mcp__gemini__analyze_intelligence - Gemini MCP

mcpgeminianalyze_intelligence

Analyze code for performance prediction, business impact, and trends. Generate quality metrics and assess project insights using comprehensive AI-powered code intelligence.

Instructions

Deep code analysis with performance prediction, business impact assessment, and trend analysis

Input Schema

TableJSON Schema

Name	Required	Description	Default
`analysis_type`	No	Analysis type	comprehensive
`generate_metrics`	No	Generate quality metrics
`include_business_impact`	No	Include business impact analysis
`performance_prediction`	No	Enable performance prediction
`target`	Yes	Code/project to analyze

Implementation Reference

src/tools/enhanced-tools.js:701-869 (handler)

The main handler function implementing the tool's logic: multi-layered AI analysis including architecture, code quality, security, optional business impact, performance prediction, and metrics storage.

    handler: async (args) => {
      const { target, analysis_type = 'comprehensive', include_business_impact = true, performance_prediction = true, generate_metrics = true } = args;
      validateString(target, 'target');
      
      const timer = performanceMonitor.startTimer('analyze_intelligence');
      
      // Multi-layered analysis
      const analysisPrompt = `Perform ${analysis_type} intelligence analysis:

Target: ${target}

Provide comprehensive analysis covering:

1. **Architecture Assessment**
   - Design patterns and principles
   - Structural quality and organization
   - Scalability considerations
   - Technology stack evaluation

2. **Code Quality Analysis**
   - Maintainability index
   - Complexity metrics
   - Technical debt assessment
   - Best practices compliance

3. **Security Posture**
   - Vulnerability assessment
   - Security pattern usage
   - Risk exposure areas
   - Compliance readiness

${performance_prediction ? `4. **Performance Intelligence**
   - Performance bottleneck prediction
   - Scalability limits
   - Resource utilization patterns
   - Optimization opportunities` : ''}

${generate_metrics ? `5. **Quality Metrics**
   - Quantitative quality scores
   - Trend analysis
   - Benchmark comparisons
   - Improvement vectors` : ''}

Be specific with actionable insights and recommendations.`;

      const coreAnalysis = await aiClient.call(analysisPrompt, 'analysis', { 
        complexity: 'complex',
        maxTokens: 4000 
      });
      
      let result = `📊 **Intelligence Analysis** (${analysis_type})

${coreAnalysis}`;

      // Business impact analysis
      if (include_business_impact) {
        const businessPrompt = `Analyze business impact for this technical assessment:

${coreAnalysis}

Provide:
1. **Financial Impact**
   - Development cost implications
   - Maintenance cost projections
   - Risk mitigation costs
   - ROI of improvements

2. **Operational Impact**
   - Performance implications
   - Reliability considerations
   - Scalability requirements
   - Support overhead

3. **Strategic Considerations**
   - Technology advancement alignment
   - Competitive positioning
   - Future-proofing assessment
   - Innovation opportunities

4. **Executive Summary**
   - Key business risks
   - Investment priorities
   - Timeline recommendations
   - Success metrics

Quantify impacts where possible with dollar estimates and timelines.`;

        const businessAnalysis = await aiClient.call(businessPrompt, 'analysis');
        
        result += `

---

💼 **Business Impact Analysis**

${businessAnalysis}`;
      }
      
      // Performance prediction
      if (performance_prediction) {
        const performancePrompt = `Create performance prediction model based on analysis:

${coreAnalysis}

Predict:
1. **Performance Bottlenecks**
   - Current performance issues
   - Future scalability limits
   - Resource constraints

2. **Load Scenarios**
   - Expected performance under load
   - Breaking points
   - Degradation patterns

3. **Optimization Impact**
   - Potential improvements
   - Implementation effort vs gain
   - Performance ROI

4. **Monitoring Strategy**
   - Key performance indicators
   - Early warning signals
   - Optimization triggers

Provide specific metrics and thresholds.`;

        const performancePrediction = await aiClient.call(performancePrompt, 'analysis');
        
        result += `

---

🚀 **Performance Prediction Model**

${performancePrediction}`;
      }
      
      // Save analysis to storage for trend tracking
      if (generate_metrics) {
        const analysisData = {
          id: Date.now().toString(),
          target,
          analysis_type,
          timestamp: new Date().toISOString(),
          analysis: coreAnalysis,
          business_impact: include_business_impact,
          performance_prediction: performance_prediction
        };
        
        const storageData = await storage.read('analyses');
        if (!storageData.analyses) storageData.analyses = [];
        storageData.analyses.push(analysisData);
        
        // Keep only last 100 analyses
        if (storageData.analyses.length > 100) {
          storageData.analyses = storageData.analyses.slice(-100);
        }
        
        await storage.write('analyses', storageData);
        
        result += `

**Analysis ID**: ${analysisData.id} (saved for trend tracking)`;
      }
      
      timer.end();
      return result;
    }

src/tools/enhanced-tools.js:694-700 (schema)

Input parameters schema defining the tool's expected arguments and their types/descriptions.

parameters: {
  target: { type: 'string', description: 'Code/project to analyze', required: true },
  analysis_type: { type: 'string', description: 'Analysis type', default: 'comprehensive' },
  include_business_impact: { type: 'boolean', description: 'Include business impact analysis', default: true },
  performance_prediction: { type: 'boolean', description: 'Enable performance prediction', default: true },
  generate_metrics: { type: 'boolean', description: 'Generate quality metrics', default: true }
},

src/tools/enhanced-tools.js:692-870 (registration)

The tool registration entry in the enhanced-tools object, including name, description, schema, and handler reference.

  'mcp__gemini__analyze_intelligence': {
    description: 'Deep code analysis with performance prediction, business impact assessment, and trend analysis',
    parameters: {
      target: { type: 'string', description: 'Code/project to analyze', required: true },
      analysis_type: { type: 'string', description: 'Analysis type', default: 'comprehensive' },
      include_business_impact: { type: 'boolean', description: 'Include business impact analysis', default: true },
      performance_prediction: { type: 'boolean', description: 'Enable performance prediction', default: true },
      generate_metrics: { type: 'boolean', description: 'Generate quality metrics', default: true }
    },
    handler: async (args) => {
      const { target, analysis_type = 'comprehensive', include_business_impact = true, performance_prediction = true, generate_metrics = true } = args;
      validateString(target, 'target');
      
      const timer = performanceMonitor.startTimer('analyze_intelligence');
      
      // Multi-layered analysis
      const analysisPrompt = `Perform ${analysis_type} intelligence analysis:

Target: ${target}

Provide comprehensive analysis covering:

1. **Architecture Assessment**
   - Design patterns and principles
   - Structural quality and organization
   - Scalability considerations
   - Technology stack evaluation

2. **Code Quality Analysis**
   - Maintainability index
   - Complexity metrics
   - Technical debt assessment
   - Best practices compliance

3. **Security Posture**
   - Vulnerability assessment
   - Security pattern usage
   - Risk exposure areas
   - Compliance readiness

${performance_prediction ? `4. **Performance Intelligence**
   - Performance bottleneck prediction
   - Scalability limits
   - Resource utilization patterns
   - Optimization opportunities` : ''}

${generate_metrics ? `5. **Quality Metrics**
   - Quantitative quality scores
   - Trend analysis
   - Benchmark comparisons
   - Improvement vectors` : ''}

Be specific with actionable insights and recommendations.`;

      const coreAnalysis = await aiClient.call(analysisPrompt, 'analysis', { 
        complexity: 'complex',
        maxTokens: 4000 
      });
      
      let result = `📊 **Intelligence Analysis** (${analysis_type})

${coreAnalysis}`;

      // Business impact analysis
      if (include_business_impact) {
        const businessPrompt = `Analyze business impact for this technical assessment:

${coreAnalysis}

Provide:
1. **Financial Impact**
   - Development cost implications
   - Maintenance cost projections
   - Risk mitigation costs
   - ROI of improvements

2. **Operational Impact**
   - Performance implications
   - Reliability considerations
   - Scalability requirements
   - Support overhead

3. **Strategic Considerations**
   - Technology advancement alignment
   - Competitive positioning
   - Future-proofing assessment
   - Innovation opportunities

4. **Executive Summary**
   - Key business risks
   - Investment priorities
   - Timeline recommendations
   - Success metrics

Quantify impacts where possible with dollar estimates and timelines.`;

        const businessAnalysis = await aiClient.call(businessPrompt, 'analysis');
        
        result += `

---

💼 **Business Impact Analysis**

${businessAnalysis}`;
      }
      
      // Performance prediction
      if (performance_prediction) {
        const performancePrompt = `Create performance prediction model based on analysis:

${coreAnalysis}

Predict:
1. **Performance Bottlenecks**
   - Current performance issues
   - Future scalability limits
   - Resource constraints

2. **Load Scenarios**
   - Expected performance under load
   - Breaking points
   - Degradation patterns

3. **Optimization Impact**
   - Potential improvements
   - Implementation effort vs gain
   - Performance ROI

4. **Monitoring Strategy**
   - Key performance indicators
   - Early warning signals
   - Optimization triggers

Provide specific metrics and thresholds.`;

        const performancePrediction = await aiClient.call(performancePrompt, 'analysis');
        
        result += `

---

🚀 **Performance Prediction Model**

${performancePrediction}`;
      }
      
      // Save analysis to storage for trend tracking
      if (generate_metrics) {
        const analysisData = {
          id: Date.now().toString(),
          target,
          analysis_type,
          timestamp: new Date().toISOString(),
          analysis: coreAnalysis,
          business_impact: include_business_impact,
          performance_prediction: performance_prediction
        };
        
        const storageData = await storage.read('analyses');
        if (!storageData.analyses) storageData.analyses = [];
        storageData.analyses.push(analysisData);
        
        // Keep only last 100 analyses
        if (storageData.analyses.length > 100) {
          storageData.analyses = storageData.analyses.slice(-100);
        }
        
        await storage.write('analyses', storageData);
        
        result += `

**Analysis ID**: ${analysisData.id} (saved for trend tracking)`;
      }
      
      timer.end();
      return result;
    }
  },

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