IntelliGlow

IntelliGlow

A Model Context Protocol (MCP) server that allows AI assistants like Claude to control real smart bulbs via UDP network communication, featuring voice commands, AI reasoning, and direct hardware control.

Category
Visit Server

README

💡 IntelliGlow - AI-Powered Smart Lighting

"Smart lighting, brilliantly simple"

IntelliGlow is a Model Context Protocol (MCP) server that allows AI assistants like Claude to control real smart bulbs via UDP network communication. This Python implementation features voice commands, AI reasoning, and direct hardware control.

🏗️ Architecture

Voice/AI ──> IntelliGlow MCP ──> UDP Network ──> Smart Bulb (192.168.1.45:4000)

The smart bulb system that actually thinks!

🌟 Features

🔴 Real Hardware Support

  • UDP Network Communication: Direct communication with real smart bulbs
  • Default Bulb Configuration: Connects to 192.168.1.45:4000 by default
  • Network Discovery: Automatically find smart bulbs on your network
  • Connection Management: Persistent connections with auto-reconnect

🎤 Voice Intelligence

  • Natural Voice Commands: "Turn on lights", "Set brightness to 75", "Make it blue"
  • AI-Powered Parsing: Understands context and natural language
  • Text-to-Speech Feedback: Speaks responses back to you
  • Smart Color Recognition: Recognizes color names and descriptive terms

🧠 AI Integration

  • MCP Protocol: Works with Claude, GPT, and other AI models
  • Context Understanding: AI can reason about lighting needs
  • Workflow Integration: Bulbs become part of larger AI workflows
  • Learning Capability: Can adapt to user patterns and preferences

🔧 Smart Bulb Control

  • Power Control: Turn bulbs on/off via UDP commands
  • Brightness Control: Adjust brightness levels (0-100%)
  • Color Control: Full RGB control with hex color codes (#FF0000)
  • Status Monitoring: Get real-time bulb status
  • Ping/Connectivity: Test network connectivity to bulbs

🌐 Network Features

  • Multi-bulb Support: Connect to multiple bulbs simultaneously
  • Discovery: Scan network for available smart bulbs
  • Environment Configuration: Set bulb IP/port via environment variables

🚀 Quick Start

Installation

  1. Install IntelliGlow:

    # Core system
    pip install -e .
    
    # With voice capabilities
    pip install -e .[voice]
    
  2. Configure your bulb (optional):

    export BULB_IP=192.168.1.45    # Your bulb's IP
    export BULB_PORT=4000          # Your bulb's port
    

Running IntelliGlow

# 1. MCP server only (for AI integration)
mcp-server-smartbulb

# 2. Voice interface only
mcp-server-smartbulb-voice

# 3. Complete IntelliGlow system (voice + AI + MCP)
python voice_enabled_server.py

Testing Network Connectivity

# Test UDP communication with your real bulb
python test_network_bulbs.py

🔧 AI Integration (Claude Desktop)

Add this to your Claude Desktop claude_desktop_config.json:

{
  "mcpServers": {
    "intelliglow": {
      "command": "python",
      "args": ["-m", "mcp_server_smartbulb.network_server"],
      "cwd": "/path/to/your/IntelliGlow",
      "env": {
        "BULB_IP": "192.168.1.45",
        "BULB_PORT": "4000"
      }
    }
  }
}

🛠️ Available Commands

🎤 Voice Commands

  • "Turn on the lights" - Power control
  • "Set brightness to 75 percent" - Brightness with smart parsing
  • "Make it blue" - Color recognition
  • "How are the lights?" - Status inquiry
  • "Find smart bulbs" - Network discovery

🤖 MCP Tools (for AI)

  • discover_bulbs() - Find smart bulbs on the network
  • connect_to_bulb(ip, port) - Connect to a specific bulb
  • turn_on_bulb(ip, port) - Turn on a bulb via UDP
  • turn_off_bulb(ip, port) - Turn off a bulb via UDP
  • set_bulb_brightness(brightness, ip, port) - Set brightness (0-100)
  • set_bulb_color(color, ip, port) - Set color using hex codes
  • get_bulb_status(ip, port) - Get current bulb status
  • ping_bulb(ip, port) - Test connectivity to a bulb

📡 Network Configuration

Default Bulb Setup

IntelliGlow connects to 192.168.1.45:4000 by default. You can override this:

export BULB_IP=192.168.1.100
export BULB_PORT=4001

Bulb Configuration File

Create bulb_config.json:

{
  "default_bulb": {
    "ip": "192.168.1.45",
    "port": 4000,
    "timeout": 5.0
  },
  "discovery": {
    "enabled": true,
    "timeout": 10.0,
    "port_range": {
      "start": 4000,
      "end": 4010
    }
  }
}

🔍 IntelliGlow vs Traditional Solutions

Feature Alexa/Google IntelliGlow
Voice Control ✅ Basic commands ✅ Natural language + AI reasoning
AI Integration ❌ Limited ecosystem ✅ Works with any AI model (Claude, GPT, etc.)
Hardware Control ❌ Cloud-dependent ✅ Direct UDP networking
Customization ❌ Vendor limitations ✅ Full control over protocol
Context Understanding ❌ Simple keywords ✅ AI understands context and workflows
Privacy ❌ Cloud processing ✅ Local processing
Developer Freedom ❌ Closed ecosystem ✅ Open protocol, extensible

Result: IntelliGlow = Convenience of Alexa + Intelligence of AI + Freedom of Open Source! 🎉

🧪 Testing

# Test real UDP communication with your bulb
python test_network_bulbs.py

This will:

  1. 🔌 Test direct connection to 192.168.1.45:4000
  2. 🔍 Scan network for other bulbs
  3. 🤖 Simulate AI/MCP commands
  4. 🎤 Test voice command processing

🐛 Troubleshooting

No Bulb Found

  • Ensure your smart bulb is on the same network
  • Check that the bulb is listening on port 4000
  • Try network discovery: python -c "import asyncio; from mcp_server_smartbulb.bulb_discovery import BulbDiscovery; asyncio.run(BulbDiscovery().discover_bulbs())"

Voice Not Working

  • Install voice dependencies: pip install -e .[voice]
  • Check microphone permissions
  • Test with: python -m mcp_server_smartbulb.voice_interface

Connection Timeout

  • Check firewall settings
  • Verify bulb IP address
  • Increase timeout in bulb_config.json

📁 Project Structure

IntelliGlow/
├── mcp_server_smartbulb/
│   ├── __init__.py              # Package initialization 
│   ├── network_server.py        # Main UDP-enabled MCP server
│   ├── udp_client.py           # UDP networking client
│   ├── bulb_discovery.py       # Network discovery
│   └── voice_interface.py      # Voice command processing
├── bulb_config.json            # Network configuration
├── test_network_bulbs.py       # UDP testing script
├── voice_enabled_server.py     # Complete IntelliGlow system
├── README.md                   # This file
└── pyproject.toml              # Project configuration

Clean, focused, and intelligent! 🧠💡

🎯 What Makes IntelliGlow Special

IntelliGlow isn't just another smart bulb controller - it's the bridge between AI intelligence and physical hardware.

🔥 Key Innovations:

  • AI-Native Design: Built for AI reasoning, not just voice commands
  • Open Protocol: Works with any AI model, not locked to one vendor
  • Local Processing: Privacy-focused, no cloud dependency required
  • Hybrid Interface: Voice + AI chat + MCP protocol
  • Developer Freedom: Full customization and extensibility

🌟 Real-World Magic:

User: "I'm working late and need focus lighting"
IntelliGlow: 
→ AI understands context
→ Sets cool white light (5000K)
→ Optimal brightness (85%)
→ Direct UDP communication
→ Responds with confirmation

This is the future of smart homes - lighting that truly understands and adapts to your needs! 🚀


Made with ❤️ for the next generation of intelligent home automation

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured