# LacyLights

> Use this tool when you need to automate theatrical lighting design tasks, such as script analysis and cue sequence creation, and manage complex lighting setups. The LacyLights system provides AI-powered lighting design capabilities, integrating script analysis, automated scene generation, and fixture management through a GraphQL-based interface. It generates contextually appropriate lighting designs and optimizes timing, making it ideal for lighting designers seeking to streamline their workflow and enhance creativity.

Canonical page: https://skillsregistry.net/skills/bbernstein-lacylights  
JSON: https://api.skillsregistry.net/v1/skills/bbernstein-lacylights

## Description

This MCP server provides AI-powered theatrical lighting design capabilities for the LacyLights system, integrating OpenAI's GPT-4 with GraphQL-based fixture management and DMX control. Built by bbernstein, it offers comprehensive tools for script analysis, automated scene generation with intelligent color mixing and intensity control, cue sequence creation with timing optimization, and fixture inventory management across multiple DMX universes. The implementation uses RAG (Retrieval-Augmented Generation) with lighting pattern matching to generate contextually appropriate lighting designs from theatrical scripts, making it valuable for lighting designers who want to automate repetitive design tasks, generate initial lighting concepts from script analysis, and manage complex multi-fixture setups with AI assistance rather than manual DMX programming.

## Trust

- **Trust score (0–1):** 0.00
- **Verification tier:** scanned
- **Last scanned:** 2026-09-19

## Facts

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

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/bbernstein-lacylights)
- **Repository:** <https://github.com/bbernstein/lacylights-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": "bbernstein-lacylights"
    }
  }
}
```

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