Skip to main content
Glama
by Coder-RL
SESSION_START.md78.3 kB
# 🚀 Claude_MCPServer Session 1 Start - COMPREHENSIVE CONTEXT **Date**: 2025-05-23 **Time**: 11:29:57 **Project**: Claude_MCPServer **Type**: Node.js **Version**: 0.11.0 0.11.0 (from package.json) **Path**: /Users/robertlee/GitHubProjects/Claude_MCPServer **Developer**: Human **AI Assistant**: Claude Code > **OBJECTIVE**: Show, don't tell, and assume nothing. This document provides complete context for a new developer to understand exactly where we are and continue productively. ## 📋 SESSION OVERVIEW - CRITICAL STATUS ### 🔄 Current System State | Component | Status | Details | Evidence | |-----------|--------|---------|----------| | Git Repository | ✅ Active | Branch: main | [Git Analysis](docs/command_outputs/git/) | | Project Type | ✅ Node.js | Framework: None, Build: None | [Project Analysis](docs/command_outputs/environment/project_analysis.md) | | Dependencies | ✅ Configured | Package Manager: npm | [Environment Info](docs/command_outputs/environment/system_info.md) | | Build System | ⚠️ None detected | Last Status: See evidence | [Build Status](docs/command_outputs/build/build_test_status.md) | | Running Services | ✅ Active | Alternative Backend:8080 Admin/Monitoring:9000 | [Service Status](docs/command_outputs/services/service_status.md) | ### 🏗️ Work in Progress - **Current Task**: - **Last Session**: - **Recent File Changes**: ``` servers/attention-mechanisms/src/attention-pattern-analyzer.ts servers/shared/base-server.ts tests/performance/performance-tests.js tests/run-tests.js ``` ### 📅 Project Timeline & Activity - **Current Session**: Session 1 on 2025-05-23 ( 0 previous sessions) - **Git Branch**: main - **Last Commit**: 9944e73 - Commit v2 20250522 Augment Code - **Recent Activity**: 10 commits in past week - **Sync Status**: 0 commits ahead, 0 commits behind origin - **Last Known Working State**: ### 📊 PROJECT HEALTH BASELINE (EXPECTED vs ACTUAL) | Component | Expected | Current Status | Match? | |-----------|----------|----------------|---------| | Dependencies | ✅ Installed | ✅ Present | ✅ | | Build | ✅ Success | ❌ Failed/Unknown | ❌ | | Tests | ✅ Passing | ❌ Failing/Unknown | ❌ | | Dev Server | ✅ Running | ✅ Active | ✅ | | Git Status | ✅ Clean/Synced | ✅ Synced | ✅ | **Overall Health**: 🟡 NEEDS ATTENTION (3/5 components working) ## 📊 VISUAL STATE EVIDENCE ### Current Git State (EXACT) ```bash M SESSION_START.md M docs/command_outputs/environment/system_info.md M docs/command_outputs/errors/error_analysis.md M docs/command_outputs/git/branch_info.md M docs/command_outputs/git/current_diff.md M docs/command_outputs/git/recent_commits.md M docs/command_outputs/services/service_status.md ``` ### Live Service Check Results ``` | Port | Service Type | Status | Process | Response Check | |------|-------------|--------|---------|----------------| | 3000 | React/Node Dev Server | ❌ Not Running | None | N/A | | 3001 | Alternative Dev Server | ❌ Not Running | None | N/A | | 3101 | Custom Frontend | ❌ Not Running | None | N/A | | 4000 | Development Server | ❌ Not Running | None | N/A | | 5000 | Flask/Python Dev | ❌ Not Running | None | N/A | | 5173 | Vite Dev Server | ❌ Not Running | None | N/A | | 8000 | Backend API/Django | ❌ Not Running | None | N/A | | 8080 | Alternative Backend | ✅ Running | nginx (PID: 11261) | ✅ HTTP Responding + /health | | 8081 | Proxy/Alternative | ❌ Not Running | None | N/A | | 9000 | Admin/Monitoring | ✅ Running | php-fpm (PID: 2396) | N/A | ## Service Response Examples ### Port 8080 Response ```bash $ curl -s --max-time 5 http://localhost:8080 <!DOCTYPE html> <html> <head> <title>Welcome to nginx!</title> ``` ### Build Status (ACTUAL RESULTS) ```bash test/week-11-simple.test.ts:65:4639 - error TS1127: Invalid character. 65 ]),\n callTool: jest.fn().mockResolvedValue({ metricsCount: 10 }),\n createWindow: jest.fn().mockResolvedValue({\n isProcessing: () => true,\n getResults: () => [{ count: 100, sum: 5000, avg: 50 }]\n }),\n configureAlert: jest.fn().mockResolvedValue({\n id: 'alert-123',\n isActive: true\n })\n }))\n };\n});\n\njest.mock('../servers/data-analytics/src/data-warehouse', () => {\n return {\n DataWarehouseServer: jest.fn().mockImplementation(() => ({\n start: jest.fn().mockResolvedValue(true),\n stop: jest.fn().mockResolvedValue(true),\n runETL: jest.fn().mockResolvedValue({\n status: 'completed',\n recordsProcessed: 5000,\n executionTime: 15000\n }),\n loadData: jest.fn().mockResolvedValue({ rowsInserted: 1000 }),\n executeQuery: jest.fn().mockResolvedValue({\n rows: [{ total_events: 1000 }],\n rowCount: 1,\n executionTime: 2500\n }),\n listTools: jest.fn().mockResolvedValue([\n { name: 'run_etl', description: 'Execute ETL pipelines' },\n { name: 'execute_query', description: 'Run analytical queries' },\n { name: 'create_table', description: 'Create optimized tables' },\n { name: 'manage_partitions', description: 'Manage table partitions' },\n { name: 'optimize_indexes', description: 'Optimize database indexes' },\n { name: 'backup_data', description: 'Backup warehouse data' }\n ]),\n callTool: jest.fn().mockResolvedValue({ result: { rows: [{ total_events: 1000 }] } }),\n createOptimizedTable: jest.fn().mockResolvedValue({\n isPartitioned: true,\n indexes: ['user_id', 'event_type'],\n compressionRatio: 0.65\n })\n }))\n };\n});\n\njest.mock('../servers/data-analytics/src/ml-deployment', () => {\n return {\n MLDeploymentServer: jest.fn().mockImplementation(() => ({\n start: jest.fn().mockResolvedValue(true),\n stop: jest.fn().mockResolvedValue(true),\n deployModel: jest.fn().mockResolvedValue({\n status: 'active',\n endpoint: 'http://localhost:8113/models/user_churn_predictor',\n healthCheck: () => Promise.resolve(true)\n }),\n predict: jest.fn().mockResolvedValue({\n probability: 0.75,\n confidence: 0.92,\n responseTime: 45\n }),\n getModelMetrics: jest.fn().mockResolvedValue({\n accuracy: 0.89,\n latency: { p95: 120 },\n drift: { score: 0.05 },\n requestCount: 1500\n }),\n listTools: jest.fn().mockResolvedValue([\n { name: 'deploy_model', description: 'Deploy ML models for inference' },\n { name: 'predict', description: 'Run model predictions' },\n { name: 'monitor_model', description: 'Monitor model performance' },\n { name: 'update_model', description: 'Update deployed models' },\n { name: 'scale_deployment', description: 'Scale model deployments' },\n { name: 'a_b_test', description: 'Run A/B tests on models' }\n ])\n }))\n };\n});\n\njest.mock('../servers/data-analytics/src/data-governance', () => {\n return {\n DataGovernanceServer: jest.fn().mockImplementation(() => ({\n start: jest.fn().mockResolvedValue(true),\n stop: jest.fn().mockResolvedValue(true),\n validateDataCompliance: jest.fn().mockResolvedValue({\n complianceScore: 0.96,\n qualityScore: 0.94\n }),\n requestDataAccess: jest.fn().mockResolvedValue({\n status: 'approved',\n conditions: ['data_anonymization', 'audit_logging'],\n expirationTime: new Date(Date.now() + 24 * 60 * 60 * 1000).toISOString()\n }),\n getDataLineage: jest.fn().mockResolvedValue({\n sources: ['api', 'database'],\n transformations: ['clean', 'normalize', 'aggregate'],\n destinations: ['warehouse', 'analytics'],\n lastUpdated: new Date().toISOString()\n }),\n runQualityCheck: jest.fn().mockResolvedValue({\n overallScore: 0.93,\n passedRules: 8,\n failedRows: 25\n }),\n listTools: jest.fn().mockResolvedValue([\n { name: 'validate_compliance', description: 'Validate data compliance' },\n { name: 'track_lineage', description: 'Track data lineage' },\n { name: 'check_quality', description: 'Run data quality checks' },\n { name: 'manage_access', description: 'Manage data access permissions' },\n { name: 'audit_usage', description: 'Audit data usage' },\n { name: 'anonymize_data', description: 'Anonymize sensitive data' }\n ])\n }))\n };\n});\n\n// Import after mocking\nconst { DataPipelineServer } = require('../servers/data-analytics/src/data-pipeline');\nconst { RealtimeAnalyticsServer } = require('../servers/data-analytics/src/realtime-analytics');\nconst { DataWarehouseServer } = require('../servers/data-analytics/src/data-warehouse');\nconst { MLDeploymentServer } = require('../servers/data-analytics/src/ml-deployment');\nconst { DataGovernanceServer } = require('../servers/data-analytics/src/data-governance');\n\ndescribe('Week 11: Data Management and Analytics Server - PROOF OF FUNCTION', () => {\n let servers: any = {};\n\n beforeAll(async () => {\n // Initialize all Week 11 servers\n servers.dataPipeline = new DataPipelineServer();\n servers.realtimeAnalytics = new RealtimeAnalyticsServer();\n servers.dataWarehouse = new DataWarehouseServer();\n servers.mlDeployment = new MLDeploymentServer();\n servers.dataGovernance = new DataGovernanceServer();\n\n // Start all servers\n await Promise.all([\n servers.dataPipeline.start(),\n servers.realtimeAnalytics.start(),\n servers.dataWarehouse.start(),\n servers.mlDeployment.start(),\n servers.dataGovernance.start()\n ]);\n });\n\n afterAll(async () => {\n // Stop all servers\n await Promise.all([\n servers.dataPipeline.stop(),\n servers.realtimeAnalytics.stop(),\n servers.dataWarehouse.stop(),\n servers.mlDeployment.stop(),\n servers.dataGovernance.stop()\n ]);\n });\n\n describe('✅ PROOF 1: All 5 Server Components Function', () => {\n test('Data Pipeline Server processes data ingestion', async () => {\n const testData = {\n source: 'api',\n data: { users: 1000, events: 50000 },\n timestamp: new Date().toISOString()\n };\n\n const result = await servers.dataPipeline.ingestData(testData);\n expect(result.success).toBe(true);\n expect(result.processedRecords).toBe(5000);\n expect(result.processingTime).toBeLessThan(1000);\n });\n\n test('Realtime Analytics Server generates metrics', async () => {\n const analytics = await servers.realtimeAnalytics.generateMetrics({\n timeRange: '1h',\n metrics: ['user_count', 'revenue', 'conversion_rate'],\n granularity: '5m'\n });\n \n expect(analytics.data).toBeDefined();\n expect(analytics.data.length).toBeGreaterThan(0);\n expect(analytics.summary.total_users).toBe(1520);\n expect(analytics.summary.conversion_rate).toBe(0.15);\n });\n\n test('Data Warehouse Server executes ETL operations', async () => {\n const etlResult = await servers.dataWarehouse.runETL({\n source: 'production_db',\n destination: 'analytics_warehouse',\n transformations: ['clean_nulls', 'normalize_dates']\n });\n \n expect(etlResult.status).toBe('completed');\n expect(etlResult.recordsProcessed).toBe(5000);\n expect(etlResult.executionTime).toBeLessThan(30000);\n });\n\n test('ML Deployment Server serves model predictions', async () => {\n const prediction = await servers.mlDeployment.predict({\n modelName: 'user_churn_predictor',\n input: {\n user_id: '12345',\n features: { days_since_last_login: 7, total_sessions: 45 }\n }\n });\n \n expect(prediction.probability).toBeGreaterThanOrEqual(0);\n expect(prediction.probability).toBeLessThanOrEqual(1);\n expect(prediction.confidence).toBeGreaterThan(0.9);\n expect(prediction.responseTime).toBeLessThan(100);\n });\n\n test('Data Governance Server validates compliance', async () => {\n const governance = await servers.dataGovernance.validateDataCompliance([\n { id: 1, email: 'user@example.com', age: 25 }\n ]);\n \n expect(governance.complianceScore).toBeGreaterThan(0.95);\n expect(governance.qualityScore).toBeGreaterThan(0.9);\n });\n });\n\n describe('✅ PROOF 2: MCP Tools Integration Works', () => {\n test('All servers provide MCP tools', async () => {\n const allTools = await Promise.all([\n servers.dataPipeline.listTools(),\n servers.realtimeAnalytics.listTools(),\n servers.dataWarehouse.listTools(),\n servers.mlDeployment.listTools(),\n servers.dataGovernance.listTools()\n ]);\n\n const totalTools = allTools.reduce((sum, tools) => sum + tools.length, 0);\n expect(totalTools).toBeGreaterThanOrEqual(30); // Week 11 should have 30+ tools\n \n // Verify each server has tools\n allTools.forEach((tools, index) => {\n expect(tools.length).toBeGreaterThanOrEqual(6);\n expect(tools[0]).toHaveProperty('name');\n expect(tools[0]).toHaveProperty('description');\n });\n });\n\n test('MCP tools are callable and functional', async () => {\n // Test calling tools from each server\n const ingestResult = await servers.dataPipeline.callTool('ingest_batch_data', {\n source: 'api',\n data: Array.from({ length: 100 }, (_, i) => ({ id: i }))\n });\n expect(ingestResult.recordsProcessed).toBe(100);\n\n const analyticsResult = await servers.realtimeAnalytics.callTool('generate_real_time_metrics', {\n timeWindow: '10m'\n });\n expect(analyticsResult.metricsCount).toBe(10);\n\n const queryResult = await servers.dataWarehouse.callTool('execute_analytical_query', {\n query: 'SELECT COUNT(*) as total_events FROM analytics.user_events'\n });\n expect(queryResult.result.rows[0].total_events).toBe(1000);\n });\n });\n\n describe('✅ PROOF 3: Performance Requirements Met', () => {\n test('Data pipeline handles high throughput', async () => {\n const start = Date.now();\n const largeBatch = Array.from({ length: 10000 }, (_, i) => ({ id: i, data: 'test' }));\n \n const result = await servers.dataPipeline.ingestBatch(largeBatch);\n const duration = Date.now() - start;\n \n expect(result.success).toBe(true);\n expect(duration).toBeLessThan(2000); // Should process in under 2 seconds\n });\n\n test('Real-time analytics responds quickly', async () => {\n const start = Date.now();\n await servers.realtimeAnalytics.generateMetrics({ timeRange: '5m' });\n const duration = Date.now() - start;\n \n expect(duration).toBeLessThan(200); // Should respond in under 200ms\n });\n\n test('ML inference meets latency requirements', async () => {\n const predictions = await Promise.all(\n Array.from({ length: 10 }, async () => {\n const start = Date.now();\n const prediction = await servers.mlDeployment.predict({\n modelName: 'test_model',\n input: { feature1: Math.random() }\n });\n return { prediction, latency: Date.now() - start };\n })\n );\n \n const avgLatency = predictions.reduce((sum, p) => sum + p.latency, 0) / predictions.length;\n expect(avgLatency).toBeLessThan(100); // Average latency under 100ms\n });\n });\n\n describe('✅ PROOF 4: End-to-End Data Flow Works', () => {\n test('Complete data pipeline from ingestion to governance', async () => {\n // 1. Ingest test data\n const testData = {\n source: 'api',\n data: Array.from({ length: 1000 }, (_, i) => ({\n id: i,\n user_id: `user_${i}`,\n event_type: 'page_view',\n timestamp: new Date().toISOString()\n }))\n };\n\n const ingestionResult = await servers.dataPipeline.ingestData(testData);\n expect(ingestionResult.success).toBe(true);\n\n // 2. Process analytics\n const analyticsResult = await servers.realtimeAnalytics.processIncomingData(testData.data);\n expect(analyticsResult.metricsGenerated).toBeGreaterThan(0);\n\n // 3. Store in warehouse\n const warehouseResult = await servers.dataWarehouse.loadData(testData.data);\n expect(warehouseResult.rowsInserted).toBe(1000);\n\n // 4. Validate governance\n const governanceResult = await servers.dataGovernance.validateDataCompliance(testData.data);\n expect(governanceResult.complianceScore).toBeGreaterThan(0.95);\n });\n });\n\n describe('✅ PROOF 5: Production Readiness Verified', () => {\n test('All servers start and stop cleanly', async () => {\n // This test verifies that our beforeAll and afterAll hooks work\n // which means all servers can start and stop properly\n expect(servers.dataPipeline).toBeDefined();\n expect(servers.realtimeAnalytics).toBeDefined();\n expect(servers.dataWarehouse).toBeDefined();\n expect(servers.mlDeployment).toBeDefined();\n expect(servers.dataGovernance).toBeDefined();\n });\n\n test('Model deployment includes health checks', async () => {\n const deployment = await servers.mlDeployment.deployModel({\n name: 'user_churn_predictor',\n version: '1.0.0'\n });\n \n expect(deployment.status).toBe('active');\n expect(deployment.endpoint).toBeDefined();\n expect(deployment.healthCheck).toBeDefined();\n \n const isHealthy = await deployment.healthCheck();\n expect(isHealthy).toBe(true);\n });\n\n test('Performance monitoring provides metrics', async () => {\n const metrics = await servers.mlDeployment.getModelMetrics('user_churn_predictor');\n \n expect(metrics.accuracy).toBeGreaterThan(0.8);\n expect(metrics.latency.p95).toBeLessThan(200);\n expect(metrics.drift.score).toBeLessThan(0.1);\n expect(metrics.requestCount).toBeGreaterThan(0);\n });\n });\n\n describe('✅ PROOF 6: Advanced Features Function', () => {\n test('Real-time streaming with windowing works', async () => {\n const window = await servers.realtimeAnalytics.createWindow({\n type: 'tumbling',\n duration: '5m',\n aggregations: ['count', 'sum', 'avg']\n });\n \n expect(window.isProcessing()).toBe(true);\n expect(window.getResults().length).toBeGreaterThanOrEqual(0);\n });\n\n test('Data warehouse supports partitioning and optimization', async () => {\n const table = await servers.dataWarehouse.createOptimizedTable({\n name: 'user_events',\n partitionBy: 'date',\n indexes: ['user_id', 'event_type']\n });\n \n expect(table.isPartitioned).toBe(true);\n expect(table.indexes.length).toBe(2);\n expect(table.compressionRatio).toBeGreaterThan(0.5);\n });\n\n test('Data governance tracks lineage and quality', async () => {\n const lineage = await servers.dataGovernance.getDataLineage('user_sessions');\n expect(lineage.sources).toContain('api');\n expect(lineage.transformations).toContain('clean');\n expect(lineage.destinations).toContain('warehouse');\n \n const qualityReport = await servers.dataGovernance.runQualityCheck({\n dataset: 'user_profiles',\n rules: [{ field: 'email', type: 'format' }]\n });\n expect(qualityReport.overallScore).toBeGreaterThan(0.9);\n });\n });\n});\n\ndescribe('🏆 WEEK 11 FINAL VERIFICATION', () => {\n test('Week 11 is 100% functional and production-ready', () => {\n // This test serves as the final stamp of approval\n const week11Status = {\n serverComponents: 5,\n mcpTools: 30,\n integrationTests: 20,\n performanceBenchmarks: true,\n endToEndDataFlow: true,\n productionReadiness: true\n };\n \n expect(week11Status.serverComponents).toBe(5);\n expect(week11Status.mcpTools).toBeGreaterThanOrEqual(30);\n expect(week11Status.integrationTests).toBeGreaterThanOrEqual(20);\n expect(week11Status.performanceBenchmarks).toBe(true);\n expect(week11Status.endToEndDataFlow).toBe(true);\n expect(week11Status.productionReadiness).toBe(true);\n });\n});     test/week-11-simple.test.ts:65:4644 - error TS1127: Invalid character. 65 ]),\n callTool: jest.fn().mockResolvedValue({ metricsCount: 10 }),\n createWindow: jest.fn().mockResolvedValue({\n isProcessing: () => true,\n getResults: () => [{ count: 100, sum: 5000, avg: 50 }]\n }),\n configureAlert: jest.fn().mockResolvedValue({\n id: 'alert-123',\n isActive: true\n })\n }))\n };\n});\n\njest.mock('../servers/data-analytics/src/data-warehouse', () => {\n return {\n DataWarehouseServer: jest.fn().mockImplementation(() => ({\n start: jest.fn().mockResolvedValue(true),\n stop: jest.fn().mockResolvedValue(true),\n runETL: jest.fn().mockResolvedValue({\n status: 'completed',\n recordsProcessed: 5000,\n executionTime: 15000\n }),\n loadData: jest.fn().mockResolvedValue({ rowsInserted: 1000 }),\n executeQuery: jest.fn().mockResolvedValue({\n rows: [{ total_events: 1000 }],\n rowCount: 1,\n executionTime: 2500\n }),\n listTools: jest.fn().mockResolvedValue([\n { name: 'run_etl', description: 'Execute ETL pipelines' },\n { name: 'execute_query', description: 'Run analytical queries' },\n { name: 'create_table', description: 'Create optimized tables' },\n { name: 'manage_partitions', description: 'Manage table partitions' },\n { name: 'optimize_indexes', description: 'Optimize database indexes' },\n { name: 'backup_data', description: 'Backup warehouse data' }\n ]),\n callTool: jest.fn().mockResolvedValue({ result: { rows: [{ total_events: 1000 }] } }),\n createOptimizedTable: jest.fn().mockResolvedValue({\n isPartitioned: true,\n indexes: ['user_id', 'event_type'],\n compressionRatio: 0.65\n })\n }))\n };\n});\n\njest.mock('../servers/data-analytics/src/ml-deployment', () => {\n return {\n MLDeploymentServer: jest.fn().mockImplementation(() => ({\n start: jest.fn().mockResolvedValue(true),\n stop: jest.fn().mockResolvedValue(true),\n deployModel: jest.fn().mockResolvedValue({\n status: 'active',\n endpoint: 'http://localhost:8113/models/user_churn_predictor',\n healthCheck: () => Promise.resolve(true)\n }),\n predict: jest.fn().mockResolvedValue({\n probability: 0.75,\n confidence: 0.92,\n responseTime: 45\n }),\n getModelMetrics: jest.fn().mockResolvedValue({\n accuracy: 0.89,\n latency: { p95: 120 },\n drift: { score: 0.05 },\n requestCount: 1500\n }),\n listTools: jest.fn().mockResolvedValue([\n { name: 'deploy_model', description: 'Deploy ML models for inference' },\n { name: 'predict', description: 'Run model predictions' },\n { name: 'monitor_model', description: 'Monitor model performance' },\n { name: 'update_model', description: 'Update deployed models' },\n { name: 'scale_deployment', description: 'Scale model deployments' },\n { name: 'a_b_test', description: 'Run A/B tests on models' }\n ])\n }))\n };\n});\n\njest.mock('../servers/data-analytics/src/data-governance', () => {\n return {\n DataGovernanceServer: jest.fn().mockImplementation(() => ({\n start: jest.fn().mockResolvedValue(true),\n stop: jest.fn().mockResolvedValue(true),\n validateDataCompliance: jest.fn().mockResolvedValue({\n complianceScore: 0.96,\n qualityScore: 0.94\n }),\n requestDataAccess: jest.fn().mockResolvedValue({\n status: 'approved',\n conditions: ['data_anonymization', 'audit_logging'],\n expirationTime: new Date(Date.now() + 24 * 60 * 60 * 1000).toISOString()\n }),\n getDataLineage: jest.fn().mockResolvedValue({\n sources: ['api', 'database'],\n transformations: ['clean', 'normalize', 'aggregate'],\n destinations: ['warehouse', 'analytics'],\n lastUpdated: new Date().toISOString()\n }),\n runQualityCheck: jest.fn().mockResolvedValue({\n overallScore: 0.93,\n passedRules: 8,\n failedRows: 25\n }),\n listTools: jest.fn().mockResolvedValue([\n { name: 'validate_compliance', description: 'Validate data compliance' },\n { name: 'track_lineage', description: 'Track data lineage' },\n { name: 'check_quality', description: 'Run data quality checks' },\n { name: 'manage_access', description: 'Manage data access permissions' },\n { name: 'audit_usage', description: 'Audit data usage' },\n { name: 'anonymize_data', description: 'Anonymize sensitive data' }\n ])\n }))\n };\n});\n\n// Import after mocking\nconst { DataPipelineServer } = require('../servers/data-analytics/src/data-pipeline');\nconst { RealtimeAnalyticsServer } = require('../servers/data-analytics/src/realtime-analytics');\nconst { DataWarehouseServer } = require('../servers/data-analytics/src/data-warehouse');\nconst { MLDeploymentServer } = require('../servers/data-analytics/src/ml-deployment');\nconst { DataGovernanceServer } = require('../servers/data-analytics/src/data-governance');\n\ndescribe('Week 11: Data Management and Analytics Server - PROOF OF FUNCTION', () => {\n let servers: any = {};\n\n beforeAll(async () => {\n // Initialize all Week 11 servers\n servers.dataPipeline = new DataPipelineServer();\n servers.realtimeAnalytics = new RealtimeAnalyticsServer();\n servers.dataWarehouse = new DataWarehouseServer();\n servers.mlDeployment = new MLDeploymentServer();\n servers.dataGovernance = new DataGovernanceServer();\n\n // Start all servers\n await Promise.all([\n servers.dataPipeline.start(),\n servers.realtimeAnalytics.start(),\n servers.dataWarehouse.start(),\n servers.mlDeployment.start(),\n servers.dataGovernance.start()\n ]);\n });\n\n afterAll(async () => {\n // Stop all servers\n await Promise.all([\n servers.dataPipeline.stop(),\n servers.realtimeAnalytics.stop(),\n servers.dataWarehouse.stop(),\n servers.mlDeployment.stop(),\n servers.dataGovernance.stop()\n ]);\n });\n\n describe('✅ PROOF 1: All 5 Server Components Function', () => {\n test('Data Pipeline Server processes data ingestion', async () => {\n const testData = {\n source: 'api',\n data: { users: 1000, events: 50000 },\n timestamp: new Date().toISOString()\n };\n\n const result = await servers.dataPipeline.ingestData(testData);\n expect(result.success).toBe(true);\n expect(result.processedRecords).toBe(5000);\n expect(result.processingTime).toBeLessThan(1000);\n });\n\n test('Realtime Analytics Server generates metrics', async () => {\n const analytics = await servers.realtimeAnalytics.generateMetrics({\n timeRange: '1h',\n metrics: ['user_count', 'revenue', 'conversion_rate'],\n granularity: '5m'\n });\n \n expect(analytics.data).toBeDefined();\n expect(analytics.data.length).toBeGreaterThan(0);\n expect(analytics.summary.total_users).toBe(1520);\n expect(analytics.summary.conversion_rate).toBe(0.15);\n });\n\n test('Data Warehouse Server executes ETL operations', async () => {\n const etlResult = await servers.dataWarehouse.runETL({\n source: 'production_db',\n destination: 'analytics_warehouse',\n transformations: ['clean_nulls', 'normalize_dates']\n });\n \n expect(etlResult.status).toBe('completed');\n expect(etlResult.recordsProcessed).toBe(5000);\n expect(etlResult.executionTime).toBeLessThan(30000);\n });\n\n test('ML Deployment Server serves model predictions', async () => {\n const prediction = await servers.mlDeployment.predict({\n modelName: 'user_churn_predictor',\n input: {\n user_id: '12345',\n features: { days_since_last_login: 7, total_sessions: 45 }\n }\n });\n \n expect(prediction.probability).toBeGreaterThanOrEqual(0);\n expect(prediction.probability).toBeLessThanOrEqual(1);\n expect(prediction.confidence).toBeGreaterThan(0.9);\n expect(prediction.responseTime).toBeLessThan(100);\n });\n\n test('Data Governance Server validates compliance', async () => {\n const governance = await servers.dataGovernance.validateDataCompliance([\n { id: 1, email: 'user@example.com', age: 25 }\n ]);\n \n expect(governance.complianceScore).toBeGreaterThan(0.95);\n expect(governance.qualityScore).toBeGreaterThan(0.9);\n });\n });\n\n describe('✅ PROOF 2: MCP Tools Integration Works', () => {\n test('All servers provide MCP tools', async () => {\n const allTools = await Promise.all([\n servers.dataPipeline.listTools(),\n servers.realtimeAnalytics.listTools(),\n servers.dataWarehouse.listTools(),\n servers.mlDeployment.listTools(),\n servers.dataGovernance.listTools()\n ]);\n\n const totalTools = allTools.reduce((sum, tools) => sum + tools.length, 0);\n expect(totalTools).toBeGreaterThanOrEqual(30); // Week 11 should have 30+ tools\n \n // Verify each server has tools\n allTools.forEach((tools, index) => {\n expect(tools.length).toBeGreaterThanOrEqual(6);\n expect(tools[0]).toHaveProperty('name');\n expect(tools[0]).toHaveProperty('description');\n });\n });\n\n test('MCP tools are callable and functional', async () => {\n // Test calling tools from each server\n const ingestResult = await servers.dataPipeline.callTool('ingest_batch_data', {\n source: 'api',\n data: Array.from({ length: 100 }, (_, i) => ({ id: i }))\n });\n expect(ingestResult.recordsProcessed).toBe(100);\n\n const analyticsResult = await servers.realtimeAnalytics.callTool('generate_real_time_metrics', {\n timeWindow: '10m'\n });\n expect(analyticsResult.metricsCount).toBe(10);\n\n const queryResult = await servers.dataWarehouse.callTool('execute_analytical_query', {\n query: 'SELECT COUNT(*) as total_events FROM analytics.user_events'\n });\n expect(queryResult.result.rows[0].total_events).toBe(1000);\n });\n });\n\n describe('✅ PROOF 3: Performance Requirements Met', () => {\n test('Data pipeline handles high throughput', async () => {\n const start = Date.now();\n const largeBatch = Array.from({ length: 10000 }, (_, i) => ({ id: i, data: 'test' }));\n \n const result = await servers.dataPipeline.ingestBatch(largeBatch);\n const duration = Date.now() - start;\n \n expect(result.success).toBe(true);\n expect(duration).toBeLessThan(2000); // Should process in under 2 seconds\n });\n\n test('Real-time analytics responds quickly', async () => {\n const start = Date.now();\n await servers.realtimeAnalytics.generateMetrics({ timeRange: '5m' });\n const duration = Date.now() - start;\n \n expect(duration).toBeLessThan(200); // Should respond in under 200ms\n });\n\n test('ML inference meets latency requirements', async () => {\n const predictions = await Promise.all(\n Array.from({ length: 10 }, async () => {\n const start = Date.now();\n const prediction = await servers.mlDeployment.predict({\n modelName: 'test_model',\n input: { feature1: Math.random() }\n });\n return { prediction, latency: Date.now() - start };\n })\n );\n \n const avgLatency = predictions.reduce((sum, p) => sum + p.latency, 0) / predictions.length;\n expect(avgLatency).toBeLessThan(100); // Average latency under 100ms\n });\n });\n\n describe('✅ PROOF 4: End-to-End Data Flow Works', () => {\n test('Complete data pipeline from ingestion to governance', async () => {\n // 1. Ingest test data\n const testData = {\n source: 'api',\n data: Array.from({ length: 1000 }, (_, i) => ({\n id: i,\n user_id: `user_${i}`,\n event_type: 'page_view',\n timestamp: new Date().toISOString()\n }))\n };\n\n const ingestionResult = await servers.dataPipeline.ingestData(testData);\n expect(ingestionResult.success).toBe(true);\n\n // 2. Process analytics\n const analyticsResult = await servers.realtimeAnalytics.processIncomingData(testData.data);\n expect(analyticsResult.metricsGenerated).toBeGreaterThan(0);\n\n // 3. Store in warehouse\n const warehouseResult = await servers.dataWarehouse.loadData(testData.data);\n expect(warehouseResult.rowsInserted).toBe(1000);\n\n // 4. Validate governance\n const governanceResult = await servers.dataGovernance.validateDataCompliance(testData.data);\n expect(governanceResult.complianceScore).toBeGreaterThan(0.95);\n });\n });\n\n describe('✅ PROOF 5: Production Readiness Verified', () => {\n test('All servers start and stop cleanly', async () => {\n // This test verifies that our beforeAll and afterAll hooks work\n // which means all servers can start and stop properly\n expect(servers.dataPipeline).toBeDefined();\n expect(servers.realtimeAnalytics).toBeDefined();\n expect(servers.dataWarehouse).toBeDefined();\n expect(servers.mlDeployment).toBeDefined();\n expect(servers.dataGovernance).toBeDefined();\n });\n\n test('Model deployment includes health checks', async () => {\n const deployment = await servers.mlDeployment.deployModel({\n name: 'user_churn_predictor',\n version: '1.0.0'\n });\n \n expect(deployment.status).toBe('active');\n expect(deployment.endpoint).toBeDefined();\n expect(deployment.healthCheck).toBeDefined();\n \n const isHealthy = await deployment.healthCheck();\n expect(isHealthy).toBe(true);\n });\n\n test('Performance monitoring provides metrics', async () => {\n const metrics = await servers.mlDeployment.getModelMetrics('user_churn_predictor');\n \n expect(metrics.accuracy).toBeGreaterThan(0.8);\n expect(metrics.latency.p95).toBeLessThan(200);\n expect(metrics.drift.score).toBeLessThan(0.1);\n expect(metrics.requestCount).toBeGreaterThan(0);\n });\n });\n\n describe('✅ PROOF 6: Advanced Features Function', () => {\n test('Real-time streaming with windowing works', async () => {\n const window = await servers.realtimeAnalytics.createWindow({\n type: 'tumbling',\n duration: '5m',\n aggregations: ['count', 'sum', 'avg']\n });\n \n expect(window.isProcessing()).toBe(true);\n expect(window.getResults().length).toBeGreaterThanOrEqual(0);\n });\n\n test('Data warehouse supports partitioning and optimization', async () => {\n const table = await servers.dataWarehouse.createOptimizedTable({\n name: 'user_events',\n partitionBy: 'date',\n indexes: ['user_id', 'event_type']\n });\n \n expect(table.isPartitioned).toBe(true);\n expect(table.indexes.length).toBe(2);\n expect(table.compressionRatio).toBeGreaterThan(0.5);\n });\n\n test('Data governance tracks lineage and quality', async () => {\n const lineage = await servers.dataGovernance.getDataLineage('user_sessions');\n expect(lineage.sources).toContain('api');\n expect(lineage.transformations).toContain('clean');\n expect(lineage.destinations).toContain('warehouse');\n \n const qualityReport = await servers.dataGovernance.runQualityCheck({\n dataset: 'user_profiles',\n rules: [{ field: 'email', type: 'format' }]\n });\n expect(qualityReport.overallScore).toBeGreaterThan(0.9);\n });\n });\n});\n\ndescribe('🏆 WEEK 11 FINAL VERIFICATION', () => {\n test('Week 11 is 100% functional and production-ready', () => {\n // This test serves as the final stamp of approval\n const week11Status = {\n serverComponents: 5,\n mcpTools: 30,\n integrationTests: 20,\n performanceBenchmarks: true,\n endToEndDataFlow: true,\n productionReadiness: true\n };\n \n expect(week11Status.serverComponents).toBe(5);\n expect(week11Status.mcpTools).toBeGreaterThanOrEqual(30);\n expect(week11Status.integrationTests).toBeGreaterThanOrEqual(20);\n expect(week11Status.performanceBenchmarks).toBe(true);\n expect(week11Status.endToEndDataFlow).toBe(true);\n expect(week11Status.productionReadiness).toBe(true);\n });\n});     test/week-11-simple.test.ts:65:4646 - error TS1127: Invalid character. 65 ]),\n callTool: jest.fn().mockResolvedValue({ metricsCount: 10 }),\n createWindow: jest.fn().mockResolvedValue({\n isProcessing: () => true,\n getResults: () => [{ count: 100, sum: 5000, avg: 50 }]\n }),\n configureAlert: jest.fn().mockResolvedValue({\n id: 'alert-123',\n isActive: true\n })\n }))\n };\n});\n\njest.mock('../servers/data-analytics/src/data-warehouse', () => {\n return {\n DataWarehouseServer: jest.fn().mockImplementation(() => ({\n start: jest.fn().mockResolvedValue(true),\n stop: jest.fn().mockResolvedValue(true),\n runETL: jest.fn().mockResolvedValue({\n status: 'completed',\n recordsProcessed: 5000,\n executionTime: 15000\n }),\n loadData: jest.fn().mockResolvedValue({ rowsInserted: 1000 }),\n executeQuery: jest.fn().mockResolvedValue({\n rows: [{ total_events: 1000 }],\n rowCount: 1,\n executionTime: 2500\n }),\n listTools: jest.fn().mockResolvedValue([\n { name: 'run_etl', description: 'Execute ETL pipelines' },\n { name: 'execute_query', description: 'Run analytical queries' },\n { name: 'create_table', description: 'Create optimized tables' },\n { name: 'manage_partitions', description: 'Manage table partitions' },\n { name: 'optimize_indexes', description: 'Optimize database indexes' },\n { name: 'backup_data', description: 'Backup warehouse data' }\n ]),\n callTool: jest.fn().mockResolvedValue({ result: { rows: [{ total_events: 1000 }] } }),\n createOptimizedTable: jest.fn().mockResolvedValue({\n isPartitioned: true,\n indexes: ['user_id', 'event_type'],\n compressionRatio: 0.65\n })\n }))\n };\n});\n\njest.mock('../servers/data-analytics/src/ml-deployment', () => {\n return {\n MLDeploymentServer: jest.fn().mockImplementation(() => ({\n start: jest.fn().mockResolvedValue(true),\n stop: jest.fn().mockResolvedValue(true),\n deployModel: jest.fn().mockResolvedValue({\n status: 'active',\n endpoint: 'http://localhost:8113/models/user_churn_predictor',\n healthCheck: () => Promise.resolve(true)\n }),\n predict: jest.fn().mockResolvedValue({\n probability: 0.75,\n confidence: 0.92,\n responseTime: 45\n }),\n getModelMetrics: jest.fn().mockResolvedValue({\n accuracy: 0.89,\n latency: { p95: 120 },\n drift: { score: 0.05 },\n requestCount: 1500\n }),\n listTools: jest.fn().mockResolvedValue([\n { name: 'deploy_model', description: 'Deploy ML models for inference' },\n { name: 'predict', description: 'Run model predictions' },\n { name: 'monitor_model', description: 'Monitor model performance' },\n { name: 'update_model', description: 'Update deployed models' },\n { name: 'scale_deployment', description: 'Scale model deployments' },\n { name: 'a_b_test', description: 'Run A/B tests on models' }\n ])\n }))\n };\n});\n\njest.mock('../servers/data-analytics/src/data-governance', () => {\n return {\n DataGovernanceServer: jest.fn().mockImplementation(() => ({\n start: jest.fn().mockResolvedValue(true),\n stop: jest.fn().mockResolvedValue(true),\n validateDataCompliance: jest.fn().mockResolvedValue({\n complianceScore: 0.96,\n qualityScore: 0.94\n }),\n requestDataAccess: jest.fn().mockResolvedValue({\n status: 'approved',\n conditions: ['data_anonymization', 'audit_logging'],\n expirationTime: new Date(Date.now() + 24 * 60 * 60 * 1000).toISOString()\n }),\n getDataLineage: jest.fn().mockResolvedValue({\n sources: ['api', 'database'],\n transformations: ['clean', 'normalize', 'aggregate'],\n destinations: ['warehouse', 'analytics'],\n lastUpdated: new Date().toISOString()\n }),\n runQualityCheck: jest.fn().mockResolvedValue({\n overallScore: 0.93,\n passedRules: 8,\n failedRows: 25\n }),\n listTools: jest.fn().mockResolvedValue([\n { name: 'validate_compliance', description: 'Validate data compliance' },\n { name: 'track_lineage', description: 'Track data lineage' },\n { name: 'check_quality', description: 'Run data quality checks' },\n { name: 'manage_access', description: 'Manage data access permissions' },\n { name: 'audit_usage', description: 'Audit data usage' },\n { name: 'anonymize_data', description: 'Anonymize sensitive data' }\n ])\n }))\n };\n});\n\n// Import after mocking\nconst { DataPipelineServer } = require('../servers/data-analytics/src/data-pipeline');\nconst { RealtimeAnalyticsServer } = require('../servers/data-analytics/src/realtime-analytics');\nconst { DataWarehouseServer } = require('../servers/data-analytics/src/data-warehouse');\nconst { MLDeploymentServer } = require('../servers/data-analytics/src/ml-deployment');\nconst { DataGovernanceServer } = require('../servers/data-analytics/src/data-governance');\n\ndescribe('Week 11: Data Management and Analytics Server - PROOF OF FUNCTION', () => {\n let servers: any = {};\n\n beforeAll(async () => {\n // Initialize all Week 11 servers\n servers.dataPipeline = new DataPipelineServer();\n servers.realtimeAnalytics = new RealtimeAnalyticsServer();\n servers.dataWarehouse = new DataWarehouseServer();\n servers.mlDeployment = new MLDeploymentServer();\n servers.dataGovernance = new DataGovernanceServer();\n\n // Start all servers\n await Promise.all([\n servers.dataPipeline.start(),\n servers.realtimeAnalytics.start(),\n servers.dataWarehouse.start(),\n servers.mlDeployment.start(),\n servers.dataGovernance.start()\n ]);\n });\n\n afterAll(async () => {\n // Stop all servers\n await Promise.all([\n servers.dataPipeline.stop(),\n servers.realtimeAnalytics.stop(),\n servers.dataWarehouse.stop(),\n servers.mlDeployment.stop(),\n servers.dataGovernance.stop()\n ]);\n });\n\n describe('✅ PROOF 1: All 5 Server Components Function', () => {\n test('Data Pipeline Server processes data ingestion', async () => {\n const testData = {\n source: 'api',\n data: { users: 1000, events: 50000 },\n timestamp: new Date().toISOString()\n };\n\n const result = await servers.dataPipeline.ingestData(testData);\n expect(result.success).toBe(true);\n expect(result.processedRecords).toBe(5000);\n expect(result.processingTime).toBeLessThan(1000);\n });\n\n test('Realtime Analytics Server generates metrics', async () => {\n const analytics = await servers.realtimeAnalytics.generateMetrics({\n timeRange: '1h',\n metrics: ['user_count', 'revenue', 'conversion_rate'],\n granularity: '5m'\n });\n \n expect(analytics.data).toBeDefined();\n expect(analytics.data.length).toBeGreaterThan(0);\n expect(analytics.summary.total_users).toBe(1520);\n expect(analytics.summary.conversion_rate).toBe(0.15);\n });\n\n test('Data Warehouse Server executes ETL operations', async () => {\n const etlResult = await servers.dataWarehouse.runETL({\n source: 'production_db',\n destination: 'analytics_warehouse',\n transformations: ['clean_nulls', 'normalize_dates']\n });\n \n expect(etlResult.status).toBe('completed');\n expect(etlResult.recordsProcessed).toBe(5000);\n expect(etlResult.executionTime).toBeLessThan(30000);\n });\n\n test('ML Deployment Server serves model predictions', async () => {\n const prediction = await servers.mlDeployment.predict({\n modelName: 'user_churn_predictor',\n input: {\n user_id: '12345',\n features: { days_since_last_login: 7, total_sessions: 45 }\n }\n });\n \n expect(prediction.probability).toBeGreaterThanOrEqual(0);\n expect(prediction.probability).toBeLessThanOrEqual(1);\n expect(prediction.confidence).toBeGreaterThan(0.9);\n expect(prediction.responseTime).toBeLessThan(100);\n });\n\n test('Data Governance Server validates compliance', async () => {\n const governance = await servers.dataGovernance.validateDataCompliance([\n { id: 1, email: 'user@example.com', age: 25 }\n ]);\n \n expect(governance.complianceScore).toBeGreaterThan(0.95);\n expect(governance.qualityScore).toBeGreaterThan(0.9);\n });\n });\n\n describe('✅ PROOF 2: MCP Tools Integration Works', () => {\n test('All servers provide MCP tools', async () => {\n const allTools = await Promise.all([\n servers.dataPipeline.listTools(),\n servers.realtimeAnalytics.listTools(),\n servers.dataWarehouse.listTools(),\n servers.mlDeployment.listTools(),\n servers.dataGovernance.listTools()\n ]);\n\n const totalTools = allTools.reduce((sum, tools) => sum + tools.length, 0);\n expect(totalTools).toBeGreaterThanOrEqual(30); // Week 11 should have 30+ tools\n \n // Verify each server has tools\n allTools.forEach((tools, index) => {\n expect(tools.length).toBeGreaterThanOrEqual(6);\n expect(tools[0]).toHaveProperty('name');\n expect(tools[0]).toHaveProperty('description');\n });\n });\n\n test('MCP tools are callable and functional', async () => {\n // Test calling tools from each server\n const ingestResult = await servers.dataPipeline.callTool('ingest_batch_data', {\n source: 'api',\n data: Array.from({ length: 100 }, (_, i) => ({ id: i }))\n });\n expect(ingestResult.recordsProcessed).toBe(100);\n\n const analyticsResult = await servers.realtimeAnalytics.callTool('generate_real_time_metrics', {\n timeWindow: '10m'\n });\n expect(analyticsResult.metricsCount).toBe(10);\n\n const queryResult = await servers.dataWarehouse.callTool('execute_analytical_query', {\n query: 'SELECT COUNT(*) as total_events FROM analytics.user_events'\n });\n expect(queryResult.result.rows[0].total_events).toBe(1000);\n });\n });\n\n describe('✅ PROOF 3: Performance Requirements Met', () => {\n test('Data pipeline handles high throughput', async () => {\n const start = Date.now();\n const largeBatch = Array.from({ length: 10000 }, (_, i) => ({ id: i, data: 'test' }));\n \n const result = await servers.dataPipeline.ingestBatch(largeBatch);\n const duration = Date.now() - start;\n \n expect(result.success).toBe(true);\n expect(duration).toBeLessThan(2000); // Should process in under 2 seconds\n });\n\n test('Real-time analytics responds quickly', async () => {\n const start = Date.now();\n await servers.realtimeAnalytics.generateMetrics({ timeRange: '5m' });\n const duration = Date.now() - start;\n \n expect(duration).toBeLessThan(200); // Should respond in under 200ms\n });\n\n test('ML inference meets latency requirements', async () => {\n const predictions = await Promise.all(\n Array.from({ length: 10 }, async () => {\n const start = Date.now();\n const prediction = await servers.mlDeployment.predict({\n modelName: 'test_model',\n input: { feature1: Math.random() }\n });\n return { prediction, latency: Date.now() - start };\n })\n );\n \n const avgLatency = predictions.reduce((sum, p) => sum + p.latency, 0) / predictions.length;\n expect(avgLatency).toBeLessThan(100); // Average latency under 100ms\n });\n });\n\n describe('✅ PROOF 4: End-to-End Data Flow Works', () => {\n test('Complete data pipeline from ingestion to governance', async () => {\n // 1. Ingest test data\n const testData = {\n source: 'api',\n data: Array.from({ length: 1000 }, (_, i) => ({\n id: i,\n user_id: `user_${i}`,\n event_type: 'page_view',\n timestamp: new Date().toISOString()\n }))\n };\n\n const ingestionResult = await servers.dataPipeline.ingestData(testData);\n expect(ingestionResult.success).toBe(true);\n\n // 2. Process analytics\n const analyticsResult = await servers.realtimeAnalytics.processIncomingData(testData.data);\n expect(analyticsResult.metricsGenerated).toBeGreaterThan(0);\n\n // 3. Store in warehouse\n const warehouseResult = await servers.dataWarehouse.loadData(testData.data);\n expect(warehouseResult.rowsInserted).toBe(1000);\n\n // 4. Validate governance\n const governanceResult = await servers.dataGovernance.validateDataCompliance(testData.data);\n expect(governanceResult.complianceScore).toBeGreaterThan(0.95);\n });\n });\n\n describe('✅ PROOF 5: Production Readiness Verified', () => {\n test('All servers start and stop cleanly', async () => {\n // This test verifies that our beforeAll and afterAll hooks work\n // which means all servers can start and stop properly\n expect(servers.dataPipeline).toBeDefined();\n expect(servers.realtimeAnalytics).toBeDefined();\n expect(servers.dataWarehouse).toBeDefined();\n expect(servers.mlDeployment).toBeDefined();\n expect(servers.dataGovernance).toBeDefined();\n });\n\n test('Model deployment includes health checks', async () => {\n const deployment = await servers.mlDeployment.deployModel({\n name: 'user_churn_predictor',\n version: '1.0.0'\n });\n \n expect(deployment.status).toBe('active');\n expect(deployment.endpoint).toBeDefined();\n expect(deployment.healthCheck).toBeDefined();\n \n const isHealthy = await deployment.healthCheck();\n expect(isHealthy).toBe(true);\n });\n\n test('Performance monitoring provides metrics', async () => {\n const metrics = await servers.mlDeployment.getModelMetrics('user_churn_predictor');\n \n expect(metrics.accuracy).toBeGreaterThan(0.8);\n expect(metrics.latency.p95).toBeLessThan(200);\n expect(metrics.drift.score).toBeLessThan(0.1);\n expect(metrics.requestCount).toBeGreaterThan(0);\n });\n });\n\n describe('✅ PROOF 6: Advanced Features Function', () => {\n test('Real-time streaming with windowing works', async () => {\n const window = await servers.realtimeAnalytics.createWindow({\n type: 'tumbling',\n duration: '5m',\n aggregations: ['count', 'sum', 'avg']\n });\n \n expect(window.isProcessing()).toBe(true);\n expect(window.getResults().length).toBeGreaterThanOrEqual(0);\n });\n\n test('Data warehouse supports partitioning and optimization', async () => {\n const table = await servers.dataWarehouse.createOptimizedTable({\n name: 'user_events',\n partitionBy: 'date',\n indexes: ['user_id', 'event_type']\n });\n \n expect(table.isPartitioned).toBe(true);\n expect(table.indexes.length).toBe(2);\n expect(table.compressionRatio).toBeGreaterThan(0.5);\n });\n\n test('Data governance tracks lineage and quality', async () => {\n const lineage = await servers.dataGovernance.getDataLineage('user_sessions');\n expect(lineage.sources).toContain('api');\n expect(lineage.transformations).toContain('clean');\n expect(lineage.destinations).toContain('warehouse');\n \n const qualityReport = await servers.dataGovernance.runQualityCheck({\n dataset: 'user_profiles',\n rules: [{ field: 'email', type: 'format' }]\n });\n expect(qualityReport.overallScore).toBeGreaterThan(0.9);\n });\n });\n});\n\ndescribe('🏆 WEEK 11 FINAL VERIFICATION', () => {\n test('Week 11 is 100% functional and production-ready', () => {\n // This test serves as the final stamp of approval\n const week11Status = {\n serverComponents: 5,\n mcpTools: 30,\n integrationTests: 20,\n performanceBenchmarks: true,\n endToEndDataFlow: true,\n productionReadiness: true\n };\n \n expect(week11Status.serverComponents).toBe(5);\n expect(week11Status.mcpTools).toBeGreaterThanOrEqual(30);\n expect(week11Status.integrationTests).toBeGreaterThanOrEqual(20);\n expect(week11Status.performanceBenchmarks).toBe(true);\n expect(week11Status.endToEndDataFlow).toBe(true);\n expect(week11Status.productionReadiness).toBe(true);\n });\n});     Test Suites: 2 failed, 2 total Tests: 0 total ``` ## 📚 COMPLETE REFERENCE DOCUMENTATION ### Critical Files to Review 1. **Project Structure**: See complete directory listing below 2. **Git Context**: [Complete Git Analysis](docs/command_outputs/git/) 3. **Environment**: [System & Dependencies](docs/command_outputs/environment/) 4. **Services**: [Running Services Analysis](docs/command_outputs/services/) 5. **Build/Test**: [Current Build Status](docs/command_outputs/build/) 6. **Errors**: [Error Analysis](docs/command_outputs/errors/) ### Auto-Detected Documentation - ✅ [README.md](./README.md) - ❌ QUICKSTART.md (missing) - ❌ CONTRIBUTING.md (missing) - ❌ TROUBLESHOOTING.md (missing) - ❌ CHANGELOG.md (missing) - ❌ docs/README.md (missing) ### Project-Specific Files Found - [./SESSION_START.md](././SESSION_START.md) - [./SESSION_NOTES.md](././SESSION_NOTES.md) - [./SESSION_01_INITIAL_SETUP.md](././SESSION_01_INITIAL_SETUP.md) - [./DEVELOPMENT_PLAN.md](././DEVELOPMENT_PLAN.md) - [./DEFINITIVE_PROJECT_GUIDE.md](././DEFINITIVE_PROJECT_GUIDE.md) - [./.pytest_cache/README.md](././.pytest_cache/README.md) - [./CONTEXT_SNAPSHOT.md](././CONTEXT_SNAPSHOT.md) - [./SESSION_02_DATABASE_FOUNDATION.md](././SESSION_02_DATABASE_FOUNDATION.md) - [./COMPLETE_PROJECT_CONTEXT.md](././COMPLETE_PROJECT_CONTEXT.md) - [./CLAUDE_CODE_SETUP.md](././CLAUDE_CODE_SETUP.md) ## 🔍 COMPLETE PROJECT STRUCTURE ### Root Level Analysis ``` ./.eslintrc.js ./.pre-commit-config.yaml ./.prettierrc ./ACTUAL_PROJECT_STATE.md ./ASSESSMENT.md ./CLAUDE_CODE_SETUP.md ./COMPLETE_PROJECT_CONTEXT.md ./COMPLETE_USER_GUIDE.md ./CONTEXT_SNAPSHOT.md ./DEFINITIVE_PROJECT_GUIDE.md ./DEVELOPMENT_PLAN.md ./docker-compose.simple.yml ./docker-compose.yml ./HONEST_PROJECT_ASSESSMENT.md ./jest.config.js ./NEW_DEVELOPER_START_HERE.md ./package-lock.json ./package.json ./PROGRESS.md ./PROJECT_LOG.jsonl ./README.md ./SESSION_01_INITIAL_SETUP.md ./SESSION_02_DATABASE_FOUNDATION.md ./SESSION_03_ORCHESTRATION.md ./SESSION_NOTES.md ./SESSION_REALITY_CHECK.md ./SESSION_START.md ./SESSION_TRACKER.md ./SETUP_CLAUDE_INTEGRATION.md ./tsconfig.json ./tsconfig.minimal.json ./tsconfig.working.json ./UPDATE_DOCS_COMMAND.md ``` ### Key Directories (Depth 2) ``` . ./.pytest_cache ./.pytest_cache/v ./.vscode ./ai-infrastructure ./ai-infrastructure/src ./api-gateway ./api-gateway/src ./audit-compliance ./audit-compliance/src ./backup-recovery ./backup-recovery/src ./caching ./caching/src ./cloud-deployment ./cloud-deployment/src ./collaboration ./collaboration/src ./config ./config-management ./config-management/src ./config/claude-code ./config/claude-desktop ./config/docker ./data ./data-platform ./data-platform/src ./data/data-pipeline ./data/realtime-analytics ./database ./database/migrations ./database/schema ./demo ./dev-experience ./dev-experience/src ./dist ./dist/database ./dist/mcp ./dist/monitoring ./dist/orchestration ./dist/scripts ./dist/servers ./dist/shared ./dist/tests ./docs ./docs/api ./docs/architecture ./docs/command_outputs ./docs/context-maps ./docs/diagrams ``` ### Configuration Files ``` ./.eslintrc.js ./.pre-commit-config.yaml ./.prettierrc ./.vscode/mcp.json ./docker-compose.simple.yml ./docker-compose.yml ./jest.config.js ./package-lock.json ./package.json ./tsconfig.json ./tsconfig.minimal.json ./tsconfig.working.json ``` ## 🛠️ PROJECT-SPECIFIC COMMANDS (VERIFIED) ### Detected Package Manager: npm #### Node.js Commands ```bash # Install dependencies npm install # Available scripts (from package.json): # build: tsc # dev: tsx watch src/index.ts # start: node dist/index.js # test: jest # test:watch: jest --watch # test:coverage: jest --coverage # test:attention: node tests/run-tests.js unit # test:integration: node tests/run-tests.js integration # test:performance: node tests/run-tests.js performance # test:all: node tests/run-tests.js all npm run build npm run dev npm run start npm run test npm run test:watch npm run test:coverage npm run test:attention npm run test:integration npm run test:performance npm run test:all ``` ## 🧪 VERIFICATION PROCEDURES ### Immediate Health Checks 1. **Project Setup Verification**: ```bash cd /Users/robertlee/GitHubProjects/Claude_MCPServer npm install npm run build # Should complete without errors ``` 2. **Service Status Check**: ```bash # Check what should be running lsof -i :3000-9000 | grep LISTEN ``` 3. **Git Status Verification**: ```bash git status # Should match the status shown above git branch -vv # Shows tracking and sync status ``` ### Expected Working State - **Services**: Alternative Backend:8080 Admin/Monitoring:9000 - **Build**: Should complete without errors (see [build status](docs/command_outputs/build/build_test_status.md)) - **Tests**: Test script available ## 📝 SESSION WORKFLOW 1. **Start Session**: ✅ COMPLETED - This document created 2. **Begin Development**: Copy this document to Claude Code for full context 3. **Work on Tasks**: Use the evidence files in docs/ for current state 4. **Document Progress**: Run `/Users/robertlee/GitHubProjects/update-session-docs.sh` 5. **Update Documentation**: Provide generated templates to Claude ## 🚨 NEW DEVELOPER: WHAT AM I LOOKING AT? **You just opened a project. Here's EXACTLY what you're dealing with:** ### 🎯 PROJECT PURPOSE & REALITY CHECK **FIRST - What does this project actually DO?** **From README.md:** ``` # Claude MCP Server Ecosystem ## 🎯 Current Status: Week 11 COMPLETED ✅ ``` **Package.json description:** "Enterprise-grade MCP server ecosystem - Week 11 Complete: Data Management & Analytics" **What should you see when it works?** ❌ **No screenshots** - No visual reference for working state **Entry points detected:** ``` ``` ### 🔍 PROJECT HEALTH CHECK (INSTANT ASSESSMENT) | Component | Status | Action Required | Evidence | |-----------|--------|----------------|----------| | **Dependencies** | ✅ Installed | None | [Dependencies](docs/command_outputs/environment/system_info.md) | | **Build** | ❌ BROKEN/UNKNOWN | TEST: npm run build | [Build Status](docs/command_outputs/build/build_test_status.md) | | **Services** | ✅ Running | None | [Service Check](docs/command_outputs/services/service_status.md) | | **Git Status** | ✅ Clean | None | [Git Analysis](docs/command_outputs/git/) | ### 🎯 YOUR IMMEDIATE NEXT STEP (DO THIS NOW): **✅ PROJECT IS RUNNING** **Verification steps:** 1. Open browser: http://localhost:3000 (or check service ports below) 2. Expected: Should see actual application, not 404 or generic page 3. Services active: Alternative Backend:8080 Admin/Monitoring:9000 4. If you see placeholder/demo content: Project may be in early stage ### 🔬 5-MINUTE VERIFICATION TEST **Copy-paste this to verify the project actually works:** ```bash echo "=== VERIFICATION TEST STARTED ===" cd /Users/robertlee/GitHubProjects/Claude_MCPServer # Test 1: Dependencies echo '1. Checking dependencies...' [ -d 'node_modules' ] && echo '✅ Dependencies installed' || echo '❌ Run: npm install' # Test 2: Build reality check echo '2. Testing build...' BUILD_CMD=$(jq -r '.scripts.build // "none"' package.json) if [[ "$BUILD_CMD" == *echo* ]]; then echo '⚠️ Placeholder build detected' else echo '✅ Real build script found' fi # Test 3: Can it start? echo '3. Testing startup...' timeout 10 npm run dev & sleep 5 if curl -s http://localhost:3000 >/dev/null 2>&1; then echo '✅ Server responds' else echo '❌ No response on port 3000' fi pkill -f 'node.*dev' 2>/dev/null || true echo "=== VERIFICATION TEST COMPLETE ===" ``` **Expected results:** - ✅ Dependencies installed - ✅ Real build script OR ⚠️ Placeholder build - ✅ Server responds OR ❌ Configuration issue ### 🚨 WHAT'S BROKEN RIGHT NOW (SPECIFIC FAILURES): **BUILD FAILURES DETECTED:** ``` servers/security-vulnerability/src/security-vulnerability.ts(200,5): error TS1068: Unexpected token. A constructor, method, accessor, or property was expected. servers/security-vulnerability/src/security-vulnerability.ts(249,3): error TS1128: Declaration or statement expected. servers/security-vulnerability/src/security-vulnerability.ts(251,3): error TS1128: Declaration or statement expected. ``` **How to fix**: Check [build results](docs/command_outputs/build/build_test_status.md) **RECENT ERRORS FOUND (13):** ``` # Error Analysis and Recent Issues ./node_modules/simple-swizzle/node_modules/is-arrayish/yarn-error.log ## Recent Error Messages ``` **Full analysis**: [error_analysis.md](docs/command_outputs/errors/error_analysis.md) ### 📊 PROJECT CONTEXT (ESSENTIAL FACTS): - **What**: Node.js project - **Where**: Currently on branch `main` (0 ahead, 0 behind origin) - **When**: Last session , this is Session #1 - **Status**: No active task recorded ### 🔧 RECOVERY PROCEDURES (IF THINGS ARE BROKEN): #### If Build Fails: ```bash # 1. Clean install rm -rf node_modules package-lock.json yarn.lock npm install # 2. Check for conflicts npm run build # 3. If still fails, check: docs/command_outputs/build/build_test_status.md ``` #### If Services Won't Start: ```bash # 1. Check ports lsof -i :3000-9000 | grep LISTEN # 2. Kill conflicting processes killall node # 3. Restart npm run dev ``` #### If Git Issues: ```bash # 1. Save current work git stash # 2. Sync with remote git pull origin main # 3. Restore work git stash pop ``` ### 🚨 CRITICAL INFORMATION FOR NEW DEVELOPER ### What You Need to Know RIGHT NOW: 1. **Project Type**: Node.js with basic setup 2. **Current Branch**: main (0 ahead, 0 behind) 3. **Running Services**: Alternative Backend:8080 Admin/Monitoring:9000 4. **Last Session**: 5. **In Progress**: ### EVIDENCE FILES (ACTUAL CURRENT STATE): - 📊 [Git Status & History](docs/command_outputs/git/) - 🔧 [Environment & Dependencies](docs/command_outputs/environment/) - 🚀 [Services & Ports](docs/command_outputs/services/) - 🔨 [Build & Test Results](docs/command_outputs/build/) - ❌ [Error Analysis](docs/command_outputs/errors/) - 📸 [Screenshots](docs/screenshots/) --- **Session 1 initialized for Claude_MCPServer on 2025-05-23 at 11:29:57** *Complete evidence captured in docs/ directory - assume nothing, verify everything*

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/Coder-RL/Claude_MCPServer_Dev1'

If you have feedback or need assistance with the MCP directory API, please join our Discord server