Workflow Templates

How it works It’s very important to come prepared to Sales calls. This often means a lot of manual research about the person you’re calling with. This workflow delivers a summary of the latest social media activity (LinkedIn + X) for businesses you are about to interact with each day. Scans Your Calendar**: Each morning, it reviews your Google Calendar for any scheduled meetings or calls with companies based on each attendee email address. Fetches Latest Posts**: For each identified company, it fetches recent LinkedIn and X posts and summerizes them using AI to deliver a qucik overview for a busy sales rep. Delivers Insights**: You receive personalized emails via Gmail, each dedicated to a company you’re meeting with that day, containing a reminder of the meeting and a summary of company's recent social media activity. Setup steps The workflow requires you to have the following accounts set up in their respective nodes: Google Calendar GMail Clearbit OpenAI Besides those, you will need an account on the RapidAPI platform and subscribe to the following APIs: Fresh LinkedIn Profile Data Twitter Email example

Who is this for? This template is for sales teams, agencies, or local service providers who want to quickly generate cold outreach lists and automatically call local businesses with a Vapi AI assistant. It’s perfect for automating cold calls from scraped local listings with no manual dialing or research. What problem is this workflow solving? Finding leads and initiating outreach calls can be time-consuming. This workflow automates the process: it scrapes business listings from Google Maps using Dumpling AI, extracts phone numbers, filters out incomplete data, formats the numbers, and uses Vapi to make outbound AI-powered calls. Every call is logged in Google Sheets for follow-up and tracking. What this workflow does Starts manually and pulls search queries (e.g., "plumbers in Austin") from Google Sheets. Sends each query to Dumpling AI’s Google Maps scraping endpoint. Splits the returned business data into individual leads. Extracts key info like business name, website, and phone number. Filters to only keep leads with valid phone numbers. Formats phone numbers for Vapi dialing (adds +1). Calls each business using Vapi AI. Logs each successful call in a Google Sheet. Setup Google Sheets Setup Create a sheet with business search queries in the first column (e.g., best+restaurants+in+Chicago) Make sure the tab name is set and authorized in your credentials. Connect your Google Sheets account in the Get Search Keywords from Google Sheets node. Dumpling AI Setup Go to dumplingai.com Generate an API Key and connect it as a header token in the Scrape Google Map Businesses using Dumpling AI node Vapi Setup Sign into Vapi and create an assistant Get your assistantId and phoneNumberId Insert these into the JSON payload of the Initiate Vapi AI Call to Business node Add your Vapi API key to the credentials section Call Logging Create another tab in your sheet (e.g., “leads”) with these headers: company name phone number website This will be used in the Log Called Business Info to Sheet node How to customize this workflow to your needs Modify the business search terms in your Google Sheet to target specific industries or locations. Add filters to exclude certain businesses based on ratings, keywords, or location. Update your Vapi assistant script to match the type of outreach or pitch you’re using. Add additional integrations (e.g., CRM logging, Slack notifications, follow-up emails). Change the trigger to run on a schedule or webhook instead of manually. Nodes and Functions Breakdown Start Workflow Manually: Initiates the automation manually for testing or controlled runs. Get Search Keywords from Google Sheets: Reads search phrases from the spreadsheet. Scrape Google Map Businesses using Dumpling AI: Sends each search query to Dumpling AI and receives matching local business data. Split Each Business Result: Breaks the returned array of businesses into individual records for processing. Extract Business Name, Phone and website: Extracts title, phone, and website from each business record. Filter Valid Phone Numbers Only: Ensures only entries with a phone number move forward. Format Phone Number for Calling: Adds a +1 country code and strips non-numeric characters. Initiate Vapi AI Call to Business: Uses the business name and number to initiate a Vapi AI outbound call. Log Called Business Info to Sheet: Appends business details into a Google Sheet for tracking. Notes You must have valid API keys and authorized connections for Dumpling AI, Google Sheets, and Vapi. Make sure to handle API rate limits if you're running the workflow on large datasets. This workflow is optimized for US-based leads (+1 country code); adjust the formatting node if calling internationally.

⏱️ 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.

🕒 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.

📉 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.

Use Case Track all Linear tickets in Google sheets. Useful if you want to do some custom analysis but don't want to pay for Linear's Plus features (Linear Insights) or that it does not cover. Setup Add Linear API header key Add Google sheets creds Update which teams to get tickets from in Graphql Nodes Update which Google Sheets page to write all the tickets to You only need to add one column, id, in the sheet. Google Sheets node in automatic mapping mode will handle adding the rest of the columns. Set any custom data on each ticket Activate workflow 🚀 How to adjust this template Set any custom fields you want to get out of this, that you can quickly do in n8n.

📅 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.

Use Case When building a product it's important to discover and eliminate bugs as quickly as possible. Since we're using our product at n8n a lot, we wanted to make it as easy as possible for everyone to add bugs with the needed level of detail. That's why we built this workflow that allows everyone to add bugs to our Linear account easily directly from Slack What this workflow does This workflow waits for a webhook call within Slack, that gets fired when users use the /bug command on a bot that you will create as part of this template. It then adds the bug to Linear using a pre-defined description and a defined label. It then notifies the user about the newly added bug as you can see below: How to create your Slack bot Visit https://api.slack.com/apps, click on New App and choose a name and workspace. Click on OAuth & Permissions and scroll down to Scopes -> Bot token Scopes Add the chat:write scope Head over to Slash Commands and click on Create New Command Use /bug as the command Copy the test URL from the Webhook node into Request URL Add whatever feels best to the description and usage hint Go to Install app and click install Setup Configure your Slack bot using the sticky to the left Fill the Set me up node. You can find the IDs easily using the Helper nodes section Make sure to exchange the Request URL in your Slack with the Prod URL of the Webhook node before activating this workflow How to adjust it to your needs Add zero, one, two or many labels when creating the new ticket Change the Slack message according to your needs Change the default description for a new bug ticket Rename the Slack command as it works best for you How to enhance this workflow At n8n we use this workflow in combination with some others. E.g. we have the following things on top: We're using AI to classify the bugs and move them to the right team as soon as they get added to Linear (see this template) We also added other commands like /pain and /idea that allow us to submit other things to Notion. You can see the workflow for that here.

📰 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.

🛠️Setup Guide 'Get OVH Invoices to Google Sheets' Author: Oliver Bardenheier Who is this for? This Workflow is for all users who have services (Domains, BareMetal, VPS, Cloud, etc.) with Provider OVH.com (European API) It automatically retrieves invoice data, -files and puts the Data in a Google Spreadsheet for further processing. What problem is this workflow solving? / use case Currently the invoices from OVH do not come as an attachment via mail, it is just a link. So, the receiver has to be logged in to the ovh account to download the file. Even more effort if one is using 2FA. This workflow retrieves all information through the oauth2 token. What this workflow does This Workflow automatically retrieves invoice data, -files from Your OVH.com account and puts the Data in a Google Spreadsheet for further processing. It also saves the invoice PDF to a certain (yearly) folder in Your Google Drive. Setup Make a copy of this Google Sheet Template Set the timeframe for the query to Your likings in "Query Latest OVH Invoices" You could set an email trigger before and make the frame only one day. Log into Your OVH Account and get Your Credentials here Authentication using oAuth2 Authorization Code "Login with OVHcloud SSO" You need to Authorize OVHcloud API console If this worked fine You'll see a green text: "Access Token Received" Head over to the OVH API Console to get Your Token. Set Up Header Auth in the HTTP nodes: Authentication = Generic Credential Type Generic Auth Type = Header Auth Header Auth = Your OVH Header Credentials: -- a.) In every API Call in the console You'll find a curl example, just take the data from the line including: -H "authorization: Bearer eyJhxxxxxxxxxxxxxxxxxxxxxxxxxxxxx......" -- b.) Create a new Credential in n8n for the header auth. Put in the 'name' Field: authorization Copy Your Token including Bearer in the value field: 'Bearer eyJhxxxxxxxxxxxxxxxxxxxxxxxxxxxxx......' How to customize this workflow to your needs You can put in a mail trigger that activates on every incoming invoice mail from OVH. Adjusting the timeframe to get invoices from a certain time period, or remove the time variables completely to get ALL invoices.

Automating Person Data Enrichment and CRM Update Use Case This automation enriches a person’s professional profile using their name and work email, scores them against an ICP (Ideal Customer Profile), and updates their record in HubSpot. It’s ideal for sales, marketing, and recruitment teams needing reliable contact insights. What This Automation Does This automation performs the following using the input parameters: Person name**: The full name of the individual. Work email**: The professional email address of the contact. Airtop Profile (connected to LinkedIn)**: An authenticated Airtop Profile used for LinkedIn-based enrichment. Hubspot object id**: The internal HubSpot ID for the contact to be updated. How It Works Initiates the workflow using a form or external trigger. Uses the name and email to extract and enrich the person’s data, including: LinkedIn profile and company page About section, job title, location ICP score, seniority level, AI interest, technical depth, connection and follower counts Formats and maps the enriched data. Pushes the updated data to HubSpot using the object ID. Setup Requirements Airtop API Key Airtop Profile logged in to LinkedIn. HubSpot access with object ID field for each contact to update. Next Steps Combine with Lead Generation**: Use as part of an end-to-end workflow that sources leads and enriches them in real time. Trigger from CRM**: Initiate this workflow when a new contact is added in HubSpot or another CRM. Customize Scoring Logic**: Tailor the ICP calculation to your team’s specific criteria. Read more about person data enrichment

How it Works Disclaimer: This template is for self-hosted n8n instances only. This workflow is designed for developers, data analysts, and automation enthusiasts seeking to automate personalized news collection and delivery. It seamlessly combines n8n, OpenAI (e.g., GPT-4.1), and Bright Data’s Model Context Protocol (MCP) to collect, extract, and email the latest global news headlines. On a schedule or via a manual trigger, the workflow prompts an AI agent to gather fresh news. The agent leverages context-aware memory and integrated MCP tools to conduct both search engine queries and direct web page scraping in real time, delivering more than just meta search results—it extracts actual on-page headlines and trusted links. Results are formatted and delivered automatically by email via your SMTP provider, requiring zero manual effort once configured. Who is this for? Developers, data engineers, or automation pros wanting an AI-powered, fully automated newsfeed Teams needing up-to-date news digests from trusted global sources Anyone self-hosting n8n who wishes to combine advanced LLMs with real-time web data Setup Steps Setup time: Approx. 15–30 minutes (n8n install, API configuration, node setup) Requirements: Self-hosted n8n instance OpenAI API key Bright Data MCP account credentials SMTP/email provider details Install the community MCP node (n8n-nodes-mcp) for n8n and set up Bright Data MCP access. Configure these nodes: Schedule Trigger: For automated delivery at your chosen interval. Edit Fields: To inject your AI news collection prompt. AI Agent: Connects to OpenAI and MCP, enabled with memory for context. OpenAI Chat Model: Connects via your OpenAI credentials. MCP Clients: Configure at least two—one for search (e.g. search_engine) and one for scraping (e.g. scrape_as_markdown). Send Email: Set up with recipient and SMTP information. Credentials must be entered into their respective nodes for successful execution. Customization Guidance Prompt Tweaks:** Refine your AI news prompt to target specific genres, regions, or sources, or broaden/narrow the coverage as needed. Tool Configuration:** Carefully define tool descriptions and parameters in MCP client nodes so the agent can pick the best tool for each step (e.g., only scrape real news sites). Delivery Settings:** Adjust email recipient(s) and SMTP details as needed. Workflow Enhancements:** Use sticky notes in n8n for extended documentation, alternate prompts, or troubleshooting tips. Run Frequency:** Set schedule as needed—from hourly to daily updates. Once configured, this workflow will automatically gather, extract, and email curated news headlines and links—no manual curation required!