AI Agent Memory
Made Simple

// Auto Tool Generation for AI Agents
import { mindcache } from 'mindcache';
import { generateText } from 'ai';

// Store user preferences and context
mindcache.set_value('userName', 'Alice', { tags: ['user'] });
mindcache.set_value('favoriteColor', 'blue', { tags: ['preferences'] });
mindcache.set_value('lastTask', 'planning vacation', { tags: ['context'] });

// Automatically generate tool schemas for Vercel AI SDK
const tools = mindcache.get_aisdk_tools();
// Returns: {
//   write_userName: { description: "...", parameters: {...} },
//   write_favoriteColor: { description: "...", parameters: {...} },
//   write_lastTask: { description: "...", parameters: {...} }
// }

// Generate system prompt with memory context
const systemPrompt = mindcache.get_system_prompt();
// "userName: Alice. You can rewrite \"userName\" by using..."
// "favoriteColor: blue. You can rewrite \"favoriteColor\" by..."
// "$date: 2025-01-15"

// Use with AI SDK - tools are automatically available
const { text, toolCalls } = await generateText({
  model: openai('gpt-4'),
  tools: tools, // AI can now call write_userName(), etc.
  system: systemPrompt,
  prompt: 'Remember that I love green now, not blue.'
});

// AI will automatically call write_favoriteColor('green')
// and the memory is updated automatically

// Context Management with Tags & System Prompts
import { mindcache } from 'mindcache';

// Set items with or without tags
mindcache.set_value('tempNote', 'Meeting at 3pm');
mindcache.set_value('userName', 'Alice', { tags: ['context'] });
mindcache.set_value('userRole', 'developer', { tags: ['context'] });
mindcache.set_value('projectName', 'MindCache', { tags: ['context'] });


// Extract only tagged context for focused prompts
const contextData = mindcache.getTagged('context');
// "userName: Alice, userRole: developer, projectName: MindCache"

// Generate system prompt with all visible keys
const fullSystemPrompt = mindcache.get_system_prompt();
// Includes all keys: userName, userRole, projectName, tempNote

// Or create focused context from tagged items only
const focusedContext = `Context: ${contextData}
Instructions: You are helping ${mindcache.get_value('userName')} 
with their ${mindcache.get_value('projectName')} project.`;

// Use focused context for specific workflows
// Or use full system prompt for comprehensive memory access

// Filter keys by tag programmatically
const allKeys = Object.keys(mindcache.getAll());
const contextKeys = allKeys.filter(key => 
  mindcache.hasTag(key, 'context')
);
// ['userName', 'userRole', 'projectName']

// MindCache Cloud Sync
import { MindCache } from 'mindcache';

// Connect to MindCache Cloud with built-in sync
const mc = new MindCache({
  cloud: {
    instanceId: 'my-instance-id',
    tokenEndpoint: '/api/ws-token', // Your API endpoint
  }
});

// Same API as local — now with cloud persistence!
mc.set_value('userName', 'Alice');
mc.set_value('notes', 'Meeting at 3pm', { tags: ['important'] });

// Real-time sync across all connected clients
mc.subscribeToAll(() => {
  console.log('Data synced from cloud!');
});

// Check connection state
console.log(mc.connectionState); // 'connected'
console.log(mc.isLoaded);        // true when initial sync done
console.log(mc.isCloud);         // true

// AI tools work the same way
const tools = mc.get_aisdk_tools();
const prompt = mc.get_system_prompt();

// Clean up when done
mc.disconnect();