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Automated Twitter intelligence digest with Gemini 2.5 Pro to WhatsApp groups

Daniel Lianes Daniel Lianes
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2/3/2026
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Auto-scrape Twitter accounts to WhatsApp groups

This workflow provides automated access to real-time Twitter/X content through intelligent scraping and AI processing. It keeps you at the cutting edge of breaking news, emerging trends, and industry developments by eliminating the need to manually check multiple social media accounts and delivering curated updates directly to your communication channels.

Overview

This workflow automatically handles the complete Twitter monitoring process using advanced scraping techniques and AI analysis. It manages API authentication, multi-source data collection, intelligent content filtering, and message delivery with built-in error handling and rate limiting for reliable automation.

Core Function: Real-time social media monitoring that transforms Twitter noise into actionable intelligence, ensuring you're always first to know about the latest trends, product launches, and industry shifts that shape your field.

Key Capabilities

  • Real-time trend detection - Catch breaking news and emerging topics as they happen on X/Twitter
  • Multi-source Twitter monitoring - Track specific accounts AND trending keyword searches simultaneously
  • AI-powered trend analysis - Gemini 2.5 Pro filters noise and surfaces only the latest developments that matter
  • Stay ahead of the curve - Identify emerging technologies, viral discussions, and industry shifts before they go mainstream
  • Flexible delivery options - Pre-configured for WhatsApp, but easily adaptable for Telegram, Slack, Discord, or even blog content generation
  • Rate limit protection - Built-in delays and error handling using TwitterAPI.io's reliable, cost-effective infrastructure

Tools Used

  • n8n: The automation platform orchestrating the entire workflow
  • TwitterAPI.io: Reliable access to Twitter/X data without API complexities
  • OpenRouter: Gateway to advanced AI models for content processing
  • Gemini 2.5 Pro: Google's latest AI for intelligent content analysis and formatting
  • Evolution API: WhatsApp Business API integration for message delivery
  • Built-in Error Handling: Automatic retry logic and comprehensive error management

How to Install

IMPORTANT: Before importing this workflow, you need to install the Evolution API community node:

  1. Install Community Node First: Go to Settings > Community Nodes in your n8n instance
  2. Add Evolution API: Install n8n-nodes-evolution-api package
  3. Restart n8n: Allow the new nodes to load properly
  4. Import the Workflow: Download the .json file and import it into your n8n instance
  5. Configure Twitter Access: Set up TwitterAPI.io credentials and add target accounts/keywords
  6. Set Up AI Processing: Add your OpenRouter API key for Gemini 2.5 Pro access
  7. Configure WhatsApp: Set up Evolution API and add your target group ID
  8. Test & Deploy: Run a test execution and schedule for daily operation

Use Cases

  • Stay Ahead of Breaking News: Be the first to know about industry announcements, product launches, and major developments the moment they hit X/Twitter
  • Spot Trends Before They Explode: Identify emerging technologies, viral topics, and shifting conversations while they're still building momentum
  • Competitive Intelligence: Monitor what industry leaders, competitors, and influencers are discussing in real-time
  • Brand Surveillance: Track mentions, discussions, and sentiment around your brand as conversations develop
  • Content Creation Pipeline: Gather trending topics, viral discussions, and timely content ideas for blogs, newsletters, or social media strategy
  • Market Research: Collect real-time social sentiment and emerging market signals from X/Twitter conversations
  • Multi-platform Distribution: While configured for WhatsApp, the structured output can easily feed Telegram bots, Slack channels, Discord servers, or automated blog generation systems

FIND YOUR WHATSAPP GROUPS

The workflow includes a helper node to easily find your WhatsApp group IDs:

  1. Use the Fetch Groups node: The workflow includes a dedicated node that fetches all your available WhatsApp groups
  2. Run the helper: Execute just that node to see a list of all groups with their IDs
  3. Copy the group ID: Find your target group in the list and copy its ID
  4. Update the delivery node: Paste the group ID into the final WhatsApp sending node

Group ID format: Always ends with @g.us (example: 120363419788967600@g.us)

Pro tip: Test with a small private group first before deploying to your main team channels.

Connect with Me

  • LinkedIn: https://www.linkedin.com/in/daniel-lianes/
  • Discovery Call: https://cal.com/averis/asesoria
  • Consulting Session: https://cal.com/averis/consultoria-personalizada

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Automated Twitter Intelligence Digest with Gemini 2.5 Pro to WhatsApp Groups

This n8n workflow automates the process of generating a daily intelligence digest from Twitter (X) and sending it to a WhatsApp group. It leverages the power of Large Language Models (LLMs) to summarize and structure information, ensuring your team stays informed with key insights.

What it does

This workflow performs the following key steps:

  1. Schedules Execution: The workflow is triggered on a predefined schedule (e.g., daily) to initiate the intelligence gathering process.
  2. Fetches Twitter (X) Data: It makes an HTTP request to an external API (likely a Twitter scraper or a custom API) to retrieve relevant tweets or trending topics.
  3. Processes Raw Data: The raw data from the HTTP request is then processed and transformed using a Code node to extract and format the necessary information.
  4. Prepares for LLM: The extracted data is prepared for the LLM by setting specific fields and potentially aggregating information.
  5. Summarizes with LLM: The core of the intelligence gathering, a Basic LLM Chain (likely utilizing Gemini 2.5 Pro via OpenRouter), summarizes the Twitter data into a concise digest.
  6. Structures LLM Output: An Auto-fixing Output Parser and a Structured Output Parser ensure the LLM's output is well-formatted and adheres to a defined structure, making it easy to consume.
  7. Formats for WhatsApp: The summarized and structured intelligence is then formatted into a message suitable for WhatsApp.
  8. Sends to WhatsApp Group: Finally, the prepared message is sent to a designated WhatsApp group, delivering the daily intelligence digest to the intended recipients.
  9. Manages Rate Limits (Optional): A Wait node is included, likely to manage API rate limits or introduce delays between operations, ensuring smooth and reliable execution.

Prerequisites/Requirements

To use this workflow, you will need:

  • n8n Instance: A running n8n instance.
  • Twitter (X) Data Source: Access to an API or service that can provide Twitter (X) data (e.g., a custom scraper, a paid Twitter API, or a service like GetOldTweets3). The HTTP Request node will need to be configured with the correct endpoint and authentication.
  • OpenRouter Account & API Key: An OpenRouter API key to access the Gemini 2.5 Pro (or other configured) LLM.
  • WhatsApp Integration: A method to send messages to WhatsApp groups. This typically involves a WhatsApp Business API account or a third-party WhatsApp integration service. The final HTTP Request node will need to be configured for this service.
  • Basic JavaScript Knowledge: For customizing the Code node if specific data transformations are required beyond the current implementation.

Setup/Usage

  1. Import the Workflow: Download the JSON content of this workflow and import it into your n8n instance.
  2. Configure Credentials:
    • HTTP Request (Twitter Data): Update the HTTP Request node (ID: 19) with the URL, headers, and any authentication required for your Twitter (X) data source.
    • OpenRouter Chat Model: Configure the OpenRouter Chat Model node (ID: 1281) with your OpenRouter API key.
    • HTTP Request (WhatsApp): Update the final HTTP Request node (ID: 19) (or add a new one if the existing one is solely for Twitter) with the endpoint, headers, and body required to send messages to your WhatsApp group. This will depend on your chosen WhatsApp integration.
  3. Customize Data Processing: Review and adjust the Code node (ID: 834) and Edit Fields (Set) nodes (ID: 38) to ensure they correctly parse and prepare the Twitter data for the LLM based on your specific data source's output.
  4. Configure LLM Prompt: Adjust the prompt in the Basic LLM Chain node (ID: 1123) to guide Gemini 2.5 Pro on how to summarize and structure the intelligence digest according to your needs.
  5. Set Schedule: Configure the Schedule Trigger node (ID: 839) to run at your desired frequency (e.g., daily at a specific time).
  6. Activate the Workflow: Once all configurations are complete, activate the workflow.

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