Gemini MCP

Instructions

Implementation Reference

• src/tools/business-tools.js:383-502 (handler)

  The main handler function executing the tool's logic: destructures args, validates input, loads historical data, generates AI prompt for quality analysis, calls AI client, simulates/computes quality score and trend, saves metrics, generates alerts, and formats/returns the report.
  handler: async (args) => { const { project_path, quality_aspects = ['code_quality', 'performance', 'security', 'maintainability'], monitoring_frequency = 'daily', alert_thresholds = {} } = args; validateString(project_path, 'project_path'); const timer = performanceMonitor.startTimer('quality_guardian'); // Load historical quality data const historicalData = await storage.read('quality_metrics'); const projectHistory = historicalData.projects?.[project_path] || []; const qualityPrompt = `Analyze current quality status and create monitoring framework: **Project**: ${project_path} **Quality Aspects**: ${quality_aspects.join(', ')} **Monitoring Frequency**: ${monitoring_frequency} Based on historical trends: ${projectHistory.length} previous measurements Create comprehensive quality assessment: 1. **Current Quality Baseline** ${quality_aspects.map(aspect => `- **${aspect}**: Current status and measurement`).join('\n ')} 2. **Quality Trends Analysis** - Historical performance patterns - Quality improvement/degradation trends - Correlation analysis between metrics - Seasonal or cyclical patterns 3. **Predictive Quality Model** - Quality trajectory predictions - Risk factors identification - Early warning indicators - Quality degradation alerts 4. **Monitoring Framework** - Automated quality checks - Continuous monitoring setup - Alert configuration and thresholds - Quality gate definitions 5. **Improvement Recommendations** - Priority quality issues - Improvement action plan - Resource allocation guidance - Success measurement criteria Provide specific metrics, thresholds, and actionable insights.`; const qualityAnalysis = await aiClient.call(qualityPrompt, 'analysis', { complexity: 'complex', maxTokens: 4000 }); // Generate quality score and trends const currentQualityScore = Math.random() * 40 + 60; // Simulate score 60-100 const trend = projectHistory.length > 0 ? (currentQualityScore - projectHistory[projectHistory.length - 1].score) : 0; // Save current measurement const qualityMeasurement = { timestamp: new Date().toISOString(), score: currentQualityScore, aspects: quality_aspects, monitoring_frequency, analysis: qualityAnalysis.substring(0, 1000) // Store summary }; if (!historicalData.projects) historicalData.projects = {}; if (!historicalData.projects[project_path]) historicalData.projects[project_path] = []; historicalData.projects[project_path].push(qualityMeasurement); // Keep only last 100 measurements per project if (historicalData.projects[project_path].length > 100) { historicalData.projects[project_path] = historicalData.projects[project_path].slice(-100); } await storage.write('quality_metrics', historicalData); // Generate alerts if needed const alerts = []; if (currentQualityScore < 70) { alerts.push('🔴 Quality Score Below Threshold (70)'); } if (trend < -5) { alerts.push('📉 Quality Declining Rapidly'); } if (projectHistory.length > 5) { const recentScores = projectHistory.slice(-5).map(m => m.score); const avgRecent = recentScores.reduce((a, b) => a + b, 0) / recentScores.length; if (currentQualityScore < avgRecent - 10) { alerts.push('⚠️ Quality Drop Detected'); } } timer.end(); return `🛡️ **Quality Guardian Report** (${monitoring_frequency}) **Project**: ${project_path} **Quality Score**: ${currentQualityScore.toFixed(1)}/100 ${trend > 0 ? '📈' : trend < 0 ? '📉' : '➡️'} (${trend > 0 ? '+' : ''}${trend.toFixed(1)}) **Monitoring**: ${quality_aspects.join(', ')} ${alerts.length > 0 ? `\n🚨 **Active Alerts**\n${alerts.map(alert => `- ${alert}`).join('\n')}\n` : '✅ **No Critical Issues Detected**\n'} --- 📊 **Quality Analysis** ${qualityAnalysis} --- 📈 **Historical Trends** (Last ${Math.min(projectHistory.length, 10)} measurements) ${projectHistory.slice(-10).map((m, i) => `${i + 1}. ${new Date(m.timestamp).toLocaleDateString()}: ${m.score.toFixed(1)}/100`).join('\n')} **Measurement saved for continuous monitoring and trend analysis.**`; }
• src/tools/business-tools.js:376-382 (schema)

  Tool description and input parameters schema defining the expected arguments: project_path (required), quality_aspects (array), monitoring_frequency, alert_thresholds.
  description: 'Continuous quality monitoring and trend analysis with predictive quality metrics', parameters: { project_path: { type: 'string', description: 'Project path or identifier', required: true }, quality_aspects: { type: 'array', description: 'Quality aspects to monitor', default: ['code_quality', 'performance', 'security', 'maintainability'] }, monitoring_frequency: { type: 'string', description: 'Monitoring frequency', default: 'daily' }, alert_thresholds: { type: 'object', description: 'Alert threshold configuration' } },
• src/tools/registry.js:244-248 (registration)

  The registerToolsFromModule method that iterates over the businessTools module (including quality_guardian) and registers each tool by calling registerTool with name, description, parameters, handler.
  registerToolsFromModule(toolsModule) { Object.entries(toolsModule).forEach(([name, tool]) => { this.registerTool(name, tool.description, tool.parameters, tool.handler); }); }
• src/tools/registry.js:238-238 (registration)

  Specific registration call for the businessTools module containing the mcp__gemini__quality_guardian tool.
  this.registerToolsFromModule(businessTools);
• src/tools/registry.js:8-8 (registration)

  Import of the businessTools module that defines the quality_guardian tool.
  import { businessTools } from './business-tools.js';