Unity MCP Server

A Model Context Protocol (MCP) server for Unity game development, enabling AI assistants to interact with Unity projects through a set of specialized tools.

Overview

The Unity MCP Server provides a bridge between AI assistants (like Cursor AI or Claude) and Unity projects. It offers tools for:

Reading and searching files in Unity projects
Parsing Unity scenes and prefabs
Analyzing C# code and detecting errors
Running automated tests in batch mode
Generating scripts from templates
Validating shaders
And more...

The server is designed to run with Unity in batch mode, allowing for operations that require the Unity engine without needing the Editor GUI.

Installation

Prerequisites

Node.js 16+
Unity 2022.3 LTS or newer (recommended)

Setup

Clone this repository:
git clone https://github.com/GrandMasterK414/unity-smithery-mcp.git cd unity-smithery-mcp
Install dependencies:
npm install
Build the project:
npm run build

Configuration

The server uses the config package for configuration. Edit config/default.json to adjust settings:

{
  "server": {
    "port": 3000,
    "host": "0.0.0.0"
  },
  "unity": {
    "unityPath": "/path/to/Unity/Editor/Unity",
    "projectPath": "/path/to/your/unity/project",
    "timeoutMs": 60000,
    "batchMode": true
  },
  "logging": {
    "level": "info",
    "file": "logs/mcp-server.log",
    "maxSize": 5242880,
    "maxFiles": 5
  },
  "security": {
    "allowedPaths": ["Assets", "ProjectSettings", "Packages"],
    "disallowedCommands": ["rm", "del", "format", "shutdown"]
  }
}

Usage

Starting the Server

npm start

To run in Smithery mode:

npm run smithery:start

Using with AI Assistants

This server is primarily designed to work with AI assistants through tools defined in the MCP specification. For Cursor or Smithery.ai integration, follow their documentation to connect to this MCP server.

Available Tools

Tool Name	Description
`open_file`	Reads the contents of a file in the Unity project
`search_files`	Searches for text patterns in project files
`list_assets`	Lists project assets of a certain type or in a folder
`get_project_info`	Gets high-level information about the Unity project
`parse_scene`	Parses a Unity scene file to extract game objects hierarchy
`parse_prefab`	Parses a Unity prefab file to extract components
`find_in_scenes`	Finds scenes containing a specific GameObject or component
`analyze_cs_code`	Compiles C# code to find compiler errors
`find_references`	Finds references to a C# class or method
`generate_script`	Creates a new C# script file from a template
`validate_shader`	Compiles a shader and reports errors
`inspect_yaml`	Inspects a YAML asset file
`run_tests`	Runs Unity's automated tests in batch mode
`simulate_playmode`	Experimental - runs a scene in play mode for a short duration

Docker Support

A Dockerfile is included for containerized deployment. Build the Docker image:

docker build -t unity-mcp-server .

Run the container:

docker run -p 3000:3000 -v /path/to/unity/project:/project unity-mcp-server

Smithery.ai Integration

This server can be deployed on Smithery.ai using the provided smithery.yaml configuration.

License

MIT

Contributing

Contributions are welcome! Please open an issue or submit a pull request.

This server cannot be installed

security - not tested

license - not found

quality - not tested

How are these scores calculated?

hybrid server

The server is able to function both locally and remotely, depending on the configuration or use case.

A protocol server that bridges AI assistants with Unity projects, allowing them to analyze code, parse scenes, generate scripts, and perform other Unity operations through specialized tools.

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View all related MCP servers

Unity MCP Server

Unity MCP Server

Overview

Installation

Prerequisites

Setup

Configuration

Usage

Starting the Server

Using with AI Assistants

Available Tools

Docker Support

Smithery.ai Integration

License

Contributing

Related MCP Servers

Notion MCP Server

MCP Python Toolbox

YetAnotherUnityMcp

Unity MCP Integration

Appeared in Searches

New MCP Servers

MCP directory API