homeassistant-mcp/docs/architecture.md

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Architecture Overview 🏗️

This document describes the architecture of the MCP Server, explaining how different components work together to provide a bridge between Home Assistant and Language Learning Models.

System Architecture

graph TD
    subgraph "Client Layer"
        WC[Web Clients]
        MC[Mobile Clients]
        VC[Voice Assistants]
    end

    subgraph "MCP Server"
        API[API Gateway]
        NLP[NLP Engine]
        SSE[SSE Manager]
        WS[WebSocket Server]
        CM[Command Manager]
        SC[Scene Controller]
        Cache[Redis Cache]
    end

    subgraph "Home Assistant"
        HA[Home Assistant Core]
        Dev[Devices & Services]
    end

    subgraph "AI Layer"
        LLM[Language Models]
        IC[Intent Classifier]
        NER[Named Entity Recognition]
    end

    WC --> |HTTP/WS| API
    MC --> |HTTP/WS| API
    VC --> |HTTP| API
    
    API --> |Events| SSE
    API --> |Real-time| WS
    API --> |Process| NLP
    
    NLP --> |Query| LLM
    NLP --> |Extract| IC
    NLP --> |Identify| NER
    
    CM --> |Execute| HA
    HA --> |Control| Dev
    
    SSE --> |State Updates| WC
    SSE --> |State Updates| MC
    WS --> |Bi-directional| WC
    
    Cache --> |Fast Access| API
    HA --> |Events| Cache

Component Details

1. Client Layer

The client layer consists of various interfaces that interact with the MCP Server:

• Web Clients: Browser-based dashboards and control panels
• Mobile Clients: Native mobile applications
• Voice Assistants: Voice-enabled devices and interfaces

2. MCP Server Core

API Gateway

• Handles all incoming HTTP requests
• Manages authentication and rate limiting
• Routes requests to appropriate handlers

interface APIGateway {
    authenticate(): Promise<boolean>;
    rateLimit(): Promise<boolean>;
    route(request: Request): Promise<Response>;
}

NLP Engine

• Processes natural language commands
• Integrates with Language Models
• Extracts intents and entities

interface NLPEngine {
    processCommand(text: string): Promise<CommandIntent>;
    extractEntities(text: string): Promise<Entity[]>;
    validateIntent(intent: CommandIntent): boolean;
}

Event Management

• SSE Manager: Handles Server-Sent Events
• WebSocket Server: Manages bi-directional communication
• Command Manager: Processes and executes commands

3. Home Assistant Integration

The server maintains a robust connection to Home Assistant through:

• REST API calls
• WebSocket connections
• Event subscriptions

interface HomeAssistantClient {
    connect(): Promise<void>;
    getState(entityId: string): Promise<EntityState>;
    executeCommand(command: Command): Promise<CommandResult>;
    subscribeToEvents(callback: EventCallback): Subscription;
}

4. AI Layer

Language Model Integration

• Processes natural language input
• Understands context and user intent
• Generates appropriate responses

Intent Classification

• Identifies command types
• Extracts parameters
• Validates requests

Data Flow

1. Command Processing

sequenceDiagram
    participant Client
    participant API
    participant NLP
    participant LLM
    participant HA
    
    Client->>API: Send command
    API->>NLP: Process text
    NLP->>LLM: Get intent
    LLM-->>NLP: Return structured intent
    NLP->>HA: Execute command
    HA-->>API: Return result
    API-->>Client: Send response

2. Real-time Updates

sequenceDiagram
    participant HA
    participant Cache
    participant SSE
    participant Client
    
    HA->>Cache: State change
    Cache->>SSE: Notify change
    SSE->>Client: Send update
    Note over Client: Update UI

3. SSE API

• Event Subscriptions
• Real-time Updates
• Connection Management

Security Architecture

Authentication Flow

1. JWT-based Authentication

   interface AuthToken {
       token: string;
       expires: number;
       scope: string[];
   }
   

2. Rate Limiting

   interface RateLimit {
       window: number;
       max: number;
       current: number;
   }
   

Security Measures

• TLS encryption for all communications
• Input sanitization
• Request validation
• Token-based authentication
• Rate limiting
• IP filtering

Performance Optimizations

Caching Strategy

graph LR
    Request --> Cache{Cache?}
    Cache -->|Hit| Response
    Cache -->|Miss| HA[Home Assistant]
    HA --> Cache
    Cache --> Response

Connection Management

• Connection pooling
• Automatic reconnection
• Load balancing
• Request queuing

Configuration

The system is highly configurable through environment variables and configuration files:

server:
  port: 3000
  host: '0.0.0.0'
  
homeAssistant:
  url: 'http://homeassistant:8123'
  token: 'YOUR_TOKEN'
  
security:
  jwtSecret: 'your-secret'
  rateLimit: 100
  
ai:
  model: 'gpt-4'
  temperature: 0.7
  
cache:
  ttl: 300
  maxSize: '100mb'

Deployment Architecture

Docker Deployment

graph TD
    subgraph "Docker Compose"
        MCP[MCP Server]
        Redis[Redis Cache]
        HA[Home Assistant]
    end
    
    MCP --> Redis
    MCP --> HA

Scaling Considerations

• Horizontal scaling capabilities
• Load balancing support
• Redis cluster support
• Multiple HA instance support

Further Reading

• API Documentation
• Installation Guide
• Contributing Guidelines
• Troubleshooting