LacyLights
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.
Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately. Last scanned 2026-09-19.
Scan details: Circle-IR · 2026-09-19 · Appeal
View full trust & usage report →Metadata
- Version
- 1.0.0
- Skill type
- atomic
- Execution layer
- mcp-remote
- Category
- ai-ml
- Source
- PulseMCP
- Repository
- github.com/bbernstein/lacylights-mcp
- Author type
- human
- Last scanned
- 2026-09-19
- Updated
- 2026-09-19
Use via MCP
Resolve LacyLights from your agent
Streamable HTTP transport at https://api.skillsregistry.net/mcp. No auth for read tools. Discovery: .well-known/mcp.json.
One command in your shell — Claude Code wires it up and verifies the connection. Run /mcp in any session to confirm.
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp--scope user for --scope project to commit it to .mcp.json.