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CheerLights MCP Server: AI-Powered Real-Time Lighting Control - MCP Implementation

CheerLights MCP Server: AI-Powered Real-Time Lighting Control

The CheerLights MCP Server bridges AI tools with real-time lighting control via the CheerLights API, empowering developers to build smart ecosystems effortlessly.

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About CheerLights MCP Server

What is CheerLights MCP Server: AI-Powered Real-Time Lighting Control?

CheerLights MCP Server is an intermediary tool enabling AI systems like Claude to interact with the global CheerLights IoT network. This server acts as a bridge between AI platforms and the CheerLights API, allowing users to query live color data and track changes across millions of synchronized lights worldwide. By leveraging the Model Context Protocol (MCP), it provides a seamless interface for AI-driven control and monitoring of this decentralized lighting ecosystem.

Key Features of CheerLights MCP Server: AI-Powered Real-Time Lighting Control?

  • Instant access to the current global CheerLights color via natural language queries
  • Historical analytics showing chronological color transitions
  • Real-time API synchronization with the official CheerLights data stream
  • Platform compatibility for desktop AI tools like Claude for Desktop

CheerLights MCP Server Features

How to use CheerLights MCP Server: AI-Powered Real-Time Lighting Control?

Follow these steps to operationalize the server:

  1. Install dependencies using pip install mcp httpx
  2. Deploy the server script via python server.py
  3. Configure your AI desktop client by editing the claude_desktop_config.json file with server parameters
  4. Query via natural language prompts like "Display recent color changes" to trigger API interactions

Use cases of CheerLights MCP Server: AI-Powered Real-Time Lighting Control?

Practical applications include:

  • Automated color updates for smart home lighting systems based on global CheerLights trends
  • Interactive educational demonstrations showing distributed system coordination
  • Event coordination through synchronized lighting effects triggered by AI commands
  • Historical pattern analysis for color popularity trends using query logs

CheerLights MCP Server FAQ

FAQ from CheerLights MCP Server: AI-Powered Real-Time Lighting Control?

Q: Does this require programming knowledge?
Only basic Python command line usage - the server handles all API interactions automatically.

Q: Which AI tools are supported?
Currently optimized for Claude for Desktop but compatible with any MCP-enabled AI platform.

Q: How often does the color data update?
Real-time updates are pulled directly from the CheerLights API endpoint here every 15 seconds.

Content

CheerLights MCP Server

A Model Context Protocol (MCP) server that allows Claude or other AI tools to interact with the CheerLights API. CheerLights is a global IoT project that synchronizes colors across connected lights worldwide.

Features

  • Get the current CheerLights color
  • View recent color change history
  • Real-time integration with the CheerLights API

Installation

First, install the necessary dependencies:

pip install mcp httpx

Running the Server

Save the code to a file (e.g., server.py) and run it:

python server.py

Connecting to Claude for Desktop

Add this to your Claude for Desktop configuration:

  • Windows: %APPDATA%\Claude\claude_desktop_config.json

  • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json

    {
    "mcpServers": {
    "cheerlights": {
    "command": "python",
    "args": ["path/to/server.py"]
    }
    }
    }

Using with Claude

After restarting Claude for Desktop, you can ask questions like:

  • "What's the current CheerLights color?"
  • "Show me the last 10 CheerLights color changes"

API Reference

The server uses the CheerLights API endpoint: http://api.thingspeak.com/channels/1417/field/1/last.json

Blog Tutorial

Learn How to Create Your Own MCP Server for Claude Desktop and Windsurf

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