RSS-MCP
Professional RSS/Atom feed management system with AI-powered analytics including sentiment analysis, trend detection, auto-categorization, cross-source verification, automated scheduling, and content export capabilities.
README
🚀 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
- Install dependencies:
npm install
- Start server (with auto-update):
npm run auto-start
- 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)
<details> <summary><b>🔷 Basic Tools (6)</b></summary>
rss_add- Add new RSS/Atom feedrss_list- List all feedsrss_update- Update feeds (fetch new articles)rss_news- Get articles from specific feedrss_search- Advanced article searchrss_delete- Remove feed
</details>
<details> <summary><b>🔷 Advanced Analytics (5)</b></summary>
rss_breaking- Breaking news detectionrss_duplicates- Find duplicate articlesrss_analytics- Feed statistics and metricsrss_trends- Trending topics analysis (NLP)rss_sentiment_analysis- Emotional tone detection
</details>
<details> <summary><b>🔷 Content & Translation (3)</b></summary>
rss_translate- AI-powered translationrss_media- Extract images and videosrss_full_content- Scrape full article content
</details>
<details> <summary><b>🔷 Comparison & Verification (2)</b></summary>
rss_compare- Compare feed coveragerss_cross_verify- Cross-source verification
</details>
<details> <summary><b>🔷 Export & Reporting (3)</b></summary>
rss_export- Export to JSON/CSV/XMLrss_daily_digest- Generate daily/weekly reportsrss_opml- OPML import/export
</details>
<details> <summary><b>🔷 AI Features (3)</b></summary>
rss_recommend- Feed recommendationsrss_auto_categorize- Auto categorizationrss_credibility_score- Reliability scoring
</details>
<details> <summary><b>🔷 Management & Monitoring (4)</b></summary>
rss_notification_setup- Webhook alertsrss_bookmark- Reading list managementrss_schedule- Automated schedulingrss_health_monitor- Feed health tracking
</details>
🔌 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.
- Fork the repository
- Create your feature branch (
git checkout -b feature/AmazingFeature) - Commit your changes (
git commit -m 'Add some AmazingFeature') - Push to the branch (
git push origin feature/AmazingFeature) - 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
⭐ Star History
If you find this project useful, please consider giving it a star!
Made with ❤️ for the MCP community
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