LacyLights MCP Server

An MCP (Model Context Protocol) server that provides AI-powered theatrical lighting design capabilities for the LacyLights system. This server enables AI assistants to create, manage, and control professional theatrical lighting designs through natural language interactions.

What is LacyLights MCP?

LacyLights MCP is an intelligent lighting control interface that bridges the gap between creative vision and technical execution. It allows lighting designers, directors, and technicians to:

• Design lighting looks using natural language descriptions
• Analyze theatrical scripts to automatically generate lighting cues
• Manage DMX fixtures from various manufacturers
• Create and run cue sequences for theatrical performances
• Optimize lighting designs for dramatic impact or energy efficiency

The system uses AI to understand artistic intent and translate it into precise DMX values for real-world lighting fixtures.

Complete Function Reference

Project Management

• `list_projects` - List all available lighting projects with optional fixture/look counts
• `create_project` - Create a new lighting project for a production
• `get_project_details` - Get comprehensive details about a specific project
• `delete_project` - Delete a project and all associated data (requires confirmation)
• `qlc_import_guidance` - Get information about importing QLC+ (.qxw) files

Fixture Management

• `get_fixture_inventory` - Query available fixtures and their capabilities
• `analyze_fixture_capabilities` - Deep analysis of fixture capabilities (color mixing, positioning, effects)
• `create_fixture_instance` - Add a new fixture to a project with manufacturer/model details
• `get_channel_map` - View DMX channel usage map for a project
• `suggest_channel_assignment` - Get optimal channel assignments for multiple fixtures
• `update_fixture_instance` - Modify existing fixture properties
• `delete_fixture_instance` - Remove a fixture from a project (requires confirmation)

Look Creation & Management

• `generate_look` - AI-powered look generation based on descriptions and context
• `analyze_script` - Extract lighting cues and suggestions from theatrical scripts
• `optimize_look` - Optimize looks for various goals (energy, impact, simplicity)
• `update_look` - Update look properties and fixture values
• `activate_look` - Activate a look by name or ID
• `fade_to_black` - Fade all lights to black with customizable timing
• `get_current_active_look` - Get information about the currently active look

Advanced Look Operations

• `add_fixtures_to_look` - Add fixtures to existing looks
• `remove_fixtures_from_look` - Remove specific fixtures from looks
• `get_look_fixture_values` - Read current fixture values in a look
• `ensure_fixtures_in_look` - Ensure fixtures exist with specific values
• `update_look_partial` - Partial look updates with fixture merging
• `bulk_update_looks_partial` - Batch partial updates across multiple looks with fixture merging

Cue Sequence Management

• `create_cue_sequence` - Build cue sequences from existing looks
• `generate_act_cues` - Generate complete cue lists for theatrical acts
• `optimize_cue_timing` - Optimize cue timing for various strategies
• `analyze_cue_structure` - Analyze cue lists with recommendations

Cue List Operations

• `update_cue_list` - Update cue list metadata
• `add_cue_to_list` - Add new cues to existing lists
• `remove_cue_from_list` - Remove cues from lists
• `update_cue` - Modify individual cue properties
• `bulk_update_cues` - Update multiple cues simultaneously
• `reorder_cues` - Reorder cues with new numbering
• `get_cue_list_details` - Query cues with filtering and sorting
• `delete_cue_list` - Delete entire cue lists (requires confirmation)

Cue Playback Control

• `start_cue_list` - Begin playing a cue list from any point
• `next_cue` - Advance to the next cue
• `previous_cue` - Go back to the previous cue
• `go_to_cue` - Jump to a specific cue by number or name
• `stop_cue_list` - Stop the currently playing cue list
• `get_cue_list_status` - Get playback status and navigation options

Look Board Management

Look Boards provide a visual layout system for organizing and triggering looks with customizable button positions on a 2D canvas (default 2000x2000 pixels).

Look Board CRUD

• `list_look_boards` - List all look boards in a project with button counts
• `get_look_board` - Get a specific look board with all buttons and layout
• `create_look_board` - Create a new look board with custom canvas and grid settings
• `update_look_board` - Update look board metadata and settings
• `delete_look_board` - Delete a look board and all its buttons (requires confirmation)
• `bulk_create_look_boards` - Create multiple look boards in a single operation
• `bulk_update_look_boards` - Update multiple look boards in a single operation
• `bulk_delete_look_boards` - Delete multiple look boards in a single operation

Look Board Button Management

• `add_look_to_board` - Add a look as a button at a specific canvas position
• `update_look_board_button` - Update button properties (position, size, color, label)
• `remove_look_from_board` - Remove a button from a look board
• `update_look_board_button_positions` - Batch update button positions (drag-and-drop)
• `bulk_create_look_board_buttons` - Create multiple buttons in a single operation
• `bulk_update_look_board_buttons` - Update multiple buttons in a single operation
• `bulk_delete_look_board_buttons` - Delete multiple buttons in a single operation

Look Board Playback

• `activate_look_from_board` - Activate a look from a board (uses board's default fade time)
• `create_look_board_with_buttons` - Create a complete look board with buttons in one command

Installation

1. Install dependencies:

npm install

2. Set up environment variables:

cp .env.example .env
# Edit .env with your configuration

3. Build the project:

npm run build

Configuration

Required Environment Variables

• `OPENAI_API_KEY` - OpenAI API key for AI-powered lighting generation
• `LACYLIGHTS_GRAPHQL_ENDPOINT` - GraphQL endpoint for your lacylights-go backend (default: http://localhost:4000/graphql)

Optional Environment Variables

• `CHROMA_HOST` - ChromaDB host for enhanced RAG functionality (default: localhost)
• `CHROMA_PORT` - ChromaDB port (default: 8000)

Running the Server

Make sure your `lacylights-go` backend is running first, then:

# Start in development mode (with auto-reload)
npm run dev

# Or build and run in production mode
npm run build
npm start

You should see:

RAG service initialized with in-memory patterns
LacyLights MCP Server running on stdio

Integration with Claude

Add this server to your Claude configuration:

{
  "mcpServers": {
    "lacylights": {
      "command": "/usr/local/bin/node",
      "args": ["/path/to/lacylights-mcp/run-mcp.js"],
      "env": {
        "OPENAI_API_KEY": "your_openai_api_key_here",
        "LACYLIGHTS_GRAPHQL_ENDPOINT": "http://localhost:4000/graphql"
      }
    }
  }
}

Important:

• Use the absolute path to `run-mcp.js` in your configuration
• If the above doesn't work, find your Node.js path with: `which node`
• The wrapper script ensures proper CommonJS module loading

Releases & Versioning

Release Channels

LacyLights MCP supports two release channels:

1. Stable Releases (e.g., `1.4.0`, `1.5.0`)

2. Beta Releases (e.g., `1.4.1b1`, `1.5.0b2`)

Version Format

• Stable: `X.Y.Z` (semantic versioning)
  • `X` = Major version (breaking changes)
  • `Y` = Minor version (new features)
  • `Z` = Patch version (bug fixes)

• Beta: `X.Y.Zb[N]` (beta with iteration)
  • `b` = Beta identifier
  • `[N]` = Beta iteration number (1, 2, 3, ...)

Installing Specific Versions

Install Latest Stable (Recommended)

# Download latest stable release
curl -s https://dist.lacylights.com/releases/mcp/latest.json | jq -r '.url' | xargs curl -LO

# Extract archive
tar -xzf lacylights-mcp-*.tar.gz
cd lacylights-mcp

# Install and run
npm ci --omit=dev
npm start

Install Specific Version

# Download specific version (replace X.Y.Z with actual version)
VERSION="1.4.0"  # or "1.4.1b1" for beta
curl -LO https://dist.lacylights.com/releases/mcp/lacylights-mcp-${VERSION}.tar.gz

# Verify SHA256 checksum (optional but recommended)
curl -s https://dist.lacylights.com/releases/mcp/latest.json | jq -r '.sha256'
sha256sum lacylights-mcp-${VERSION}.tar.gz

# Extract and run
tar -xzf lacylights-mcp-${VERSION}.tar.gz
cd lacylights-mcp
npm ci --omit=dev
npm start

Install Beta for Testing

# Download latest beta (check GitHub releases for version)
VERSION="1.5.0b2"
curl -LO https://dist.lacylights.com/releases/mcp/lacylights-mcp-${VERSION}.tar.gz

# Extract and test
tar -xzf lacylights-mcp-${VERSION}.tar.gz
cd lacylights-mcp
npm ci --omit=dev
npm start

Release Distribution

All releases are distributed through multiple channels:

1. GitHub Releases: https://github.com/bbernstein/lacylights-mcp/releases

2. S3 Distribution: https://dist.lacylights.com/releases/mcp/

3. DynamoDB Registry:

Beta Testing Program

Want to help test new features? Install beta releases:

1. Check for betas: Visit GitHub Releases

2. Install beta:

# See "Install Beta for Testing" above

3. Report issues:

Release Process

For maintainers: See RELEASE_PROCESS.md for complete release documentation including:

• Beta release workflows
• Stable release procedures
• Version management
• Distribution verification
• Troubleshooting and rollback

Complete Example: Lighting Design for Macbeth

Here's a comprehensive example showing how a lighting designer would use LacyLights MCP to create a complete lighting design for Shakespeare's Macbeth:

Step 1: Create the Project

Use create_project to create a new project called "Macbeth - Main Stage 2024"
with description "Shakespeare's Macbeth, directed by Jane Smith, March 2024 production"

Step 2: Set Up Fixtures

Use create_fixture_instance to add these fixtures to the project:
- 12x Chauvet SlimPAR Pro RGBA fixtures for front wash (channels 1-48)
- 8x Martin MAC Quantum Profile moving heads for specials (channels 100-163)
- 6x ETC Source Four LED Series 2 for side lighting (channels 200-241)
- 4x Chauvet Strike 4 strobes for storm effects (channels 300-315)
- 2x Rosco Vapour Plus hazers for atmosphere (channels 400-403)

Step 3: Analyze the Script

Use analyze_script with the full text of Act 1 to extract:
- All lighting cues mentioned in stage directions
- Scene transitions that need lighting changes
- Mood and atmosphere requirements for each scene

Step 4: Generate Key Looks

Use generate_look to create these essential looks:

1. "Opening - Thunder and Lightning"
   - Script context: "Thunder and lightning. Enter three witches."
   - Mood: ominous, supernatural
   - Color palette: ["deep purple", "electric blue", "white strobe"]
   - Intensity: dramatic

2. "Duncan's Arrival at Inverness"
   - Script context: "Hautboys and torches. Enter Duncan, Malcolm, Donalbain, Banquo"
   - Mood: regal, warm
   - Color palette: ["warm amber", "gold", "soft orange"]
   - Intensity: moderate

3. "Lady Macbeth Reads the Letter"
   - Script context: "Enter Lady Macbeth, reading a letter"
   - Mood: intimate, plotting
   - Color palette: ["cool blue", "pale amber", "shadow"]
   - Focus areas: ["center stage", "downstage center"]

4. "The Dagger Soliloquy"
   - Script context: "Is this a dagger which I see before me"
   - Mood: hallucinatory, tense
   - Color palette: ["blood red", "deep shadow", "cold steel blue"]
   - Intensity: subtle
   - Focus areas: ["center stage spot"]

5. "Murder of Duncan"
   - Script context: "Macbeth exits to kill Duncan, bell rings"
   - Mood: dark, suspenseful
   - Color palette: ["deep red", "black", "moonlight blue"]
   - Intensity: dramatic

6. "Banquo's Ghost Appears"
   - Script context: "The Ghost of Banquo enters, and sits in Macbeth's place"
   - Mood: supernatural, terrifying
   - Color palette: ["ghostly green", "cold white", "shadow"]
   - Effects: use moving heads for ghost tracking

7. "Lady Macbeth's Sleepwalking"
   - Script context: "Enter Lady Macbeth with a taper"
   - Mood: haunted, guilty
   - Color palette: ["candlelight amber", "moonlight", "deep shadow"]
   - Focus areas: ["follow spot", "single candle effect"]

8. "Final Battle"
   - Script context: "Alarums. Enter Macbeth and Macduff fighting"
   - Mood: violent, chaotic
   - Color palette: ["fire red", "steel blue", "explosive white"]
   - Intensity: dramatic
   - Effects: strobe for sword clashes

Step 5: Create Cue Sequences

Use create_cue_sequence to build the Act 1 cue list:
- Name: "Act 1 - Complete"
- Include all Act 1 looks in order
- Set default fade times: 3 seconds in, 3 seconds out
- Add follow cues for quick transitions during soliloquies

Step 6: Generate Act Cues with Script Analysis

Use generate_act_cues with the complete text of Act 2:
- This will analyze the script and create a complete cue list
- Automatically times transitions based on dramatic pacing
- Suggests lighting changes for every entrance, exit, and mood shift

Step 7: Optimize for Performance

Use optimize_cue_timing on the Act 1 cue list:
- Strategy: "dramatic_timing"
- This will adjust fade times for maximum dramatic impact
- Smooth transitions for scene changes
- Sharp cuts for supernatural appearances

Step 8: Create Special Effect Sequences

Use create_cue_sequence for the storm effect:
1. Lightning Strike 1 (strobes at full, 0.1s)
2. Thunder Roll (deep blue wash, 2s fade)
3. Lightning Strike 2 (strobes at 75%, 0.15s)
4. Return to storm base (purple/blue, 3s fade)
- Set follow times for automatic progression

Step 9: Run the Show

During performance, the stage manager can use:

start_cue_list "Act 1 - Complete"
next_cue  # Advance through each cue
go_to_cue 15.5  # Jump to specific cue for pickups
fade_to_black 5  # Emergency blackout with 5-second fade

Step 10: Make Live Adjustments

Use update_look to adjust the "Banquo's Ghost" look:
- Increase moving head intensity for better visibility
- Adjust color temperature based on costume reflectance
- Fine-tune positioning for actor's blocking changes

Advanced Usage Examples

Script-Driven Design Workflow

1. Analyze the entire script:
   analyze_script with full play text

2. Review extracted cues and looks

3. Generate all suggested looks in batch:
   generate_look for each suggestion

4. Create master cue list:
   create_cue_sequence with all looks

5. Optimize for your venue:
   optimize_look for each look with "technical_simplicity"

Multi-Universe Setup

For large productions spanning multiple DMX universes:

1. Plan channel allocation:
   suggest_channel_assignment for all fixtures

2. Create fixtures with specific universe assignments:
   create_fixture_instance with universe: 1 for front lights
   create_fixture_instance with universe: 2 for moving heads
   create_fixture_instance with universe: 3 for effects

3. View the complete channel map:
   get_channel_map for the project

Collaborative Design Process

Director requests:
"I want the witches' scenes to feel otherworldly but not cartoonish"

Use generate_look:
- Description: "Witches on the heath"
- Mood: "otherworldly, mysterious"
- Color palette: ["deep violet", "fog grey", "pale green"]
- Intensity: "subtle"

Then iterate with optimize_look using "dramatic_impact" until satisfied

AI-Powered Features

Intelligent Script Analysis

• Extracts explicit lighting cues from stage directions
• Identifies implicit lighting needs from dialogue and action
• Suggests atmospheric lighting based on dramatic context
• Recognizes standard theatrical conventions (sunrise, sunset, storms)

Context-Aware Look Generation

• Understands theatrical lighting principles
• Applies color theory for emotional impact
• Considers fixture capabilities and positions
• Generates DMX values that respect real-world constraints

Adaptive Optimization

• Energy Efficiency: Reduces power consumption while maintaining artistic intent
• Dramatic Impact: Enhances contrast and focus for maximum effect
• Technical Simplicity: Simplifies programming for easier operation
• Color Accuracy: Optimizes for true color rendering

Troubleshooting

Common Issues

1. Module import errors

2. GraphQL connection errors

3. OpenAI API errors

4. MCP connection errors in Claude

5. "Unexpected token ?" error

ChromaDB Setup (Optional - For Enhanced RAG)

The MCP server works out of the box with in-memory pattern storage. For persistent vector storage and more sophisticated pattern matching:

Option 1: Docker (Recommended)

# Start ChromaDB with Docker
docker-compose up -d chromadb

# Verify it's running
curl http://localhost:8000/api/v2/heartbeat

Option 2: Local Installation

# Install ChromaDB
pip install chromadb

# Start the server
chroma run --host localhost --port 8000

Then update your `.env` file:

# Uncomment these lines in .env
CHROMA_HOST=localhost
CHROMA_PORT=8000

Integration with LacyLights Ecosystem

This MCP server is part of the complete LacyLights system:

• lacylights-go - Backend GraphQL API for fixture and look management
• lacylights-fe - Web frontend for manual control and visualization
• lacylights-mcp - AI interface for intelligent automation

The MCP server enhances the existing system with:

• Natural language control
• Intelligent look generation
• Script analysis capabilities
• Automated cue creation
• Performance optimization

Development

Project Structure

src/
├── tools/           # MCP tool implementations
│   ├── fixture-tools.ts    # Fixture management operations
│   ├── look-tools.ts       # Look creation and control
│   ├── cue-tools.ts        # Cue list management
│   └── project-tools.ts    # Project operations
├── services/        # Core services
│   ├── graphql-client.ts   # GraphQL API client
│   ├── rag-service.ts      # RAG pattern matching
│   └── ai-lighting.ts      # AI look generation
├── types/          # TypeScript type definitions
│   └── lighting.ts         # Core lighting types
└── index.ts        # MCP server entry point

Adding New Tools

1. Create tool implementation in appropriate file under `src/tools/`

2. Add tool definition to `src/index.ts` in the `ListToolsRequestSchema` handler

3. Add tool handler in the `CallToolRequestSchema` handler

4. Update this README with tool documentation

Testing

npm test

MCP Directory

License

MIT