🚀 RSS-MCP v3.0

Professional RSS Feed Management System with AI-Powered Analytics

Modern RSS/Atom feed aggregation and analysis tool built for Model Context Protocol (MCP), enabling AI assistants like Claude to manage and analyze news feeds with advanced features.

✨ Features

🎯 Core Features

• RSS Feed Management - Add, list, update, and delete RSS/Atom feeds
• Smart Search - Advanced filtering by keyword, category, date range
• Auto Updates - Automatic feed refresh with configurable scheduling
• SQLite Database - Persistent storage with optimized indexing

🤖 AI-Powered Analytics

• Sentiment Analysis - Detect positive/negative/neutral tone in articles
• Trend Detection - NLP-based topic clustering and trending keywords
• Auto-Categorization - Intelligent AI-based article classification
• Cross-Verification - Compare article coverage across multiple sources

🔔 Automation & Monitoring

• Webhook Notifications - Real-time alerts with keyword filtering
• Feed Scheduling - Cron-based automated updates
• Health Monitoring - Track feed uptime and performance
• Credibility Scoring - Assess feed reliability and quality

📊 Content & Export

• Daily Digest - Generate HTML/Markdown summary reports
• OPML Support - Import/export feed lists for easy migration
• Full Content Extraction - Web scraping for complete articles
• Multiple Export Formats - JSON, CSV, XML support

🚀 Quick Start

Automatic Setup (Recommended)

Windows:

FIRST_TIME_SETUP.bat
START_SERVER.bat

Linux/Mac:

npm run setup
chmod +x start_server.sh
./start_server.sh

Manual Setup

1. Install dependencies:

npm install

1. Start server (with auto-update):

npm run auto-start

1. Or start without updates:

npm start

Server will be available at:

• MCP Endpoint: http://localhost:3000/mcp
• Health Check: http://localhost:3000/health

📋 Available Tools (26)

• rss_add - Add new RSS/Atom feed
• rss_list - List all feeds
• rss_update - Update feeds (fetch new articles)
• rss_news - Get articles from specific feed
• rss_search - Advanced article search
• rss_delete - Remove feed

• rss_breaking - Breaking news detection
• rss_duplicates - Find duplicate articles
• rss_analytics - Feed statistics and metrics
• rss_trends - Trending topics analysis (NLP)
• rss_sentiment_analysis - Emotional tone detection

• rss_translate - AI-powered translation
• rss_media - Extract images and videos
• rss_full_content - Scrape full article content

• rss_compare - Compare feed coverage
• rss_cross_verify - Cross-source verification

• rss_export - Export to JSON/CSV/XML
• rss_daily_digest - Generate daily/weekly reports
• rss_opml - OPML import/export

• rss_recommend - Feed recommendations
• rss_auto_categorize - Auto categorization
• rss_credibility_score - Reliability scoring

• rss_notification_setup - Webhook alerts
• rss_bookmark - Reading list management
• rss_schedule - Automated scheduling
• rss_health_monitor - Feed health tracking

🔌 MCP Client Integration

Claude Desktop

Add to your Claude Desktop config:

Windows: %APPDATA%\Claude\claude_desktop_config.json
macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Linux: ~/.config/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "rss-mcp": {
      "command": "node",
      "args": [
        "node_modules/tsx/dist/cli.mjs",
        "src/index.ts"
      ],
      "cwd": "/path/to/RSS-MCP"
    }
  }
}

MCP Inspector (Testing)

npx @modelcontextprotocol/inspector
# Connect to: http://localhost:3000/mcp

💡 Usage Examples

With Claude

Add a feed:

"Add BBC News RSS feed: https://feeds.bbci.co.uk/news/rss.xml"

Analyze trends:

"Show me trending topics from the last 7 days"

Sentiment analysis:

"Analyze the sentiment of today's news"

Generate digest:

"Create a daily digest of top 10 articles in HTML format"

Schedule updates:

"Schedule BBC News to update every 6 hours"

🛠️ Development

npm run dev              # Development mode (watch)
npm run dev:http         # HTTP transport development
npm run build            # TypeScript compilation
npm run clean            # Clean build artifacts
npm run update-deps      # Update dependencies

📦 Tech Stack

• Runtime: Node.js 18+
• Language: TypeScript
• Database: SQLite (better-sqlite3)
• MCP SDK: @modelcontextprotocol/sdk
• NLP: natural, sentiment
• Web Scraping: cheerio
• Scheduling: cron-parser, node-cron
• Validation: Zod

🏗️ Project Structure

RSS-MCP/
├── src/
│   ├── database/          # Database schema & repositories
│   ├── services/          # Business logic (22 services)
│   ├── tools/             # MCP tools (26 tools)
│   ├── utils/             # Utilities
│   └── index.ts           # MCP server
├── data/                  # SQLite database (auto-created)
├── START_SERVER.bat       # Auto-update launcher (Windows)
├── start_server.sh        # Auto-update launcher (Linux/Mac)
├── FIRST_TIME_SETUP.bat   # Initial setup script
└── package.json

🔒 Security

• ✅ URL validation (HTTP/HTTPS only)
• ✅ Private IP blacklist
• ✅ MIME type validation
• ✅ Request timeout protection
• ✅ Domain-based rate limiting
• ✅ SQL injection protection (prepared statements)

📚 Documentation

• AUTO_UPDATE_GUIDE.md - Auto-update system guide
• MCP_CLIENT_GUIDE.md - MCP client setup
• CHANGELOG.md - Version history
• KURULUM_REHBERI.md - Installation guide (Turkish)

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

1. Fork the repository
2. Create your feature branch (git checkout -b feature/AmazingFeature)
3. Commit your changes (git commit -m 'Add some AmazingFeature')
4. Push to the branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgments

• Built with Model Context Protocol SDK
• Powered by Natural for NLP features
• Uses Cheerio for web scraping

📞 Support

• 🐛 Report Bug
• 💡 Request Feature
• 📖 Documentation

⭐ Star History

If you find this project useful, please consider giving it a star!

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