by Cyril Nicko Gaspar
📌 HubSpot Lead Enrichment with Bright Data MCP This template enables natural-language-driven automation using Bright Data's MCP tools, triggered directly by new leads in HubSpot. It dynamically extracts and executes the right tool based on lead context—powered by AI and configurable in N8N. ❓ What Problem Does This Solve? Manual lead enrichment is slow, inconsistent, and drains valuable time. This solution automates the process using a no-code workflow that connects HubSpot, Bright Data MCP, and an AI agent—without requiring scripts or technical skills. Perfect for marketing, sales, and RevOps teams. 🧰 Prerequisites To use this template, you’ll need: A self-hosted or cloud instance of N8N A Bright Data MCP API token A valid OpenAI API key (or compatible AI model) A HubSpot account Either a Private App token or OAuth credentials for HubSpot Basic familiarity with N8N workflows ⚙️ Setup Instructions 1. Set Up Authentication in HubSpot 🔐 Option 1: Use a Private App Token (Simple Setup) Log in to your HubSpot account. Navigate to Settings → Integrations → Private Apps. Create a new Private App with the following scopes: crm.objects.contacts.read crm.objects.contacts.write crm.schemas.contacts.read crm.objects.companies.read (optional) Copy the Access Token. In N8N, create a credential for HubSpot App Token and paste the app token in the field. Go back to Hubspot Private App settings to setup a webhook. Copy the url in your workflow's Webhook node and paste it here. 🔁 Option 2: Use OAuth (Advanced + Secure) In HubSpot, go to Settings → Integrations → Apps → Create App. Set your Redirect URL to match your N8N OAuth2 redirect path. Choose scopes like: crm.objects.companies.read crm.objects.contacts.read crm.objects.deals.read crm.schemas.companies.read crm.schemas.contacts.read crm.schemas.deals.read crm.objects.contacts.write (conditionally required) Note the Client ID and Client Secret. Copy the App ID and the developer API key In N8N, create a credential for HubSpot Developer API and paste those info from previous step. Attach these credentials to the HubSpot node in N8N. 2. 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 API username and password string separated by colon (optional) 3. 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_AUTH=optional_browser_auth` 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_ZONE=optional_browser_zone_name` 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 4. Connect Google Sheets to N8N Ensure your Google Sheet: Contains columns like row_id, first_name, last_name, email, and status. Is shared with your N8N service account (or connected via OAuth) In N8N: Add a Google Sheets Trigger node Set it to watch for new rows in your lead sheet 5. Import and Configure the N8N Workflow Import the provided JSON workflow into N8N Update nodes with your credentials: Hubspot: Add your API key or connect it via OAuth. Google Sheets Trigger: Link to your actual sheet OpenAI Node: Add your API key Bright Data Tool Execution: Add Bright Data token and SSE URL 🔄 How It Works New contact in Hubspot or a new row is added to the Google Sheet N8N triggers the workflow AI agent classifies the task (e.g., “Find LinkedIn”, “Get company info”) The relevant MCP tool is called Results are appended back to the sheet or routed to another destination Rerun the specific record by specifying status "needs more enrichment", or leaving it blank. 🧩 Use Cases B2B Lead Enrichment** – Add missing fields (title, domain, social profiles) Email Intelligence** – Validate and enrich based on email Market Research** – Pull company or contact data on demand CRM Auto-fill** – Push enriched leads to tools like HubSpot or Salesforce 🛠️ Customization Prompt Tuning** – Adjust how the AI interprets input data Column Mapping** – Customize which fields to pull from the sheet Tool Logic** – Add retries, fallback tools, or confidence-based routing Destination Output** – Integrate with CRMs, Slack, or webhook endpoints ✅ Summary This template turns a Google Sheet into an AI-powered lead enrichment engine. By combining Bright Data’s tools with a natural language AI agent, your team can automate repetitive tasks and scale lead ops—without writing code. Just add a row, and let the workflow do the rest.
by Jonas
🎧 Daily RSS Digest & Podcast Generation This workflow automates the creation of a daily sports podcast from your favorite news sources. It fetches articles, uses AI to write a digest and a two-person dialogue, and produces a single, merged audio file with KOKORO TTS ready for listening. ✨ How it works: 📰 Fetch & Filter Daily News: The workflow triggers daily, fetches articles from your chosen RSS feeds, and filters them to keep only the most recent content. ✍️ Generate AI Digest & Script: Using Google Gemini, it first creates a written summary of the day's news. A second AI agent then transforms this news into an engaging, conversational podcast script between two distinct AI speakers. 🗣️ Generate Voices in Chunks: The script is split into individual lines of dialogue. The workflow then loops through each line, calling a Text-to-Speech (TTS) API to generate a separate audio file (an MP3 chunk) for each part of the conversation. 🎛️ Merge Audio with FFmpeg: After all the audio chunks are created and saved locally, a command-line script generates a list of all the files and uses FFmpeg to losslessly merge them into a single, seamless MP3 file. All temporary files are then deleted. 📤 Send the Final Podcast: The final, merged MP3 is read from the server and delivered directly to your Telegram chat with a dynamic, dated filename. You can modify: 📰 The RSS Feeds to any news source you want. 🤖 The AI Prompts to change the tone, language, or style of the digest and podcast. 🎙️ The TTS Voices used for the two speakers. 📫 The Final Delivery Method (e.g., send to Discord, save to Google Drive, etc.). Perfect for creating a personalized, hands-free news briefing to listen to on your commute. Inspired by: https://n8n.io/workflows/6523-convert-newsletters-into-ai-podcasts-with-gpt-4o-mini-and-elevenlabs/
by Anna Bui
🎯 LinkedIn ICP Lead Qualification Automation Automatically identify and qualify ideal customer prospects from LinkedIn post reactions using AI-powered profile analysis and intelligent data enrichment. Perfect for sales teams and marketing professionals who want to convert LinkedIn engagement into qualified leads without manual research. This workflow transforms post reactions into actionable prospect data with AI-driven ICP classification. Good to know LinkedIn Safety**: Only use cookie-free Apify actors to avoid account detection and suspension risks Daily Processing Limits**: Scrape maximum 1 page of reactions per day (50-100 profiles) to stay under LinkedIn's radar Apify actors cost approximately $0.01-0.05 per profile scraped - budget accordingly for daily processing Includes intelligent rate limiting to prevent API restrictions and maintain LinkedIn account safety AI classification requires clear definition of your Ideal Customer Profile criteria Processing too many profiles or running too frequently will trigger LinkedIn's anti-scraping measures Always monitor your LinkedIn account health and Apify usage patterns for any warning signs How it works Scrapes LinkedIn post reactions using Apify's specialized actor to identify engaged users Extracts and cleans profile data including names, job titles, and LinkedIn URLs Checks against existing Airtable records to prevent duplicate processing and save costs Creates new prospect records with basic information for tracking purposes Enriches profiles with comprehensive LinkedIn data including company details and experience Aggregates and formats profile data for AI analysis and classification Uses AI to analyze prospects against your ICP criteria with detailed reasoning Updates records with ICP classification results and extracted email addresses Implements smart batching and delays to respect API rate limits throughout the process How to use IMPORTANT**: Select cookie-free Apify actors only to avoid LinkedIn account suspension Set up Apify API credentials in both HTTP Request nodes for safe LinkedIn scraping Configure Airtable OAuth2 authentication and select your prospect tracking base Replace the LinkedIn post URL with your target post in the initial scraper node Daily Usage**: Process only 1 page of reactions per day (typically 50-100 profiles) maximum Customize the AI classification prompt with your specific ICP criteria and job titles Test with a small batch first to verify setup and monitor both API costs and LinkedIn account health Schedule workflow to run daily rather than processing large batches to maintain account safety Requirements Apify account with API access and sufficient credits for profile scraping Airtable account with OAuth2 authentication configured OpenAI or compatible AI model credentials for prospect classification LinkedIn post URL with reactions to analyze (minimum 10+ reactions recommended) Clear definition of your Ideal Customer Profile criteria for accurate AI classification Customising this workflow Safety First**: Always verify Apify actors are cookie-free before configuring to protect your LinkedIn account Modify ICP classification criteria in the AI prompt to match your specific target customer profile Set up daily scheduling (not hourly/frequent) to respect LinkedIn's usage patterns and avoid detection Adjust rate limiting delays based on your comfort level with LinkedIn scraping frequency Add additional data fields to Airtable schema for storing custom prospect information Integrate with CRM systems like HubSpot or Salesforce for automatic lead import Set up Slack notifications for new qualified prospects or daily summary reports Create email marketing sequences in tools like Mailchimp for nurturing qualified leads Add lead scoring based on company size, industry, or engagement level for prioritization Consider rotating between different LinkedIn posts to diversify your prospect sources while maintaining daily limits
by Hunyao
Note: This workflow assumes you already have your product’s Amazon reviews saved in a Google Sheet. If you still need those reviews, run my Amazon Reviews Scraper workflow first, then plug the resulting spreadsheet into this template. What it does Transforms any draft Google Doc into multiple high-converting sales pages. It blends Alex Hormozi’s value-stacking tactics with persona targeting based on Maslow’s Hierarchy of Needs, using your own customer reviews for proof and voice of customer (VOC). Perfect for • Growth and creative strategists • Freelance copywriters and agencies • Founders sharpening offers and funnels Apps used Google Sheets, Google Docs, LangChain OpenRouter LLM How it works Form Trigger collects Drive folder IDs, base copy URL and options. Workflow fetches the draft copy and product feature doc. It samples reviews, extracts VOC insights and maps them to Maslow needs. LLM drafts headlines and hooks following Hormozi’s \$100M Offers principles. Personas drive tone, objections and urgency in each copy variant. Loop writes one Google Doc per variant in your chosen folder. Customer analysis docs are saved to a second folder for reuse. Setup Share two Drive folders, copy the IDs (text after folders/). Paste each ID into Customer Analysis Folder ID and Advertorial Copy Folder ID. Provide File Name, Base copy (Google Docs URL) and Product Feature/USPs Doc. Optional: Reviews Sheet URL, Number of reviews to use, Target City. Set Number of Copies you need (1–20). Add Google Docs OAuth2 and Google Sheets OAuth2 credentials in n8n. If you have any questions in running the workflow, feel free to reach out to me at my youtube channel: https://www.youtube.com/@lifeofhunyao
by Hybroht
Source Discovery - Automatically Search More Up-to-Date Information Sources 🎬 Overview Version : 1.0 This workflow utilizes various nodes to discover and analyze potential sources of information from platforms like Google, Reddit, GitHub, Bluesky, and others. It is designed to streamline the process of finding relevant sources based on specified search themes. ✨ Features Automated source discovery from multiple platforms. Filtering of existing and undesired sources. Error handling for API requests. User-friendly configuration options. 👤 Who is this for? This workflow is ideal for researchers, content marketers, journalists, and anyone looking to efficiently gather and analyze information from various online sources. 💡 What problem does this solve? This workflow addresses the challenge of manually searching for relevant information sources, saving time and effort while ensuring that users have access to the most pertinent content. Ideal use-cases include: Resource Compilation for Academic and Educational Purposes Journalism and Research Content Marketing Competitor Analysis 🔍 What this workflow does The workflow gathers data from selected platforms through search terms. It filters out known and undesired sources, analyzes the content, and provides insights into potential sources relevant to the user's needs. 🔄 Workflow Steps 1. Search Queries Fetch sources using SerpAPI search, DuckDuckGo, and Bluesky. Utilizes GitHub repositories to find relevant links. Leverages RSS feeds from subreddits to identify potential sources. 2. Filtering Step Removes existing and undesired sources from the results. 3. Source Selection Analyzes the content of the identified sources for relevance. 📌 Expected Input / Configuration The workflow is primarily configured via the Configure Workflow Args (Manual) node or the Global Variables custom node. Search themes: Keywords or phrases relevant to the desired content. Lists of known sources and undesired sources for filtering. 📦 Expected Output A curated list of potential sources relevant to the specified search themes, along with insights into their content. 📌 Example ⚙️ n8n Setup Used n8n version:** 1.105.3 n8n-nodes-serpapi:** 0.1.6 n8n-nodes-globals:** 1.1.0 n8n-nodes-bluesky-enhanced**: 1.6.0 n8n-nodes-duckduckgo-search**: 30.0.4 LLM Model:** mistral-small-latest (API) Platform:** Podman 4.3.1 on Linux Date:** 2025-08-06 ⚡ Requirements to Use / Setup Self-hosted or cloud n8n instance. Install the following custom nodes: SerpAPI, Bluesky, and DuckDuckGo Search. n8n-nodes-serpapi n8n-nodes-duckduckgo-search n8n-nodes-bluesky-enhanced Install the Global Variables Node for enhanced configuration: n8n-nodes-globals (or use Edit Field (Set) node instead) Provide valid credentials to nodes for your preferred LLM model, SerpAPI, and Bluesky. Credentials for GitHub recommended. ⚠️ Notes, Assumptions \& Warnings Ensure compliance with the terms of service of any platforms accessed or discovered in this workflow, particularly concerning data usage and attribution. Monitor API usage to avoid hitting rate limits. The workflow may encounter errors such as 403 responses; in such cases, it will continue by ignoring the affected substep. Duplicate removal is applied, but occasional overlaps might still appear depending on the sources. This workflow assumes familiarity with n8n, APIs, and search engines. Using AI agents (Mistral or substitute LLMs) requires access to their API services and keys. This is not a Curator of News. It is designed to find websites that are relevant and useful to your searches. If you are looking for a relevant news selector, please check this workflow. ℹ️ About Us This workflow was developed by the Hybroht team. Our goal is to create tools that harness the possibilities of technology and more. We aim to continuously improve and expand functionalities based on community feedback and evolving use cases. For questions, reach out via contact@hybroht.com. ⚖️ Warranty & Legal Notice This free workflow is provided "as-is" without any warranties of any kind, either express or implied, including but not limited to the implied warranties of merchantability, fitness for a particular purpose, or non-infringement. By using this workflow, you acknowledge that you do so at your own risk. We shall not be held responsible for any damages, losses, or liabilities arising from the use or inability to use this workflow, including but not limited to any direct, indirect, incidental, or consequential damages. It is your responsibility to ensure that your use of this workflow complies with all applicable laws and regulations.
by ömerDrn
Automated Cryptocurrency Analysis & Reporting with Google Gemini and CoinGecko This powerful template is an n8n workflow that automates cryptocurrency market data analysis and delivers reports directly to your inbox. It fetches real-time data from CoinGecko API, generates AI-powered analysis, and sends the report via email. Features Scheduled Execution**: Runs automatically at a set time daily (default: 10:00 AM). Customizable Analysis**: Personalize analysis content/language via "AI Prompt" nodes. Easy Scalability**: Duplicate node groups to add more cryptocurrencies. Flexible AI Integration**: Defaults to Google Gemini, but supports ChatGPT/Ollama. Setup Instructions n8n Installation: Install n8n (self-hosted or Cloud version). Email Account Setup: Add email service credentials in n8n (e.g., Microsoft Outlook OAuth2). AI Model Credentials (Google Gemini): Obtain API key from Google AI Studio and add to n8n "Credentials". Import Template: Copy the JSON code into n8n as a new workflow. Customization Change Cryptocurrencies**: Update ids= parameter in HTTP Request nodes (e.g., ids=bitcoin). Edit AI Prompt**: Modify text in "AI Prompt" nodes. Use Different AI Model**: Replace Google Gemini with supported alternatives. Update Email Address**: Change recipient in "Send Mail" nodes. `
by Hunyao
What it does Automatically monitors multiple subreddits daily, identifies trending posts with high engagement, and delivers AI-powered summaries directly to your inbox. Never miss important discussions in your favorite communities again. Perfect for Investors tracking market sentiment, researchers monitoring industry discussions, content creators finding trending topics, or anyone wanting curated Reddit insights without endless scrolling. Apps used Reddit, OpenRouter (GPT-4o mini), Gmail How it works Triggers daily at your chosen time across all specified subreddits Fetches hot posts from the last 24 hours with scores above 30 upvotes Sorts posts by engagement score to prioritize trending content Extracts post content plus top-level comments for full context Generates concise AI summaries for each high-value thread Compiles summaries into a clean HTML email digest Delivers the digest to your Gmail inbox with clickable Reddit links Setup Configure these three essential settings: Schedule time: Set your preferred daily delivery time in the Schedule Trigger node. **Replace with your preferred hour (currently 6 AM). Note: Times display in your workflow timezone Topic and subreddits: In the "Set Topic, Subreddits and Email Address" node, **replace with your topic name (e.g., "Investing") and replace with your subreddit array (e.g., ["investing", "stocks"]) Email recipient: **Replace with your Gmail address in the same node Credentials Reddit OAuth2 for API access, OpenRouter API key for AI summaries, Gmail OAuth2 for email delivery If you have any questions in running the workflow, feel free to reach out to me at my youtube channel: https://www.youtube.com/@lifeofhunyao
by gotoHuman
Generate AI video clips to promote products, services or events on social media. Use gotoHuman as an interface to control and supervise each step of the workflow to create content that's actually worth posting. How it works gotoHuman will show the workflow steps that need approval or input in its' inbox and notify you via email or Slack. We choose from different topics for our post suggested by AI We select the image style, a product to show, and review an AI-generated tag line We use Fal.ai to generate an image that serves as a reference image for our video clip. And we use Cloudinary to add an overlay for the tag line. We review the image in gotoHuman and can iterate on it by retrying or even changing the prompt. We review the video clip that's generated with Fal.ai based on the approved image and can, again, retry or reprompt. How to set up Most importantly, install the gotoHuman node before importing this template! (Just add the node to a blank canvas before importing) Follow the instructions shown along the workflow and in the incl. video guide. You mainly need to set up your credentials for gotoHuman, OpenAI, Fal.ai and Cloudinary import the review templates with these IDs in gotoHuman: Z7V1jyImY1pho9eY039R,0GBaOCWd27tqV562kkCL,E2wlCVPWmk2UnLHVt4uu,DitPdbIapS4rBxBTIYGt,Z2T7nFwkXVFQlD6z50eV select these templates in the gotoHuman nodes do a quick setup for Cloudinary Requirements You need accounts for gotoHuman (human supervision) OpenAI (ideation) Fal.ai (image/video generation) Cloudinary (text overlay) How to customize Adjust/Replace the workflow triggers as needed Change the prompt in the topics generation node Replace the product image URLs used in the "gotoHuman - Content" node Adjust the available styles for image generation in the gotoHuman review template and the prompts they link to in the "Set Initial Image Prompt" node Adjust the prompt used for video generation in the "Set Initial Video Prompt" node If you want to use a different service/model for image and video generation, replace the nodes related to Fal.ai. Also, if you do not need a text overlay, remove the Cloudinary nodes.
by Nabin Bhandari
This n8n template uses AI to automatically classify incoming Gmail messages into five categories and route them to the right people or departments. It can also reply automatically and send WhatsApp alerts for urgent or relevant messages. This helps ensure high-priority emails never get missed, while other messages are handled efficiently. ##How It Works Trigger A new email in Gmail triggers the workflow. Classification (OpenAI GPT) The email is analyzed by an OpenAI GPT model and classified into one of: High Priority Customer Support Promotion Finance/Billing Random/Other Conditional Logic & Actions High Priority → Create draft reply + send WhatsApp alert. Customer Support → Auto-reply + send WhatsApp confirmation alert. Promotion → Summarize email + send WhatsApp promotional alert. Finance/Billing → Forward to finance team + send WhatsApp finance alert. Random/Other → Label and log only. Multi-Channel Output Responses are sent via Gmail. Alerts are sent via WhatsApp (or another compatible API). ##Setup Instructions Step 1: Gmail Authorization Add a Gmail node in n8n. Connect using OAuth2 and grant read/send permissions. Step 2: OpenAI API Key Get your API key from OpenAI. Add it to n8n credentials for the OpenAI node. Step 3: WhatsApp Integration Use your WhatsApp Business API or a provider like Twilio or 360Dialog. Replace placeholders with your details: [YOUR_WHATSAPP_NUMBER] [YOUR_FINANCE_TEAM_NUMBER] [YOUR_SUPPORT_TEAM_NUMBER] Step 4: Import & Run Import the workflow JSON into n8n. Adjust prompts, labels, and routing logic as needed. Execute and monitor results. ##Good to Know Fully customizable — add or remove categories, adjust responses, and change alert channels. Can be integrated with Slack, Discord, Trello, Notion, Jira, or CRM systems. Scales easily across teams and departments. ##Requirements Gmail account with OAuth2 credentials set up in n8n OpenAI API key for classification and content generation WhatsApp (or other messaging service) integration Optional: Slack, Notion, CRM, or accounting tool integrations ##Customization Ideas Create support tickets in Trello, Notion, or Jira from Customer Support emails. Sync Finance emails with QuickBooks, Stripe, or Google Sheets. Replace WhatsApp alerts with Slack or Discord messages. Use Zapier/Make for cross-platform automations.
by Angel Menendez
Who is this for? Public-facing professionals (developer advocates, founders, marketers, content creators) who get bombarded with LinkedIn messages that aren't actually for them - support requests when you're in marketing, sales inquiries when you're a devrel, partnership pitches when you handle content, etc. What problem is this workflow solving? When you're visible online, people assume you handle everything at your company. You end up spending hours daily playing human router, forwarding messages like "How do I reset my password?" or "What's your enterprise pricing?" to the right teams. This LinkedIn automation workflow stops you from being your company's unofficial customer service representative. What this workflow does This AI-powered LinkedIn DM management workflow automatically assesses incoming LinkedIn messages and routes them intelligently: Automated Message Assessment: Receives inbound LinkedIn messages via UniPile and looks up sender details from both personal and company LinkedIn profiles. Smart Route Matching: Compares the message content against your message routing workflow table in Notion, which contains: Question: "How can I become an n8n ambassador?" Description: "Route here when a user is requesting to become an n8n ambassador. Also when they're asking how they could do more to evangelize n8n in their city, or to start organizing n8n meetups and events in their city." Action: "Tell the user to open the following notion page which has details on ambassador program including how to apply, as well as perks of the program: https://www.notion.so/n8n-Ambassador-Program-d883b2a130e5448faedbebe5139187ea?pvs=21" AI Response Generation: When a message matches an existing route, this AI assistant generates a personalized response draft based on the "Action" instructions from your routing table. Human-in-the-Loop Approval: Sends the draft response to Slack with approve/reject buttons, so you maintain control while saving time. Draft can be edited from within Slack on desktop and mobile. Automated LinkedIn Responses: Once approved, sends the reply back via LinkedIn and marks the original message as handled. The result: You stop being a human switchboard and can focus on your actual job while people still get helpful, timely responses through automated customer service. You can also add routes for things you do handle but get asked about daily (like 'How do I join your beta?' or 'What's your content strategy?') to standardize your responses. Setup Sign up for a UniPile account and create a webhook under the Messaging section Set the callback URL to this workflow's production URL Generate a UniPile API key with all required scopes and store it in your n8n credentials Create a Slack app and enable interactive message buttons and webhooks Here is a slack App manifest template for easy deployment in slack: { "display_information": { "name": "Request Router", "description": "A bot that alerts when a new linkedin question comes in.", "background_color": "#12575e" }, "features": { "bot_user": { "display_name": "Request Router", "always_online": false } }, "oauth_config": { "scopes": { "bot": [ "chat:write", "chat:write.customize", "chat:write.public", "links:write", "im:history", "im:read", "im:write" ] } }, "settings": { "interactivity": { "is_enabled": true, "request_url": "Your webhook url here" }, "org_deploy_enabled": false, "socket_mode_enabled": false, "token_rotation_enabled": false } } Set up your Notion database with the three-column structure (Question, Description, Action) Configure the AI node with your preferred provider (OpenAI, Gemini, Ollama etc) Replace placeholder LinkedIn user and organization IDs with your own How to customize this workflow to your needs Database Options**: Swap Notion with Google Sheets, Airtable, or another database Filtering Logic**: Add custom filters based on keywords, message length, follower count, or business logic AI Customization**: Adjust the system prompt to match your brand tone and response goals Approval Platform**: Replace Slack with email, Discord, or another review platform Team Routing**: Use Slack metadata to route approvals to specific team members based on message category Enrichment**: Add secondary data enrichment using tools like Clearbit or FullContact Response Rules**: Create conditional logic for different response types based on sender profile or message content Perfect for anyone who's tired of being their company's accidental customer service department while trying to do their real job. This LinkedIn automation template was inspired by a live build done by Max Tkacz and Angel Menendez for The Studio.
by Garri
Description This workflow is designed to automate the security reputation check of domains and IP addresses using multiple APIs such as VirusTotal, AbuseIPDB, and Google DNS. It assesses potential threats including malicious and suspicious scores, as well as email security configurations (SPF, DKIM, DMARC). The analysis results are processed by AI to produce a concise assessment, then automatically updated into Google Sheets for documentation and follow-up. How It Works Automatic Trigger – The workflow runs periodically via a Schedule Trigger. Data Retrieval – Fetches a list of domains from Google Sheets with status "To do". Domain Analysis – Uses VirusTotal API to get the domain report, perform a rescan, and check IP resolutions. IP Analysis – Checks IP reputation using AbuseIPDB. Email Security Validation – Verifies SPF, DKIM, and DMARC configurations via Google DNS. AI Assessment – Analysis data is processed by AI to produce a short summary in Indonesian. Data Update – The results are automatically updated to Google Sheets, changing the status to "Done" or adding notes if potential threats are found. How to Setup Prepare API Keys Sign up and obtain API keys from VirusTotal and AbuseIPDB. Set up access to Google Sheets API. Configure Credentials in n8n Add VirusTotal API, AbuseIPDB API, and Google Sheets OAuth credentials in n8n. Prepare Google Sheets Create a sheet with columns No, Domain, Customer, Keterangan, Status. Ensure initial data has the status "To do". Import Workflow Upload the workflow JSON file into n8n. Set Schedule Trigger Define the checking interval as needed (e.g., every 1 hour). Test Run Run the workflow manually to ensure all API connections and Google Sheets output work properly.
by Intuz
This n8n template from Intuz provides a complete and automated solution for creating an autonomous social media manager. This workflow uses an AI agent to intelligently generate unique, high-quality content, check for duplicates, and post it on a consistent schedule to automate your entire Twitter presence. Who's this workflow for? Social Media Managers Marketing Teams & Agencies Startup Founders & Solopreneurs Content Creators How it works 1. Runs on a Schedule: The workflow automatically starts at a set interval (e.g., every 6 hours), ensuring a consistent posting schedule. 2. AI Generates a New Tweet: An advanced AI Agent, powered by OpenAI, uses a detailed prompt to craft a new, engaging tweet. The prompt defines the tone, topics, character limits, and hashtags. 3. Checks for Duplicates: Before finalizing the tweet, the AI Agent is equipped with a tool to read a Google Sheet containing a log of all previously published posts. This allows it to ensure the new content is always unique. 4. Posts to Twitter (X): The final, unique tweet is automatically posted to your connected Twitter account. 5. Logs the New Post: After posting, the workflow logs the new tweet back into the Google Sheet, updating the history for the next run. This completes the autonomous loop. Setup Instructions Schedule Your Posts: In the Start Workflow (Schedule Trigger) node, set the frequency you want the workflow to run (e.g., every 6 hours). Connect OpenAI: Add your OpenAI API key in the OpenAI Chat Model node. Customize the prompt in the AI Agent node to match your brand's voice, target keywords, and specific URLs. Configure Google Sheets: Connect your Google Sheets account. Create a sheet with two columns: Tweet Content and Status. In both the Get Data from Google Sheet and Add new Tweet to Google sheet nodes, select your credentials and specify the Document ID and Sheet Name. Connect Twitter (X): In the Create Tweet node, connect the Twitter account where you want to post. Activate Workflow: Save the workflow and toggle the "Active" switch to ON. Your AI social media manager is now live! Key Requirements to Use This Template Before you start, please ensure you have the following accounts and assets ready: An n8n Instance: An active n8n account (Cloud or self-hosted) where you can import and run this workflow. OpenAI Account: An active OpenAI account with an API Key. You will need to have billing enabled to use the language models for tweet generation. Google Account & Sheet: A Google account and a pre-made Google Sheet. The sheet must have two specific columns: Tweet Content and Status. Twitter (X) Developer Account: A Twitter (X) account with an approved Developer profile. You need an App created within the Developer Portal with the necessary permissions (v2 API access with Write scopes) to post tweets automatically. Connect with us Website: https://www.intuz.com/services Email: getstarted@intuz.com LinkedIn: https://www.linkedin.com/company/intuz Get Started: https://n8n.partnerlinks.io/intuz For Custom Worflow Automation Click here- Get Started