CHECKPOINT: Brainy 2.0 API refactor - pre-fixes state

Current state:
- Unified augmentation system to BrainyAugmentation interface
- Changed methods to specific noun/verb naming (addNoun, getNoun, etc)
- Made old methods private
- Combined getNouns into single unified method
- Neural API exists and is complete
- Triple Intelligence uses correct Brainy operators (not MongoDB)

Issues identified:
- Documentation incorrectly shows MongoDB operators (code is correct)
- Need to ensure all features are properly exposed
- Need to verify nothing was lost in simplification

This commit serves as a rollback point before applying fixes.

examples/api-server-example.ts

@@ -0,0 +1,105 @@
+/**
+ * API Server Example
+ * 
+ * This example shows how to expose Brainy through REST, WebSocket, and MCP APIs
+ * using the APIServerAugmentation.
+ * 
+ * Zero-config philosophy: Just create and register the augmentation!
+ */
+
+import { BrainyData } from '../src/index.js'
+import { APIServerAugmentation } from '../src/augmentations/apiServerAugmentation.js'
+
+async function main() {
+  // 1. Create Brainy with zero config
+  const brain = new BrainyData()
+  await brain.init()
+  
+  // 2. Add some sample data
+  await brain.add("The quick brown fox", { type: "sentence", category: "animals" })
+  await brain.add("Machine learning models", { type: "tech", category: "AI" })
+  await brain.add("Natural language processing", { type: "tech", category: "NLP" })
+  
+  // 3. Create and register the API Server augmentation
+  const apiServer = new APIServerAugmentation({
+    port: 3000,
+    host: 'localhost'
+  })
+  
+  // Register the augmentation with Brainy
+  brain.augmentations.register(apiServer)
+  
+  // Initialize augmentations with Brainy context
+  await brain.augmentations.initialize({
+    brain,
+    log: (msg: string, level?: string) => console.log(`[${level || 'info'}] ${msg}`),
+    config: {}
+  })
+  
+  console.log('🚀 Brainy API Server is running!')
+  console.log('📡 REST API: http://localhost:3000')
+  console.log('🔌 WebSocket: ws://localhost:3000/ws')
+  console.log('🧠 MCP: http://localhost:3000/api/mcp')
+  console.log('')
+  console.log('Try these endpoints:')
+  console.log('  GET  http://localhost:3000/health')
+  console.log('  POST http://localhost:3000/api/search')
+  console.log('       Body: { "query": "fox", "limit": 10 }')
+  console.log('  POST http://localhost:3000/api/add')
+  console.log('       Body: { "content": "New data", "metadata": {} }')
+  console.log('')
+  console.log('Press Ctrl+C to stop the server')
+}
+
+// Run the example
+main().catch(console.error)
+
+/**
+ * Example REST API calls:
+ * 
+ * # Health check
+ * curl http://localhost:3000/health
+ * 
+ * # Search
+ * curl -X POST http://localhost:3000/api/search \
+ *   -H "Content-Type: application/json" \
+ *   -d '{"query": "fox", "limit": 5}'
+ * 
+ * # Add data
+ * curl -X POST http://localhost:3000/api/add \
+ *   -H "Content-Type: application/json" \
+ *   -d '{"content": "The cat sat on the mat", "metadata": {"type": "sentence"}}'
+ * 
+ * # Get by ID
+ * curl http://localhost:3000/api/get/[id]
+ * 
+ * # Statistics
+ * curl http://localhost:3000/api/stats
+ */
+
+/**
+ * Example WebSocket client (browser):
+ * 
+ * const ws = new WebSocket('ws://localhost:3000/ws')
+ * 
+ * ws.onopen = () => {
+ *   // Subscribe to all operations
+ *   ws.send(JSON.stringify({
+ *     type: 'subscribe',
+ *     operations: ['all']
+ *   }))
+ *   
+ *   // Perform a search
+ *   ws.send(JSON.stringify({
+ *     type: 'search',
+ *     query: 'fox',
+ *     limit: 5,
+ *     requestId: '123'
+ *   }))
+ * }
+ * 
+ * ws.onmessage = (event) => {
+ *   const msg = JSON.parse(event.data)
+ *   console.log('Received:', msg)
+ * }
+ */