# Divoom LAN

> Use this tool when you need to control and customize Divoom watchfaces on a local network, solving problems such as limited device connectivity and lack of automation. It provides a range of tools and inputs, including watchface information retrieval and settings patching, with outputs such as adjusted brightness and screen state. Use it in contexts where cloud connectivity is not required or available, and LAN-based control is preferred.

Canonical page: https://skillsregistry.net/skills/divoom-lan  
JSON: https://api.skillsregistry.net/v1/skills/divoom-lan

## Description

This MCP server wraps Divoom's local network APIs to expose watchface control as standard MCP tools for AI clients. It provides 12+ tools for retrieving watchface information, patching settings such as fonts and colors, switching between watchfaces, adjusting brightness, toggling screen state, uploading files, creating new watchfaces, and executing raw device commands. The server communicates with Divoom devices over LAN without requiring cloud connectivity.

## Trust

- **Trust score (0–1):** 0.64
- **Verification tier:** scanned
- **Last scanned:** 2026-09-01

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** file-system
- **Updated:** 2026-09-01

## Source

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

## 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": "divoom-lan"
    }
  }
}
```

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