for product, software or service reviews Need to keep track of your brand sentiments across different niche facebook groups Are starting on market research and would like to get insights from differnt facebook groups on app usage, strngths weaknesses, features etc How it works You will set the desired schedule by which to monitor the groups This gets the brand names and facebook Groups to monitor. Setup Steps Before you begin You will need access to a Bright Data API to run this workflows Make a copy of the sheet below and add the urls for the facebook groups to scrap and the brand names you wish to monitor. Import the workflow json to your canvas Make a copy of this Google sheet to get started easily Set your APi key in the Map out the Google sheet to your tables You can use/update the current AI models to differnt models eg Gemini or anthropic Run the workflow Setup B Bright Data provides an option to receive the results on an external webhook via a POST call. This can be collected via the