intentional-masking
Renders Ready Player Me avatars with phoneme-based lip-sync from audio using Remotion and React Three Fiber.
README
intentional-masking
MCP server for rendering Ready Player Me avatars with lip-sync using Remotion and React Three Fiber.
Features
- render_frame - Render a single still image of an avatar with expression, pose, camera, and lighting options
- render_speaking_video - Render a video of an avatar speaking with real phoneme-based lip-sync from audio
Requirements
- Node.js 18+
- macOS, Linux, or Windows
Installation
cd intentional-masking
npm install
npm run build
Usage
As MCP Server
Add to your Claude Code configuration (~/.claude.json or project .claude/settings.local.json):
{
"mcpServers": {
"intentional-masking": {
"command": "node",
"args": ["/path/to/intentional-masking/dist/server/index.js"],
"env": {
"INTENTIONAL_MASKING_ROOT": "/path/to/intentional-masking"
}
}
}
}
MCP Tools
render_frame
Render a single still frame of an avatar.
{
"avatar_path": "/path/to/avatar.glb",
"expression": "happy",
"pose": "greeting",
"camera_preset": "closeup",
"lighting_preset": "soft",
"background": "#1a1a2e"
}
Options:
expression:neutral|happy|thinking|surprisedpose:default|greeting|listeningcamera_preset:closeup|medium|fulllighting_preset:soft|dramatic|naturalbackground: Hex color (default:#1a1a2e)
Returns: { "success": true, "image_path": "/path/to/output.png" }
render_speaking_video
Render an avatar speaking with lip-sync from audio.
{
"avatar_path": "/path/to/avatar.glb",
"audio_path": "/path/to/speech.wav",
"camera_preset": "closeup",
"lighting_preset": "soft",
"background": "#1a1a2e"
}
Audio requirements:
- 16kHz 16-bit mono PCM WAV (as produced by info-dump)
Returns: { "success": true, "video_path": "/path/to/output.mp4", "duration_seconds": 5.2 }
Architecture
src/
├── server/
│ ├── index.ts # MCP server entry point
│ ├── services/
│ │ └── lip-sync.ts # Rhubarb lip-sync integration
│ └── tools/
│ ├── render-frame.ts # Still image rendering
│ └── render-speaking-video.ts # Video rendering
├── config/
│ └── viseme-map.ts # Rhubarb → RPM morph target mapping
└── remotion/
├── index.ts # Remotion entry point
├── Root.tsx # Composition registration
├── AvatarFrame.tsx # Still frame composition
├── AvatarSpeaking.tsx # Speaking video composition
└── components/
├── Avatar.tsx # GLB model loader
├── Scene.tsx # Three.js scene setup
└── LipSyncController.tsx # Morph target application
Lip-Sync Pipeline
- Audio analysis: rhubarb-lip-sync-wasm analyzes 16kHz audio
- Phoneme mapping: Rhubarb shapes (A-H, X) → Ready Player Me viseme morph targets
- Frame interpolation: Smooth blending between viseme shapes
- Video rendering: Remotion captures Three.js scene frame-by-frame
Rhubarb Shape Mapping
| Shape | Phonemes | RPM Morph Targets |
|---|---|---|
| A | P, B, M (closed) | viseme_PP |
| B | K, S, T (teeth) | viseme_kk, viseme_nn |
| C | EH, AE (vowels) | viseme_I, viseme_E |
| D | AA (wide open) | viseme_aa |
| E | AO, ER (rounded) | viseme_O, viseme_aa |
| F | UW, OW, W (puckered) | viseme_U |
| G | F, V (teeth-on-lip) | viseme_FF |
| H | L sound | viseme_TH, viseme_nn |
| X | Silence | viseme_sil |
Integration with info-dump
This server pairs with info-dump for complete TTS → avatar rendering:
info-dump generate_audio("Hello!", voice, output_path)
↓
intentional-masking render_speaking_video(avatar_path, audio_path)
↓
MP4 video with lip-synced avatar
Avatar Requirements
Avatars must be Ready Player Me GLB files with standard viseme morph targets:
viseme_aa,viseme_E,viseme_I,viseme_O,viseme_Uviseme_PP,viseme_FF,viseme_TH,viseme_DD,viseme_kk,viseme_nn,viseme_sil
Create avatars at readyplayer.me
Development
# Run tests
npm test
# Watch mode
npm run dev
# Preview Remotion compositions
npm run remotion:preview
Environment Variables
INTENTIONAL_MASKING_ROOT- Project root directory (default: cwd)INTENTIONAL_MASKING_OUTPUT- Output directory for rendered files (default:{root}/output)
License
MIT
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.