Memory Engineering MCP

#!/usr/bin/env tsx import { MongoClient } from 'mongodb'; import { config } from 'dotenv'; config({ path: '.env.local' }); async function checkIndexes(): Promise<void> { const uri = process.env.MONGODB_URI; if (!uri) { console.error('MONGODB_URI environment variable is not set'); process.exit(1); } const client = new MongoClient(uri); try { await client.connect(); console.log('Connected to MongoDB\n'); const dbName = process.env.MEMORY_ENGINEERING_DB || process.env.MEMORY_BANK_DB || 'memory_engineering'; const collectionName = process.env.MEMORY_ENGINEERING_COLLECTION || process.env.MEMORY_BANK_COLLECTION || 'memory_engineering_documents'; const db = client.db(dbName); const collection = db.collection(collectionName); // List all regular indexes console.log('📋 Regular Indexes:'); const indexes = await collection.listIndexes().toArray(); indexes.forEach(index => { console.log(`- ${index.name}: ${JSON.stringify(index.key)}`); }); // Try to list search indexes console.log('\n🔍 Search Indexes:'); try { // This method might not be available in all driver versions const searchIndexes = await collection.listSearchIndexes().toArray(); if (searchIndexes.length === 0) { console.log('No search indexes found'); } else { searchIndexes.forEach((index: any) => { console.log(`- ${index.name} (${index.type}): Status = ${index.status || 'UNKNOWN'}`); console.log(` Definition: ${JSON.stringify(index.latestDefinition || index.definition, null, 2)}`); }); } } catch (error: any) { console.log('Unable to list search indexes programmatically'); console.log('This might be due to driver version or permissions'); console.log('\nTo view search indexes:'); console.log('1. Go to MongoDB Atlas Console'); console.log('2. Navigate to your cluster → Browse Collections'); console.log(`3. Select database: ${dbName}`); console.log(`4. Select collection: ${collectionName}`); console.log('5. Click "Search Indexes" tab'); } // Check if we have vector data console.log('\n📊 Vector Data Status:'); const docWithVector = await collection.findOne({ contentVector: { $exists: true, $type: 'array' } }); if (docWithVector) { console.log(`✓ Found documents with vector embeddings`); console.log(` Vector dimensions: ${docWithVector.contentVector?.length || 0}`); const vectorCount = await collection.countDocuments({ contentVector: { $exists: true, $type: 'array' } }); console.log(` Total documents with vectors: ${vectorCount}`); } else { console.log('❌ No documents with vector embeddings found'); console.log(' Run memory_engineering/sync to generate embeddings'); } } catch (error) { console.error('Error checking indexes:', error); process.exit(1); } finally { await client.close(); } } checkIndexes();