AI MCP Gateway

#!/usr/bin/env node /** * Database migration script * Runs the schema.sql file to set up the database */ import { readFileSync } from 'fs'; import { join, dirname } from 'path'; import { fileURLToPath } from 'url'; import { Pool } from 'pg'; import { config } from 'dotenv'; // Load environment variables config(); const __filename = fileURLToPath(import.meta.url); const __dirname = dirname(__filename); async function runMigration() { console.log('🚀 Starting database migration...\n'); // Create database connection const pool = new Pool({ host: process.env.DB_HOST || 'localhost', port: parseInt(process.env.DB_PORT || '5432'), database: process.env.DB_NAME || 'ai_mcp_gateway', user: process.env.DB_USER || 'postgres', password: process.env.DB_PASSWORD, }); try { // Test connection await pool.query('SELECT NOW()'); console.log('✅ Database connection successful\n'); // Read schema file const schemaPath = join(__dirname, 'schema.sql'); const schema = readFileSync(schemaPath, 'utf-8'); console.log('📄 Running schema.sql...\n'); // Execute schema await pool.query(schema); console.log('✅ Database schema created successfully!\n'); // Show tables const tablesResult = await pool.query(` SELECT table_name FROM information_schema.tables WHERE table_schema = 'public' ORDER BY table_name; `); console.log('📊 Created tables:'); tablesResult.rows.forEach((row: { table_name: string }) => { console.log(` - ${row.table_name}`); }); console.log('\n✅ Migration completed successfully!'); } catch (error) { console.error('❌ Migration failed:'); console.error(error); process.exit(1); } finally { await pool.end(); } } // Run migration runMigration().catch((error) => { console.error('Fatal error:', error); process.exit(1); });