Mcp Unity

Mcp Unity Overview

What is Mcp Unity about?

Mcp Unity provides a bridge between the Unity Editor and AI coding assistants (Claude, Cursor, Windsurf, OpenAI, Gemini, etc.). It runs a WebSocket server inside Unity and a Node.js client that implements the Model Context Protocol, allowing AI agents to execute menu items, manipulate GameObjects, manage packages, run tests, and retrieve editor information through natural‑language prompts.

How to use Mcp Unity?

Install prerequisites – Unity 2022.3+ and Node.js 18+.
Add the package – In Unity Package Manager, add the Git URL https://github.com/CoderGamester/mcp-unity.git.
Configure the AI client – Use the Server Window (Tools > Mcp Unity > Server Window) to generate the configuration JSON or manually add the snippet pointing to Server~/build/index.js.
Start the server – Click Start Server in the same window; the WebSocket server listens on port 8090 (configurable).
Issue prompts – In a supported AI IDE, ask commands such as “Create an empty GameObject named Player and add a Rigidbody with mass 5”. The AI will invoke the corresponding MCP tool, and Unity will execute it.

Key Features

IDE integration – Automatically adds Library/PackedCache to VS Code‑like workspaces for better code intelligence.
MCP tools – execute_menu_item, select_gameobject, update_gameobject, update_component, add_package, run_tests, send_console_log, add_asset_to_scene, create_prefab.
MCP resources – Retrieve menus, scene hierarchy, GameObject details, console logs, package list, assets, and test information via unity:// URIs.
Customizable port & timeout – Adjustable WebSocket port and request timeout from the Server Window.
Remote connections – Option to bind to 0.0.0.0 for external machine access.
Extensible – Developers can add project‑specific tools by extending the C# base classes and registering them in the server.

Use Cases

Rapid prototyping – Create and configure objects, add components, and set up scenes via simple text prompts.
Automated testing – Trigger EditMode or PlayMode test runs from an AI assistant.
Asset management – Install packages, add prefabs, or query assets without leaving the editor.
Team onboarding – New developers can ask the AI to explore the project hierarchy, view component settings, or fix console errors.
CI/CD assistance – Scripts can invoke MCP tools to prepare builds, adjust settings, or verify project health.

FAQ

Why can’t I connect? Ensure the WebSocket server is running, the project path contains no spaces, and the correct port is configured.
What if the server won’t start? Verify Node.js is in your PATH, install dependencies in Server~ (npm install), and check Unity console for errors.
Play Mode disables the bridge? Disable Reload Domain in Unity’s Enter Play Mode Settings to keep the connection alive.
Running on WSL2? Use Windows 11 mirrored networking or set UNITY_HOST to the Windows host IP; optionally enable remote connections in Unity.
Can I add custom tools? Yes—create new C# classes inheriting from the MCP base classes, register them, and implement matching handlers in the Node.js server.

Mcp Unity's README

MCP Unity Editor (Game Engine)

🇺🇸English	🇨🇳简体中文	🇯🇵日本語

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MCP Unity is an implementation of the Model Context Protocol for Unity Editor, allowing AI assistants to interact with your Unity projects. This package provides a bridge between Unity and a Node.js server that implements the MCP protocol, enabling AI agents like Claude, Windsurf, and Cursor to execute operations within the Unity Editor.

Features

IDE Integration - Package Cache Access

MCP Unity provides automatic integration with VSCode-like IDEs (Visual Studio Code, Cursor, Windsurf) by adding the Unity Library/PackedCache folder to your workspace. This feature:

Improves code intelligence for Unity packages
Enables better autocompletion and type information for Unity packages
Helps AI coding assistants understand your project's dependencies

MCP Server Tools

The following tools are available for manipulating and querying Unity scenes and GameObjects via MCP:

execute_menu_item: Executes Unity menu items (functions tagged with the MenuItem attribute)

Example prompt: "Execute the menu item 'GameObject/Create Empty' to create a new empty GameObject"
select_gameobject: Selects game objects in the Unity hierarchy by path or instance ID

Example prompt: "Select the Main Camera object in my scene"
update_gameobject: Updates a GameObject's core properties (name, tag, layer, active/static state), or creates the GameObject if it does not exist

Example prompt: "Set the Player object's tag to 'Enemy' and make it inactive"
update_component: Updates component fields on a GameObject or adds it to the GameObject if it does not contain the component

Example prompt: "Add a Rigidbody component to the Player object and set its mass to 5"
add_package: Installs new packages in the Unity Package Manager

Example prompt: "Add the TextMeshPro package to my project"
run_tests: Runs tests using the Unity Test Runner

Example prompt: "Run all the EditMode tests in my project"
send_console_log: Send a console log to Unity

Example prompt: "Send a console log to Unity Editor"
add_asset_to_scene: Adds an asset from the AssetDatabase to the Unity scene

Example prompt: "Add the Player prefab from my project to the current scene"
create_prefab: Creates a prefab with optional MonoBehaviour script and serialized field values

Example prompt: "Create a prefab named 'Player' from the 'PlayerController' script"

MCP Server Resources

unity://menu-items: Retrieves a list of all available menu items in the Unity Editor to facilitate execute_menu_item tool

Example prompt: "Show me all available menu items related to GameObject creation"
unity://scenes-hierarchy: Retrieves a list of all game objects in the current Unity scene hierarchy

Example prompt: "Show me the current scenes hierarchy structure"
unity://gameobject/{id}: Retrieves detailed information about a specific GameObject by instance ID or object path in the scene hierarchy, including all GameObject components with it's serialized properties and fields

Example prompt: "Get me detailed information about the Player GameObject"
unity://logs: Retrieves a list of all logs from the Unity console

Example prompt: "Show me the recent error messages from the Unity console"
unity://packages: Retrieves information about installed and available packages from the Unity Package Manager

Example prompt: "List all the packages currently installed in my Unity project"
unity://assets: Retrieves information about assets in the Unity Asset Database

Example prompt: "Find all texture assets in my project"
unity://tests/{testMode}: Retrieves information about tests in the Unity Test Runner

Example prompt: "List all available tests in my Unity project"

Requirements

Unity 2022.3 or later - to install the server
Node.js 18 or later - to start the server
npm 9 or later - to debug the server

[!IMPORTANT] Project Path Cannot Contain Spaces

It is crucial that the file path to your Unity project does not contain any spaces. If your project path includes spaces, the MCP Client (e.g., Cursor, Claude, Windsurf) will fail to connect to the MCP Unity server.

Examples:

✅ Works: C:\Users\YourUser\Documents\UnityProjects\MyAwesomeGame

❌ Fails: C:\Users\Your User\Documents\Unity Projects\My Awesome Game

Please ensure your project is located in a path without spaces before proceeding with the installation.

Installation

Installing this MCP Unity Server is a multi-step process:

Step 1: Install Node.js

To run MCP Unity server, you'll need to have Node.js 18 or later installed on your computer:

node

Visit the Node.js download page
Download the Windows Installer (.msi) for the LTS version (recommended)
Run the installer and follow the installation wizard
Verify the installation by opening PowerShell and running:
```
node --version
```

Visit the Node.js download page
Download the macOS Installer (.pkg) for the LTS version (recommended)
Run the installer and follow the installation wizard
Alternatively, if you have Homebrew installed, you can run:
```
brew install node@18
```
Verify the installation by opening Terminal and running:
```
node --version
```

Step 2: Install Unity MCP Server package via Unity Package Manager

Open the Unity Package Manager (Window > Package Manager)
Click the "+" button in the top-left corner
Select "Add package from git URL..."
Enter: https://github.com/CoderGamester/mcp-unity.git
Click "Add"

package manager

Step 3: Configure AI LLM Client

Open the Unity Editor
Navigate to Tools > MCP Unity > Server Window
Click on the "Configure" button for your AI LLM client as shown in the image below

Confirm the configuration installation with the given popup

Open the MCP configuration file of your AI client (e.g. claude_desktop_config.json in Claude Desktop) and copy the following text:

Replace ABSOLUTE/PATH/TO with the absolute path to your MCP Unity installation or just copy the text from the Unity Editor MCP Server window (Tools > MCP Unity > Server Window).

{
   "mcpServers": {
       "mcp-unity": {
          "command": "node",
          "args": [
             "ABSOLUTE/PATH/TO/mcp-unity/Server~/build/index.js"
          ]
       }
   }
}

Start Unity Editor MCP Server

Open the Unity Editor
Navigate to Tools > MCP Unity > Server Window
Click "Start Server" to start the WebSocket server
Open Claude Desktop or your AI Coding IDE (e.g. Cursor IDE, Windsurf IDE, etc.) and start executing Unity tools

connect

When the AI client connects to the WebSocket server, it will automatically show in the green box in the window

Optional: Set WebSocket Port

By default, the WebSocket server runs on port '8090'. You can change this port in two ways:

Open the Unity Editor
Navigate to Tools > MCP Unity > Server Window
Change the "WebSocket Port" value to your desired port number
Unity will setup the system environment variable UNITY_PORT to the new port number
Restart the Node.js server
Click again on "Start Server" to reconnect the Unity Editor web socket to the Node.js MCP Server

Optional: Set Timeout

By default, the timeout between the MCP server and the WebSocket is 10 seconds. You can change depending on the OS you are using:

Open the Unity Editor
Navigate to Tools > MCP Unity > Server Window
Change the "Request Timeout (seconds)" value to your desired timeout seconds
Unity will setup the system environment variable UNITY_REQUEST_TIMEOUT to the new timeout value
Restart the Node.js server
Click again on "Start Server" to reconnect the Unity Editor web socket to the Node.js MCP Server

[!TIP]
The timeout between your AI Coding IDE (e.g., Claude Desktop, Cursor IDE, Windsurf IDE) and the MCP Server depends on the IDE.

Optional: Allow Remote MCP Bridge Connections

By default, the WebSocket server binds to 'localhost'. To allow MCP bridge connections from other machines:

Open the Unity Editor
Navigate to Tools > MCP Unity > Server Window
Enable the "Allow Remote Connections" checkbox
Unity will bind the WebSocket server to '0.0.0.0' (all interfaces)
Restart the Node.js server to apply the new host configuration
Set the environment variable UNITY_HOST to your Unity machine's IP address when running the MCP bridge remotely: UNITY_HOST=192.168.1.100 node server.js

Debugging the Server

The MCP Unity server is built using Node.js . It requires to compile the TypeScript code to JavaScript in the build directory. In case of issues, you can force install it in by:

Open the Unity Editor
Navigate to Tools > MCP Unity > Server Window
Click on "Force Install Server" button

install

If you want to build it manually, you can follow these steps:

Open a terminal/PowerShell/Command Prompt
Navigate to the Server directory:
```
cd ABSOLUTE/PATH/TO/mcp-unity/Server~
```
Install dependencies:
```
npm install
```
Build the server:
```
npm run build
```
Run the server:
```
node build/index.js
```

Debug the server with @modelcontextprotocol/inspector:

Powershell

npx @modelcontextprotocol/inspector node Server~/build/index.js

Command Prompt/Terminal

npx @modelcontextprotocol/inspector node Server~/build/index.js

Don't forget to shutdown the server with Ctrl + C before closing the terminal or debugging it with the MCP Inspector.

Enable logging on your terminal or into a log.txt file:

Powershell

$env:LOGGING = "true"
$env:LOGGING_FILE = "true"

Command Prompt/Terminal

set LOGGING=true
set LOGGING_FILE=true

Frequently Asked Questions

MCP Unity is a powerful bridge that connects your Unity Editor environment to AI assistants LLM tools using the Model Context Protocol (MCP).

In essence, MCP Unity:

Exposes Unity Editor functionalities (like creating objects, modifying components, running tests, etc.) as "tools" and "resources" that an AI can understand and use.
Runs a WebSocket server inside Unity and a Node.js server (acting as a WebSocket client to Unity) that implements the MCP. This allows AI assistants to send commands to Unity and receive information back.
Enables you to use natural language prompts with your AI assistant to perform complex tasks within your Unity project, significantly speeding up development workflows.

MCP Unity offers several compelling advantages for developers, artists, and project managers:

Accelerated Development: Automate repetitive tasks, generate boilerplate code, and manage assets using AI prompts. This frees up your time to focus on creative and complex problem-solving.
Enhanced Productivity: Interact with Unity Editor features without needing to manually click through menus or write scripts for simple operations. Your AI assistant becomes a direct extension of your capabilities within Unity.
Improved Accessibility: Allows users who are less familiar with the deep intricacies of the Unity Editor or C# scripting to still make meaningful contributions and modifications to a project through AI guidance.
Seamless Integration: Designed to work with various AI assistants and IDEs that support MCP, providing a consistent way to leverage AI across your development toolkit.
Extensibility: The protocol and the toolset can be expanded. You can define new tools and resources to expose more of your project-specific or Unity's functionality to AI.
Collaborative Potential: Facilitates a new way of collaborating where AI can assist in tasks traditionally done by team members, or help in onboarding new developers by guiding them through project structures and operations.

Unity 6.2 is set to introduce new built-in AI tools, including the previous Unity Muse (for generative AI capabilities like texture and animation generation) and Unity Sentis (for running neural networks in Unity runtime). As Unity 6.2 is not yet fully released, this comparison is based on publicly available information and anticipated functionalities:

Focus:
- MCP Unity: Primarily focuses on Editor automation and interaction. It allows external AI (like LLM-based coding assistants) to control and query the Unity Editor itself to manipulate scenes, assets, and project settings. It's about augmenting the developer's workflow within the Editor.
- Unity 6.2 AI:
  - Aims at in-Editor content creation (generating textures, sprites, animations, behaviors, scripts) and AI-powered assistance for common tasks, directly integrated into the Unity Editor interface.
  - A fine-tuned model to ask any question about Unity's documentation and API structure, with customized examples more accurate to Unity's environment.
  - Adds the functionality to run AI model inference, allowing developers to deploy and run pre-trained neural networks within your game or application for features like NPC behavior, image recognition, etc.
Use Cases:
- MCP Unity: "Create a new 3D object, name it 'Player', add a Rigidbody, and set its mass to 10." "Run all Play Mode tests." "Ask to fix the error on the console log." "Execute the custom menu item 'Prepare build for iOS' and fix any errors that may occur."
- Unity 6.2 AI: "Generate a sci-fi texture for this material." "Update all trees position in the scene to be placed inside of terrain zones tagged with 'forest'." "Create a walking animation for this character." "Generate 2D sprites to complete the character." "Ask details about the error on the console log."
Complementary, Not Mutually Exclusive: MCP Unity and Unity's native AI tools can be seen as complementary. You might use MCP Unity with your AI coding assistant to set up a scene or batch-modify assets, and then use Unity AI tools to generate a specific texture, or to create animations, or 2D sprites for one of those assets. MCP Unity provides a flexible, protocol-based way to interact with the Editor, which can be powerful for developers who want to integrate with a broader range of external AI services or build custom automation workflows.

MCP Unity is designed to work with any AI assistant or development environment that can act as an MCP client. The ecosystem is growing, but current known integrations or compatible platforms include:

Windsurf
Cursor
GitHub Copilot
Claude Desktop

Yes, absolutely! One of the significant benefits of the MCP Unity architecture is its extensibility.

In Unity (C#): You can create new C# classes that inherit from McpToolBase (or a similar base for resources) to expose custom Unity Editor functionality. These tools would then be registered in McpUnityServer.cs. For example, you could write a tool to automate a specific asset import pipeline unique to your project.
In Node.js Server (TypeScript): You would then define the corresponding TypeScript tool handler in the Server/src/tools/ directory, including its Zod schema for inputs/outputs, and register it in Server/src/index.ts. This Node.js part will forward the request to your new C# tool in Unity.

This allows you to tailor the AI's capabilities to the specific needs and workflows of your game or application.

Yes, MCP Unity is an open-source project distributed under the MIT License. You are free to use, modify, and distribute it according to the license terms.

Ensure the WebSocket server is running (check the Server Window in Unity)
Send a console log message from MCP client to force a reconnection between MCP client and Unity server
Change the port number in the Unity Editor MCP Server window. (Tools > MCP Unity > Server Window)

Check the Unity Console for error messages
Ensure Node.js is properly installed and accessible in your PATH
Verify that all dependencies are installed in the Server directory

The run_tests tool returns the following response:

Error:
Connection failed: Unknown error

This error occurs because the bridge connection is lost when the domain reloads upon switching to Play Mode. The workaround is to turn off Reload Domain in Edit > Project Settings > Editor > "Enter Play Mode Settings".

Troubleshooting: WSL2 (Windows 11) networking

When running the MCP (Node.js) server inside WSL2 while Unity runs on Windows 11, connecting to ws://localhost:8090/McpUnity may fail with ECONNREFUSED.

Cause: WSL2 and Windows have separate network namespaces — localhost inside WSL2 does not point to the Windows host. By default, Unity listens on localhost:8090.

Solution 1 — Enable WSL2 Mirrored mode networking (preferred)

Windows 11: Settings → System → For developers → WSL → Enable “Mirrored mode networking”.
Or via .wslconfig (then run wsl --shutdown and reopen WSL):

[wsl2]
networkingMode=mirrored

After enabling, localhost is shared between Windows and WSL2, so the default config (localhost:8090) works.

Solution 2 — Point the Node client to the Windows host

Set in your WSL shell before starting the MCP client:

# Use the Windows host IP detected from resolv.conf
export UNITY_HOST=$(grep -m1 nameserver /etc/resolv.conf | awk '{print $2}')

With this, Server~/src/unity/mcpUnity.ts will connect to ws://$UNITY_HOST:8090/McpUnity instead of localhost (it reads UNITY_HOST, and may also honor a Host in ProjectSettings/McpUnitySettings.json if present).

Solution 3 — Allow remote connections from Unity

Unity: Tools → MCP Unity → Server Window → enable “Allow Remote Connections” (Unity binds to 0.0.0.0).
Ensure Windows Firewall allows inbound TCP on your configured port (default 8090).
From WSL2, connect to the Windows host IP (see Solution 2) or to localhost if mirrored mode is enabled.

[!NOTE] Default port is 8090. You can change it in the Unity Server Window (Tools → MCP Unity → Server Window). The value maps to McpUnitySettings and is persisted in ProjectSettings/McpUnitySettings.json.

Validate connectivity

npm i -g wscat
# After enabling mirrored networking
wscat -c ws://localhost:8090/McpUnity
# Or using the Windows host IP
wscat -c ws://$UNITY_HOST:8090/McpUnity

Support & Feedback

If you have any questions or need support, please open an issue on this repository or alternative you can reach out on:

Linkedin:
Discord: gamester7178
Email: game.gamester@gmail.com

Contributing

Contributions are welcome! Please feel free to submit a Pull Request or open an Issue with your request.

Commit your changes following the Conventional Commits format.

License

This project is under MIT License

Acknowledgements

Mcp Unity Reviews

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