AI News Agent: A Multi-Source News Auto-Summarization and Delivery System Based on n8n

This is an AI-driven news automation system based on n8n workflows. By integrating RSS feeds, Gemini summarization, and automatic email delivery, it enables automatic daily news acquisition, intelligent summarization, and precise delivery. Designed specifically for self-hosted environments to ensure privacy protection and reliable execution. Original author/maintainer: Tanvianejaa. The project is open-sourced on GitHub with the original title AI-News-Agent-Automated-Multi-Source-News-Summarizer. Link: https://github.com/Tanvianejaa/AI-News-Agent-Automated-Multi-Source-News-Summarizer. Update time: 2026-05-23T14:15:41Z.

In today's information explosion, manually filtering and reading news has become impractical. Existing news aggregation services have the following issues:

• Information overload: Too much irrelevant content is pushed
• Privacy risks: Commercial services may misuse user data
• Lack of personalization: One-size-fits-all pushes cannot meet individual interests
• Inconsistent summary quality: Automatic summaries lack focus and readability

The AI-News-Agent project aims to solve these problems by providing a self-hosted solution that allows users to fully control their news consumption experience.

Tech Stack Selection

• n8n Workflow Engine: Visual design, rich integrations, self-host friendly, active community
• Gemini Large Language Model: Multilingual support, long context window, structured output, cost-effective
• RSS Feeds: Standardized format, real-time updates, diverse sources, lightweight and efficient

Workflow Details

Divided into three stages:

1. News Acquisition: Configure multi-domain RSS feeds for scheduled polling, auto-deduplication, extract metadata and full text
2. Intelligent Summarization: Filter irrelevant content, generate optimized summaries with Gemini (control length, extract key points)
3. Automatic Delivery: Design email templates, scheduled batch delivery, support personalized settings (subject, summary length, delivery time)

Multi-Source Aggregation

Supports RSS feeds from tech (TechCrunch, etc.), international (BBC, etc.), finance (Bloomberg, etc.) and vertical fields

Intelligent Filtering

• Keyword filtering: Include/exclude keywords, weight scoring
• Deduplication mechanism: Cross-source deduplication, similarity detection, avoid duplicates via historical records

High-Quality Summaries

Advantages of Gemini generative summaries: Context understanding, no copyright issues, controllable length, multilingual support; Summary quality assurance includes key information integrity check, fact consistency verification

Privacy Protection

• Self-hosted architecture: Local data processing, independent API key management
• Data minimization: Only store necessary data, regular cleanup
• Open-source transparency: Auditable code, no hidden data collection

Application Scenarios

• Personal Subscription: Tech practitioners track trends, investors monitor markets, researchers follow academic progress
• Team Sharing: Enterprise intelligence summary, team learning material delivery
• Content Creators: Topic reference, material organization

Deployment Guide

• Environment requirements: Docker/Node.js, email server, Gemini API key
• Steps: Clone repository → Configure environment variables → Import n8n workflow → Set RSS feeds and scheduled tasks → Start service
• Personalized configuration: Manage RSS feeds, set summary preferences, adjust delivery parameters

Limitations

• Content quality depends on RSS feed quality
• Summaries may misinterpret meaning, miss information, or generate inaccurate statements
• Personalization only based on keywords, no deep user profiles

Improvement Directions

• Intelligent source discovery: Auto-evaluate high-quality RSS feeds
• User feedback learning: Optimize recommendations based on clicks
• Multi-modal support: Image/video content summarization
• Collaboration features: Multi-user shared annotations

The AI-News-Agent project combines n8n workflows and large language models to solve the pain point of information overload and enable efficient acquisition of valuable content. Its greatest value lies in the self-hosted and open-source features, allowing users to control their information consumption. It is an ideal solution for tech users who care about privacy and want to customize their news processes. As LLM capabilities improve and costs decrease, such AI automation tools will become more popular, and this project provides an excellent reference implementation for similar applications.