# mixi-mcp

> Use this tool when you need to conduct spatial preference interviews for the MIXI lighting brand, solving issues of inefficient data collection and analysis for lighting design preferences. It takes user inputs via Claude.ai and outputs results saved to Cloudflare KV, streamlining the interview process. Ideal for use cases requiring centralized storage and analysis of user preferences for informed lighting design decisions.

Canonical page: https://skillsregistry.net/skills/caffeineworks-ai-mixi-mcp  
JSON: https://api.skillsregistry.net/v1/skills/caffeineworks-ai-mixi-mcp

## Description

Enables conducting spatial preference interviews for the MIXI lighting brand via Claude.ai, with results saved to Cloudflare KV.

## Trust

- **Trust score (0–1):** 0.70
- **Verification tier:** verified
- **Last scanned:** 2026-08-30

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** cloud-infra
- **Updated:** 2026-08-30

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/j5rgcpgt4f)
- **Repository:** <https://github.com/caffeineworks-ai/mixi-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": "caffeineworks-ai-mixi-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/caffeineworks-ai-mixi-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/caffeineworks-ai-mixi-mcp/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