What is Lightfast Mcp

Lightfast MCP is a Model Context Protocol designed for creative applications, allowing AI models to interact with tools like Blender, TouchDesigner, Ableton, Adobe Creative Suite, and Unreal Engine. It provides a structured way for AI to assist in creation, manipulation, and automation.

Use cases

Use cases for Lightfast MCP include automating repetitive tasks in Blender, generating music in Ableton, creating interactive installations with TouchDesigner, and enhancing design workflows in Adobe Creative Suite.

How to use

To use Lightfast MCP, install Python 3.12 or newer and the uv package manager. Follow the installation instructions specific to your operating system. Once installed, refer to the documentation for examples and tutorials to get started with implementing MCPs in your creative applications.

Key features

Key features of Lightfast MCP include strict adherence to the Model Context Protocol specification, compatibility with various creative applications, comprehensive documentation, and tools for developers to create their own MCPs.

Where to use

Lightfast MCP can be used in various fields such as digital art, music production, game development, and any creative domain where AI can enhance the workflow and creativity of artists and developers.

lightfast-mcp - MCP Server Implementations for Creative Applications

Production-ready MCP server implementations for creative applications - Control Blender and other creative tools through the Model Context Protocol.

Lightfast MCP provides reliable, well-tested MCP server implementations for creative applications, with optional management and AI client tools.

🎯 Core MCP Servers

• 🎨 Blender MCP Server: Control Blender through MCP protocol for 3D modeling, animation, and rendering
• 🧪 Mock MCP Server: Testing and development server for MCP protocol validation

🔧 Optional Features

• Multi-Server Orchestration: Run and coordinate multiple MCP servers simultaneously
• AI Integration: Built-in AI tools for testing and interacting with servers
• Configuration-Driven: YAML/JSON configuration for easy server management
• Flexible Transport: Support for both stdio and HTTP-based transports

Protocol Compliance

Lightfast MCP strictly adheres to the official Model Context Protocol specification. This ensures compatibility with all MCP clients and provides a standardized way for AI models to interact with creative applications.

For more information about the Model Context Protocol, including core concepts, resources, prompts, tools, and sampling, please refer to the official MCP documentation.

Installation

• Python 3.10 or newer
• uv package manager

If you’re on Mac, please install uv as

brew install uv

On Windows

powershell -c "irm https://astral.sh/uv/install.ps1 | iex" 

and then

set Path=C:\Users\nntra\.local\bin;%Path%

Otherwise installation instructions are on their website: Install uv

Development

For development setup, workflow information, and Cursor IDE integration, please see our Developer Guide.

Documentation

For comprehensive documentation, examples, and guides, please visit our documentation site.

Contributing

We welcome contributions from the community! Whether you want to add support for a new creative application, improve existing implementations, or enhance documentation, please feel free to submit a pull request.

See our Contributing Guide for more information on how to get started.

License

This project is licensed under the MIT License. See the LICENSE file for details.

Disclaimer

This is a community-driven project. The integrations provided are third-party and not officially made or endorsed by the respective software vendors.

Quick Start

🎯 Core Usage (MCP Servers Only)

# Install core package
pip install lightfast-mcp

# Run individual servers
lightfast-blender-server    # Blender MCP server
lightfast-mock-server       # Mock MCP server for testing

🔧 Development Tools (Orchestration + AI)

# Install with development tools
pip install lightfast-mcp[tools]

# Multi-server orchestration
lightfast-mcp-orchestrator init
lightfast-mcp-orchestrator start

# AI integration for testing
lightfast-mcp-ai chat

🧪 Development

# Development setup
uv pip install -e ".[dev]"
nox  # Run tests

For comprehensive development documentation, testing guide, and architecture details, see DEV.md.