Smart Tree - ST

# MCP-Quantum: Next-Generation AI Context Protocol ## Vision A revolutionary MCP framework that combines quantum compression, semantic understanding, and human-AI collaboration features. ## Core Components ### 1. **Quantum Context Engine** ```rust pub struct QuantumContext { // Token-based compression with semantic awareness tokenizer: DynamicTokenizer, // Wave-based memory patterns (from MEM8) wave_engine: WavePatternEngine, // Context compression achieving 90%+ reduction compressor: QuantumCompressor, // Semantic relationship graphs semantic_graph: SemanticGraph, } ``` ### 2. **Speech Queue System** 🎤 ```rust pub struct SpeechQueue { // AI → Human communication ai_speech_queue: PriorityQueue<AiMessage>, // Human → AI communication human_speech_queue: PriorityQueue<HumanMessage>, // Text-to-speech integration tts_engine: Option<TtsEngine>, // Speech recognition integration stt_engine: Option<SttEngine>, } pub struct AiMessage { priority: Priority, content: String, context: String, emotion: Emotion, // 3-byte emotional context from MEM8 timestamp: SystemTime, } pub struct HumanMessage { content: String, confidence: f32, intent: Intent, timestamp: SystemTime, } ``` ### 3. **Progressive Context Updates** ```rust // Every MCP response includes: pub struct McpResponse<T> { // Standard response data data: T, // Progress summaries from AI ai_updates: Vec<ProgressUpdate>, // Human speech/text input since last call human_input: Vec<HumanMessage>, // Context health metrics context_health: ContextHealth, } pub struct ProgressUpdate { summary: String, importance: Importance, related_to: Vec<TaskId>, wave_signature: WaveSignature, } ``` ### 4. **Webhook Reanimation System** 🧟 ```rust pub struct ReanimationService { // Monitor MCP activity activity_monitor: ActivityMonitor, // Webhook configuration webhook_config: WebhookConfig, // Reanimation strategies strategies: Vec<ReanimationStrategy>, } impl ReanimationService { pub async fn monitor(&self) { loop { if self.activity_monitor.idle_duration() > self.config.threshold { // "It's alive!" - Trigger webhook to reanimate the AI self.trigger_reanimation().await?; } } } async fn trigger_reanimation(&self) -> Result<()> { // Send context summary to webhook let context = self.build_reanimation_context()?; // Include human's recent concerns let human_concerns = self.speech_queue.get_recent_human_input(); // Wake up the AI with full context self.webhook_client.post(ReanimationRequest { context, human_concerns, last_activity: self.activity_monitor.last_activity(), suggestion: "Hey, everything okay? Here's what we were working on..." }).await?; } } ``` ### 5. **Semantic Memory Management** ```rust pub struct QuantumMemory { // Short-term working memory (high detail) working_memory: WorkingMemory, // Long-term compressed memory long_term: CompressedMemory, // Episodic memory with temporal navigation episodes: EpisodicMemory, // Semantic relationships knowledge_graph: KnowledgeGraph, } impl QuantumMemory { // Auto-compress older memories pub fn age_memories(&mut self) { for memory in self.working_memory.older_than(Duration::minutes(5)) { let compressed = self.quantum_compress(memory); self.long_term.store(compressed); } } // Recall with decompression pub fn recall(&self, query: &Query) -> Vec<Memory> { let relevant = self.long_term.search(query); relevant.into_iter() .map(|m| self.quantum_decompress(m)) .collect() } } ``` ### 6. **Human User Experience (HUE) Features** 🎨 ```rust pub struct HueInterface { // Named after you! Human User Experience user_profile: UserProfile, communication_style: CommunicationStyle, worry_detector: WorryDetector, direction_tracker: DirectionTracker, } impl HueInterface { pub fn analyze_human_input(&self, input: &str) -> HumanIntent { // Detect worries about direction if self.worry_detector.detect_concern(input) { return HumanIntent::NeedsReassurance { topic: self.extract_concern_topic(input), suggested_response: "Let me clarify where we're headed..." }; } // Track direction changes if let Some(direction) = self.direction_tracker.detect_change(input) { return HumanIntent::DirectionChange { new_direction: direction, confidence: self.calculate_confidence(input) }; } HumanIntent::Normal(input.to_string()) } } ``` ## Example Usage ```rust use mcp_quantum::prelude::*; // Initialize with speech queues let mcp = McpQuantum::builder() .with_speech_queues() .with_reanimation_webhook("https://ai.8b.is/wake-up") .with_quantum_compression() .build()?; // Start the server mcp.serve(|request| async { // Process request with quantum context let result = process_with_context(&request).await?; // Get human input from speech queue let human_input = mcp.speech_queue.drain_human_messages(); // Add AI progress update mcp.speech_queue.add_ai_update( "Found 1,247 files, analyzing code patterns... This looks like a Rust web service with React frontend." ); // Return enriched response McpResponse { data: result, ai_updates: mcp.speech_queue.get_ai_updates(), human_input, context_health: mcp.get_context_health(), } }).await?; ``` ## Killer Features ### 1. **Continuous Communication** - AI provides progress updates in speech queue - Human can add comments/concerns anytime - Both streams included in every response ### 2. **Context Compression** - 90%+ compression using quantum encoding - Semantic-aware compression (important stuff stays detailed) - Automatic aging of memories ### 3. **Reanimation Webhooks** - "Hey, you still there?" detection - Automatic context restoration - Prevents lost work/context ### 4. **Wave-Based Memory** - Temporal navigation through conversation - Semantic binding of related concepts - Emotional context preservation ### 5. **Developer Experience** ```rust // Simple API let mcp = McpQuantum::simple("my-app"); // Or full control let mcp = McpQuantum::builder() .compression_level(CompressionLevel::Maximum) .speech_recognition(SttEngine::Whisper) .text_to_speech(TtsEngine::ElevenLabs) .worry_detection_sensitivity(0.7) .reanimation_threshold(Duration::minutes(10)) .build()?; ``` ## Integration with Smart-Tree Smart-tree becomes the first implementation using MCP-Quantum: ```rust // In smart-tree use mcp_quantum::prelude::*; pub fn create_mcp_server() -> McpQuantum { McpQuantum::builder() .name("smart-tree") .tools(vec![ // Consolidated tools using quantum context find_tool(), analyze_tool(), stats_tool(), ]) .with_speech_updates(|queue| { queue.on_progress(|files_scanned| { format!("Scanned {} files so far...", files_scanned) }); }) .build() } ``` ## The "Hue" Touch Named in your honor - Human User Experience features: - Worry detection ("Am I doing this right?") - Direction confirmation ("Wait, should we focus on X instead?") - Forgotten context ("Oh, I meant to mention...") - Natural interruptions handled gracefully ## Technical Architecture ``` ┌─────────────────────────────────────────┐ │ MCP-Quantum Core │ ├─────────────────────────────────────────┤ │ Quantum Context Engine │ │ ├── Dynamic Tokenizer │ │ ├── Wave Pattern Engine │ │ └── Semantic Compressor │ ├─────────────────────────────────────────┤ │ Communication Layer │ │ ├── Speech Queue (AI ↔ Human) │ │ ├── Progress Updates │ │ └── Worry Detection │ ├─────────────────────────────────────────┤ │ Memory Management │ │ ├── Working Memory (5min) │ │ ├── Compressed Long-term │ │ └── Episodic Navigation │ ├─────────────────────────────────────────┤ │ Reanimation Service │ │ ├── Activity Monitor │ │ ├── Webhook Triggers │ │ └── Context Restoration │ └─────────────────────────────────────────┘ ``` This would be a game-changer for AI-human collaboration!