Overview
Unlock the power of AI within your Unity Editor with MCP for Unity (Model Context Protocol). This groundbreaking tool acts as a seamless bridge, enabling Large Language Models (LLMs) like Claude, Codex, and even local models, to interact with and control your Unity projects. Imagine describing complex scene modifications, asset management tasks, or script edits in natural language and seeing them executed instantly. MCP for Unity empowers your AI assistants with a comprehensive toolkit for asset manipulation, scene control, script editing, automated testing, and much more, revolutionizing your game development workflow.
Key Features
- Natural Language Control: Interact with your Unity Editor using plain English prompts, powered by your favorite LLM.
- Extensive Toolset: Leverage over 47 specialized MCP tool entrypoints for creating scenes and GameObjects, editing C# scripts, managing project assets, running tests, profiling performance, and generating builds.
- Broad LLM Compatibility: Works seamlessly with a wide range of MCP clients, including Claude Desktop & Code, Cursor, VS Code, Windsurf, Cline, Gemini CLI, and other LLM interfaces.
- Protocol-Driven: Built upon the open Model Context Protocol, ensuring robust and standardized communication between AI and Unity.
- Flexible Installation: Easily integrate via Unity's Package Manager from a Git URL or through OpenUPM.
- Open Source & Free: Developed under the permissive MIT license, making it accessible for all developers.
- Extensible: Supports advanced features like multi-instance routing, custom tool groups, and remote server authentication.
Typical Use Cases
- Rapid Prototyping: Quickly generate game environments, place objects, and set up basic game logic using simple text commands.
- Automated Asset Management: Instruct your AI to import, organize, or modify assets within your project.
- Intelligent Scripting: Have your LLM generate, debug, or refactor C# scripts directly within Unity.
- Workflow Automation: Automate repetitive tasks such as setting up prefabs, applying components, or running build pipelines.
- Interactive Debugging: Use AI to analyze game state, run tests, and identify issues through natural language queries.
- Creative Exploration: Experiment with different scene designs and gameplay mechanics by describing your vision to the AI.
