import { createHTTPServer } from "@leanmcp/core";

// Services are automatically discovered from ./mcp directory
await createHTTPServer({
  name: "sentiment-analysis-server",
  version: "1.0.0",
  port: 8080,
  cors: true,
  logging: true
});

console.log("\nSentiment Analysis MCP Server");

import { Tool, Optional, SchemaConstraint } from "@leanmcp/core";

// Define input schema as a TypeScript class
class AnalyzeSentimentInput {
  @SchemaConstraint({
    description: 'Text to analyze',
    minLength: 1
  })
  text!: string;

  @Optional()
  @SchemaConstraint({
    description: 'Language code',
    enum: ['en', 'es', 'fr', 'de'],
    default: 'en'
  })
  language?: string;
}

// Define output schema
class AnalyzeSentimentOutput {
  @SchemaConstraint({ enum: ['positive', 'negative', 'neutral'] })
  sentiment!: string;

  @SchemaConstraint({ minimum: -1, maximum: 1 })
  score!: number;

  @SchemaConstraint({ minimum: 0, maximum: 1 })
  confidence!: number;
}

export class SentimentService {
  @Tool({ 
    description: 'Analyze sentiment of text',
    inputClass: AnalyzeSentimentInput
  })
  async analyzeSentiment(args: AnalyzeSentimentInput): Promise<AnalyzeSentimentOutput> {
    const sentiment = this.detectSentiment(args.text);
    
    return {
      sentiment: sentiment > 0 ? 'positive' : sentiment < 0 ? 'negative' : 'neutral',
      score: sentiment,
      confidence: Math.abs(sentiment)
    };
  }

  private detectSentiment(text: string): number {
    // Simple keyword-based sentiment analysis
    const positiveWords = ['good', 'great', 'excellent', 'amazing', 'love'];
    const negativeWords = ['bad', 'terrible', 'awful', 'horrible', 'hate'];
    
    let score = 0;
    const words = text.toLowerCase().split(/\s+/);
    
    words.forEach(word => {
      if (positiveWords.includes(word)) score += 0.3;
      if (negativeWords.includes(word)) score -= 0.3;
    });
    
    return Math.max(-1, Math.min(1, score));
  }
}