
Advanced Unity MCP
A bridge that enables controlling Unity Editor through natural language commands via AI assistants, allowing users to create materials, build projects, manage scenes, and configure settings without manual interaction.
README
Advanced Unity MCP from Code Maestro
Control Unity with AI through natural language commands.
Instead of clicking through menus and manually setting up GameObjects, just tell your AI assistant what you want and watch it happen automatically.
"Create a red material and apply it to a cube"
"Build the project for Android"
"Make a new scene with a camera and directional light"
Quick Start
1. Install the Package
Unity Package Manager → Add package from git URL:
https://github.com/codemaestroai/advanced-unity-mcp.git
2. Connect Your AI
- Go to
Code Maestro > MCP Dashboard
in Unity - Click Configure next to your preferred MCP client
- Start giving commands!
Supported MCP Clients: Code Maestro, GitHub Copilot, Cursor, Windsurf, Claude Code
What Unity MCP Can Do
Core Editor Control - Play/pause/stop game, execute menu items, read/clear console messages
Asset & Scene Management - Create/modify/delete materials, prefabs, scripts, manage scenes and GameObjects
Build & Platform Tools - Build settings, platform switching, Android Debug Bridge operations
Project Configuration - Unity packages, project settings, PlayerPrefs, external tools
Performance Analysis - Unity Profiler control for performance bottlenecks
Examples
"Check the console for any errors"
"Create a script called PlayerMovement with WASD controls"
"Switch the build target to iOS"
"Add a rigidbody component to the selected object"
"Create a new material with metallic properties"
"Save the current GameObject as a prefab"
"Clear all console messages and check for warnings"
How It Works
Unity MCP bridges your Unity Editor with AI assistants using the Model Context Protocol. Two components work together:
- Bridge Server - Runs in Unity Editor, provides API access
- Relay Server - Handles communication with MCP clients
The setup is automatic once you install the package and configure your MCP client.
Requirements
- Unity 2022+
- MCP Client (Such as GitHub Copilot or Cursor)
- Python 3.12+ and UV package manager installed and configured in the environment path
Troubleshooting
Installing Python and UV
Windows:
- Download Python from python.org
- During installation, check "Add Python to PATH"
- Open Command Prompt and run:
# Verify Python is installed python --version # Install UV pip install uv
macOS: Install Python using Homebrew:
# Install Homebrew if not already installed
/bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"
# Install Python
brew install python@3.12
# Install UV
pip3 install uv
Linux:
# Ubuntu/Debian
sudo apt update
sudo apt install python3.12 python3-pip
# Install UV
pip3 install uv
Verify Installation
Open a terminal and run:
python --version # Should show Python 3.12+
uv --version # Should show UV version
Common Issues
"python is not recognized" error:
- Make sure Python is added to your system PATH
- On Windows, restart your computer after installation
- On macOS/Linux, restart your terminal
"uv is not recognized" error:
- Install UV with:
pip install uv
orpip3 install uv
- On Windows, you may need to add Python Scripts folder to PATH:
C:\Users\[YourUsername]\AppData\Local\Programs\Python\Python312\Scripts
Permission errors on macOS/Linux:
- Use
pip3 install --user uv
to install for current user only
Made by Code Maestro • Join our Discord • Report Issues
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.