# CheerLights

> Use this tool when you need to integrate CheerLights data into AI conversations, allowing users to retrieve current colors and history from the global light synchronization project. It solves the problem of accessing CheerLights data directly within AI interfaces, providing a bridge between AI assistants and the IoT ecosystem. The tool takes API requests as input and outputs current colors and recent color change history, making it ideal for IoT enthusiasts and developers who want to enhance their AI conversations with real-time CheerLights data.

Canonical page: https://skillsregistry.net/skills/cheerlights  
JSON: https://api.skillsregistry.net/v1/skills/cheerlights

## Description

CheerLights MCP Server provides a bridge between Claude and the CheerLights IoT ecosystem, allowing AI assistants to retrieve current colors and history from the global light synchronization project. Built by Hans Scharler, this Python implementation uses FastMCP and httpx to connect with the ThingSpeak API, offering tools to fetch the current CheerLights color and view recent color change history. The server parses timestamp data into readable formats and includes proper error handling, making it ideal for IoT enthusiasts who want to integrate CheerLights data directly into their AI conversations without leaving the interface.

## Trust

- **Trust score (0–1):** 0.85
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** iot-hardware
- **Updated:** 2026-09-19

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/cheerlights)
- **Repository:** <https://github.com/cheerlights/cheerlights-mcp>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "cheerlights"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/cheerlights` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/cheerlights/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt