lightfast-mcp

# 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](https://modelcontextprotocol.io/introduction). 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](https://modelcontextprotocol.io/introduction). ## Installation - Python 3.10 or newer - uv package manager **If you're on Mac, please install uv as** ```bash brew install uv ``` **On Windows** ```bash powershell -c "irm https://astral.sh/uv/install.ps1 | iex" ``` and then ```bash set Path=C:\Users\nntra\.local\bin;%Path% ``` Otherwise installation instructions are on their website: [Install uv](https://docs.astral.sh/uv/getting-started/installation/) ## Development For development setup, workflow information, and Cursor IDE integration, please see our [Developer Guide](DEV.md). ## Documentation For comprehensive documentation, examples, and guides, please visit our [documentation site](https://yourprojecturl.com/docs). ## 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](CONTRIBUTING.md) for more information on how to get started. ## License This project is licensed under the MIT License. See the [LICENSE](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) ```bash # 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) ```bash # 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 ```bash # Development setup uv pip install -e ".[dev]" nox # Run tests ``` For comprehensive development documentation, testing guide, and architecture details, see [DEV.md](DEV.md).