Unity MCP Server (C#)

Created By

NoSpoonLab8 months ago

Unity MCP server, providing a bridge between the Unity Editor and external Large Language Models (LLMs) or cloud-based AI agents.

# unity

# mcp

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Content

Unity MCP Server (C#)

This project is a Model Context Protocol (MCP) server for Unity, providing a bridge between the Unity Editor and external Large Language Models (LLMs) or cloud-based AI agents. The server side is fully implemented with C#.

What is Unity Model Context Protocol (MCP)?

Unity MCP is a protocol designed to enable seamless communication between the Unity Editor and external tools, scripts, or AI models. It allows for real-time automation, remote control, and intelligent interaction with Unity projects. MCP can be used as a bridge so that LLMs (Large Language Models), either running locally or in the cloud, can directly interact with the Unity Editor—enabling advanced workflows, procedural content generation, automated testing, and more.

Key Features

C# Server Implementation: The backend/server is written entirely in C#, making it easy to integrate with Unity and .NET environments.
MCP Bridge: Acts as a bridge between Unity and external LLMs or cloud services, allowing AI models to send commands and receive data from the Unity Editor.
Real-time Automation: Supports real-time automation of editor tasks, scene manipulation, asset management, and more.
Extensible Protocol: Built on the open Model Context Protocol, making it easy to extend for custom workflows or new AI capabilities.
Inspired by: This project is based on the original work at https://github.com/justinpbarnett/unity-mcp/.

How it Works

Server-Client Architecture: The C# MCP server listens for incoming connections from clients (such as LLMs, scripts, or cloud agents).
Command Handling: Clients send MCP-formatted messages to the server, which are then interpreted and executed in the Unity Editor context.
Bi-directional Communication: The server can send responses, data, or events back to the client, enabling interactive and intelligent workflows.
Use Cases: Procedural content generation, automated scene setup, AI-driven testing, remote Unity control, and more.

This project is a starting point for anyone looking to connect Unity with the power of LLMs or external automation tools using the Model Context Protocol.

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