asmaamohamed0264/reddit-sentiment-mcp-server

Reddit Sentiment Analysis MCP Server 🚀

An enterprise-grade Reddit sentiment analysis server built with Claude AI and Model Context Protocol (MCP) that provides advanced sentiment analysis capabilities for business intelligence and product research.

🎯 Key Features

✅ Enterprise Ready: Production-grade server optimized for Dokploy deployment
✅ Claude AI Integration: Advanced sentiment analysis with reasoning capabilities
✅ Multi-subreddit Analysis: Analyze across multiple communities simultaneously
✅ Business Intelligence: Extract pain points, feature requests, and urgency levels
✅ Real-time Processing: Async architecture for high performance
✅ MCP Protocol: Full Model Context Protocol implementation
✅ REST API: Traditional REST endpoints alongside MCP
✅ Docker Optimized: Secure, lightweight container deployment

🚀 Quick Deploy to Dokploy

1. Create Application in Dokploy

• Create new project: reddit-sentiment-mcp
• Add new application: reddit-sentiment-server

2. Configure Git Repository

• Repository: https://github.com/asmaamohamed0264/reddit-sentiment-mcp-server.git
• Branch: main
• Build Type: dockerfile
• Port: 3000

3. Environment Variables

Add these environment variables in Dokploy:

# Reddit API Credentials (Required for full functionality)
REDDIT_CLIENT_ID=YJYHcDTzrPJ--F7vgOX4Fg
REDDIT_CLIENT_SECRET=your_reddit_secret_here
REDDIT_USER_AGENT=RedditSentimentBot/1.0 by YourUsername

# Claude AI Integration (Optional - falls back to rule-based analysis)
ANTHROPIC_API_KEY=your_anthropic_api_key_here

# Server Configuration
PORT=3000
HOST=0.0.0.0
ENVIRONMENT=production

4. Deploy

• Click Deploy in Dokploy
• Server will be available at your Dokploy domain

📊 API Usage

Health Check

GET /health

Sentiment Analysis

POST /analyze
Content-Type: application/json

{
  "query": "iPhone 15",
  "subreddits": ["technology", "apple", "iphone"],
  "time_filter": "week",
  "limit": 10,
  "use_claude": true,
  "product_context": "Apple iPhone 15 launch analysis",
  "return_full_data": false
}

Response Format

{
  "overview": {
    "total_posts_analyzed": 25,
    "analysis_method": "claude_ai",
    "query": "iPhone 15",
    "subreddits_searched": ["technology", "apple", "iphone"],
    "time_filter": "week"
  },
  "sentiment_breakdown": {
    "distribution": {"positive": 15, "negative": 5, "neutral": 5},
    "percentages": {"positive": "60.0%", "negative": "20.0%", "neutral": "20.0%"},
    "overall_sentiment": "positive"
  },
  "key_insights": {
    "top_themes": ["performance", "design", "price"],
    "main_pain_points": ["battery life", "price point"],
    "top_feature_requests": ["better camera", "longer battery"]
  },
  "business_metrics": {
    "urgent_issues": 2,
    "high_impact_items": 4,
    "business_impact": "Generally positive reception with specific improvement areas identified"
  }
}

🔧 MCP Integration

This server implements the Model Context Protocol and can be used with Claude Desktop or other MCP clients:

{
  "mcpServers": {
    "reddit-sentiment": {
      "command": "npx",
      "args": ["-c", "curl -X POST https://your-dokploy-domain.com/analyze"],
      "env": {}
    }
  }
}

🎯 Business Applications

Product Management

• Feature Prioritization: Based on user feedback volume and sentiment
• Competitive Analysis: Track brand mentions and sentiment
• Release Impact: Monitor sentiment changes after product launches

Customer Success

• Proactive Issue Identification: Early warning through pain point analysis
• Support Optimization: Prevent tickets via community sentiment monitoring
• Satisfaction Tracking: Monitor customer satisfaction across product updates

Marketing Intelligence

• Brand Perception: Monitor brand sentiment across relevant communities
• Campaign Effectiveness: Measure sentiment shifts during campaigns
• Influencer Identification: Find high-impact feedback and discussions

🏗️ Technical Architecture

• FastAPI: High-performance async web framework
• AsyncPRAW: Async Reddit API wrapper for optimal performance
• Claude AI: Advanced sentiment analysis with reasoning
• MCP Protocol: Standard AI assistant integration
• Docker: Secure containerized deployment
• Health Checks: Dokploy-optimized monitoring

🔒 Security Features

• Non-root container user
• Environment-based configuration
• Input validation with Pydantic
• Rate limiting and timeout protection
• Secure API key handling

🚧 Advanced Configuration

Custom Docker Build

docker build -t reddit-sentiment-mcp .
docker run -p 3000:3000 \
  -e REDDIT_CLIENT_ID=your_id \
  -e REDDIT_CLIENT_SECRET=your_secret \
  -e ANTHROPIC_API_KEY=your_key \
  reddit-sentiment-mcp

Local Development

git clone https://github.com/asmaamohamed0264/reddit-sentiment-mcp-server.git
cd reddit-sentiment-mcp-server
pip install -r requirements.txt
cp .env.example .env
# Edit .env with your credentials
python server.py

📈 Performance & Limits

• Concurrent Requests: Async architecture supports high concurrency
• Reddit API: Respects Reddit rate limits (60-100 requests/minute)
• Claude AI: Optimized prompts for cost-effective analysis
• Memory Usage: ~50MB base, scales with request volume
• Response Time: ~2-5 seconds for typical analysis

🤝 Support & Contributing

• Issues: GitHub Issues
• Documentation: This README and inline code comments
• License: MIT - Use it however you want!

🏆 Why This Server?

Enterprise Grade: Built for production use with proper error handling, logging, and monitoring.

AI-Powered: Uses Claude AI for sophisticated sentiment analysis beyond simple keyword matching.

Dokploy Optimized: Specifically designed for seamless Dokploy deployment with health checks and proper containerization.

Full-Stack: Provides both MCP protocol integration AND REST API for maximum flexibility.

Business Focused: Extracts actionable business intelligence, not just sentiment scores.

Built with ❤️ for the MCP community and optimized for Dokploy deployment