MCP Unity by Codergamester is a server plugin designed to link the Unity Editor with AI assistants and Large Language Model tools. This free tool transforms Unity Editor functionalities into an accessible protocol, enabling AI clients to directly interact with and manipulate game development environments. It operates by running a WebSocket server within Unity, allowing external AI clients like Cursor and GitHub Copilot to control various aspects of a Unity project. MCP Unity enhances productivity for developers by automating tasks, debugging, and accelerating content creation through AI-driven commands.

What does MCP Unity connect to?

MCP Unity establishes a connection between the Unity Editor environment and various AI assistants and Large Language Model tools. It functions as a Model Context Protocol server plugin, allowing these AI systems to understand and utilize Unity's functionalities. The server component runs as a WebSocket server directly within Unity, while a Node.js server acts as its WebSocket client, implementing the MCP protocol. This bridge enables AI to interact with the Unity Editor for development tasks.

Core features and tools

MCP Unity exposes Unity Editor functionalities as "tools" and "resources" for AI use. It supports categories of operations including creating objects, modifying components, running tests, and managing projects. Specific actions include creating GameObjects, adding and configuring components like Rigidbody and CharacterController, fixing failing physics tests, installing Unity packages such as TextMeshPro, and creating or configuring UI elements. This allows AI to perform concrete development tasks within Unity.

Who is it for?

MCP Unity is for Unity developers who employ AI coding assistants and LLMs, such as Cursor, Claude Code, GitHub Copilot, and Augment Code, and desire direct AI interaction and control over the Unity Editor for game development. Its purpose is to automate tasks and accelerate workflows through AI commands. Skip this if you do not use AI coding assistants or LLMs for direct interaction with your Unity Editor environment.

How to get started

The server authenticates using an API key passed as an environment variable, configured in Unity's Project Settings, or stored in a Resources/MCPSettings.asset. The communication uses the WebSocket protocol.

Use cases

• Automating scene setup and object creation: An AI assistant can create GameObjects, add and configure components, and place them in the scene based on natural language commands.
• Debugging and testing: AI can analyze failing tests, identify problematic GameObjects or configurations, modify them, and re-run tests to verify fixes.
• UI/UX element creation and package management: AI can install Unity packages, create UI elements with proper setup, and configure their styling and positioning.

MCP Unity offers a direct pathway for AI assistants to control the Unity Editor, automating various development processes. It supports several AI clients and provides methods for securing external LLM API keys. This tool bridges the gap between AI capabilities and game development tasks, enabling more efficient scene setup, debugging, and UI creation. Try enabling an AI assistant to create a simple GameObject with a Rigidbody component in a new Unity scene.