Avatar Renderer
This project is an AI engine that brings a single photo to life, creating a realistic 'talking head' video from just an audio file. It's built for flexibility, offering two ways to use it: a standard web API for easy integration into any application,
What is Avatar Renderer?
Avatar Renderer is a Model Context Protocol (MCP) server that allows AI assistants like Claude, Cursor, and VS Code to this project is an ai engine that brings a single photo to life, creating a realistic 'talking head' video from just an audio file. it's built for flexibility, offering two ways to use it: a standard ...
This project is an AI engine that brings a single photo to life, creating a realistic 'talking head' video from just an audio file. It's built for flexibility, offering two ways to use it: a standard web API for easy integration into any application,
This server falls under the Browser Automation category on MCPgee, the world's largest MCP server directory with 33,000+ servers.
Features
- This project is an AI engine that brings a single photo to l
Use Cases
Maintainer
Works with
Installation
Manual Installation
npx avatar-rendererConfiguration
Configuration Details
claude_desktop_config.json
Performance
Response Metrics
Resource Usage
How to Set Up and Use Avatar Renderer
The Avatar Renderer MCP Server is an AI-powered talking head video generation engine that animates a single portrait photo using an audio file, producing a synchronized video with lip-sync, eye movement, facial expressions, and body language. It supports 10 enhancement modules including MuseTalk, LivePortrait, LatentSync, and Hallo3 cinematic rendering, as well as CosyVoice TTS for text-to-speech in 23 languages. Developers can integrate it as a web API, run it as a desktop application, or invoke it directly as an MCP tool from AI agents for automated avatar video creation.
Prerequisites
- Python 3.11 or higher installed
- NVIDIA GPU with CUDA 12.4 recommended (an NVIDIA T4 or A10G is ideal); CPU-only execution is supported but significantly slower
- Docker with NVIDIA Container Toolkit for containerized deployment
- Git and make (GNU Make) for running the Makefile-based setup
- An MCP-compatible client such as Claude Desktop, or use the built-in REST API directly
Clone the repository
Download the avatar-renderer-mcp source code from GitHub.
git clone https://github.com/ruslanmv/avatar-renderer-mcp.git
cd avatar-renderer-mcpInstall dependencies via make
Run the unified install target which sets up the Python environment, downloads model weights, and installs all required packages.
make installStart the server in MCP stdio mode
Launch the server in stdio transport mode for use with MCP clients like Claude Desktop. For a standalone REST API, use 'make run' instead.
# MCP stdio mode for AI agent integration:
make run-stdio
# REST API mode (port 8080):
make run
# Desktop application UI:
make launchConfigure Claude Desktop
Add the avatar renderer to your Claude Desktop configuration using the stdio transport command.
{
"mcpServers": {
"avatar-renderer": {
"command": "make",
"args": ["run-stdio"],
"cwd": "/path/to/avatar-renderer-mcp"
}
}
}Test via the REST API
Verify the server is running by sending a test render request with a portrait photo and audio file.
curl -X POST http://localhost:8080/render \
-H 'Content-Type: application/json' \
-d '{"avatarPath": "photo.png", "audioPath": "speech.wav"}'Avatar Renderer Examples
Client configuration
Claude Desktop configuration for the Avatar Renderer MCP server using stdio mode.
{
"mcpServers": {
"avatar-renderer": {
"command": "make",
"args": ["run-stdio"],
"cwd": "/Users/yourname/avatar-renderer-mcp"
}
}
}Prompts to try
Example prompts for generating avatar videos and using the REST API.
- "Generate a talking head video using the photo at /tmp/portrait.jpg and the audio file at /tmp/speech.wav."
- "Create a high-quality avatar video — I'm OK waiting 10-30 seconds for better results."
- "Use the real-time mode to generate a quick preview avatar video from my photo and audio."
- "Generate speech audio in French from this text and animate my avatar photo with it."Troubleshooting Avatar Renderer
CUDA out of memory error during video generation
Switch to real-time mode instead of high-quality mode, which uses fewer GPU resources. Reduce the input image resolution to 512x512 or less, or use Docker with GPU memory limits: 'docker run --gpus all --shm-size=8g avatar-renderer:latest'.
Model weights not found after 'make install'
The install target downloads several GB of model files. Re-run 'make install' and ensure you have a stable internet connection and sufficient disk space (at least 10GB free). Check for any download errors in the install output.
Audio and video are out of sync in the output
Ensure the input audio file is a clean WAV file sampled at 16kHz or 44.1kHz. MP3 files may need conversion: 'ffmpeg -i input.mp3 -ar 16000 output.wav'. High-quality mode generally produces better sync than real-time mode.
Frequently Asked Questions about Avatar Renderer
What is Avatar Renderer?
Avatar Renderer is a Model Context Protocol (MCP) server that this project is an ai engine that brings a single photo to life, creating a realistic 'talking head' video from just an audio file. it's built for flexibility, offering two ways to use it: a standard web api for easy integration into any application, It connects AI assistants to external tools and data sources through a standardized interface.
How do I install Avatar Renderer?
Follow the installation instructions on the Avatar Renderer GitHub repository. Clone the repo, install dependencies, and add the server config to your AI client.
Which AI clients work with Avatar Renderer?
Avatar Renderer works with all major MCP-compatible AI clients including Claude Desktop, Claude Code, Cursor, VS Code (GitHub Copilot), Windsurf, and Cline.
Is Avatar Renderer free to use?
Yes, Avatar Renderer is open source and available under the NOASSERTION license. You can use it freely in both personal and commercial projects.
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Set Up Avatar Renderer in Your Editor
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Quick Config Preview
Add this to your claude_desktop_config.json or .cursor/mcp.json
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