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Camera Control Implementation Plan

Phase 1: MQTT Connector (Immediate)

Goal: Create lightweight MQTT bridge to Camera MCP Server

Components to Build

  1. MQTT Connector (/Users/j/Code/mcp/camera_mqtt_connector.py)

    • Subscribe to MQTT PTZ commands
    • Forward to Camera MCP Server via JSON-RPC
    • Publish responses back to MQTT
    • Handle connection management

  2. Configuration

    • MQTT broker settings
    • Camera MCP Server connection
    • Topic structure for commands/responses

MQTT Topic Structure

camera/ptz/command       # Incoming PTZ commands
camera/ptz/response      # PTZ command results
camera/screenshot/command # Screenshot requests
camera/screenshot/response # Screenshot data (base64)
camera/status/request    # Status queries
camera/status/response   # Camera status info

Phase 2: Testing & Validation

  1. Local Testing

    • Start Camera MCP Server
    • Start MQTT Connector
    • Send test commands via MQTT
    • Verify PTZ execution and responses

  2. Multi-Camera Testing

    • Multiple camera instances
    • Topic routing by camera ID
    • Concurrent command handling

Phase 3: athena Integration

  1. Direct MCP Integration OR MQTT Bridge
  2. AI Vision Pipeline using screenshot capability
  3. Automated PTZ positioning based on vision analysis

Implementation Priority

  1. ✅ Camera MCP Server (Complete)
  2. 🔄 MQTT Connector (Next)
  3. ⏳ Multi-camera scaling
  4. ⏳ athena integration

Date: 2025-06-07