mcp-context-engineering/src/context/ResearchEngine.ts

The intelligent context optimization system for AI coding assistants. Built with Cole's PRP methodology, Context Portal knowledge graphs, and production-ready MongoDB architecture.

/**
 * Research Engine - Simplified implementation for real testing
 */
export class ResearchEngine {
  async conductResearch(query: string, depth: 'basic' | 'comprehensive' | 'exhaustive' = 'comprehensive'): Promise<string[]> {
    // Simplified research simulation
    const baseResults = [
      `Research finding for "${query}": Best practices analysis`,
      `Technical implementation patterns for ${query}`,
      `Performance considerations and optimization strategies`,
    ];
    
    if (depth === 'comprehensive') {
      baseResults.push(
        `Advanced architectural patterns for ${query}`,
        `Integration examples and real-world implementations`
      );
    }
    
    if (depth === 'exhaustive') {
      baseResults.push(
        `Cutting-edge innovations in ${query}`,
        `Cross-platform compatibility analysis`,
        `Future-proofing strategies and emerging trends`
      );
    }
    
    return baseResults;
  }
  
  async analyzeCodebase(techStack: string[]): Promise<string> {
    return `Codebase analysis for tech stack: ${techStack.join(', ')}. 
    Identified patterns: component-based architecture, modern tooling, type safety focus.`;
  }
}