Unity Editor package + Node.js bridge that implements the Model Context Protocol (MCP) so AI assistants (Claude, Cursor, Windsurf, Copilot, etc.) can inspect and manipulate your Unity projects via tools such as execute_menu_item, update_gameobject, run_tests, etc.
https://github.com/CoderGamester/mcp-unityYou're deep in a Unity workflow when you need to create a dozen GameObjects, configure their components, run specific tests, and check the console logs. Instead of clicking through menus and manually tweaking inspector values, you type: "Create 10 enemy spawn points with BoxCollider components, set their layers to 'Enemy', run the PlayMode tests, and show me any errors from the console."
MCP Unity makes this happen. It's a Model Context Protocol bridge that connects your AI assistant directly to Unity Editor, turning natural language into actual Unity operations.
Unity development involves tons of repetitive Editor tasks. You know the drill: right-click menus, inspector tweaks, test running, asset management. These operations break your flow and eat up time that should go toward actual game logic.
Most Unity AI tools focus on code generation, but your bottleneck isn't writing code—it's managing the Editor itself. You need something that understands Unity's structure and can execute Editor operations directly.
This isn't another code generator. MCP Unity exposes Unity Editor functionality as tools that AI assistants can execute. Your AI can:
The key difference? Your AI assistant operates Unity Editor directly instead of just generating code you then have to execute manually.
Scene Setup Speed: "Create a player prefab with CharacterController, set its layer to Player, and add it to the current scene" happens in seconds, not minutes of clicking.
Batch Operations: "Find all objects tagged 'Enemy' and add a NavMeshAgent component with speed 3.5" processes your entire scene instantly.
Test Automation: "Run all PlayMode tests containing 'Movement' and show me the failures" gives you immediate feedback without navigating the Test Runner.
Asset Discovery: "List all texture assets larger than 2MB" or "Find prefabs containing Rigidbody components" replaces manual asset searching.
Debug Workflows: "Show me the last 10 error messages and explain what might be causing them" combines console monitoring with AI analysis.
Rapid Prototyping: You're building a tower defense game. Instead of manually creating and configuring tower prefabs, you describe what you need: "Create 5 tower GameObjects with different names, add Collider and custom TowerBehavior script, set their ranges to 5, 7, 10, 12, 15 respectively." Your AI executes this through Unity Editor while you focus on game logic.
Asset Cleanup: Before a build, you need to optimize. "Find all unused textures in the project and list materials using uncompressed textures above 1024x1024." Your AI scans the asset database and provides a detailed report, saving hours of manual inspection.
Test-Driven Development: You've written new player movement code. "Run all tests in the PlayerMovement test suite, and if any fail, show me the failing assertions and suggest fixes based on the current player controller implementation." Your AI runs the tests and analyzes failures with full context of your codebase.
Team Onboarding: A new developer joins your project. They can ask: "Explain the scene hierarchy structure and show me which GameObjects handle player input" - your AI provides a detailed breakdown of your project's architecture by actually inspecting the Unity project.
MCP Unity connects to AI assistants that support the Model Context Protocol: Claude Desktop, Cursor, Windsurf, and others. The setup is straightforward - install the Unity package, configure your AI client, and start the server.
The workflow feels natural: You're already using these AI assistants for coding, now they can manipulate your Unity project directly. No context switching between your AI chat and Unity Editor - your assistant becomes an extension of Unity itself.
Development Flow: You're working in Cursor on a Unity script. You realize you need to test it with specific scene conditions. Instead of switching to Unity, you tell Cursor: "Create a test scene with 3 enemies at positions (1,0,1), (5,0,3), (2,0,7), add NavMeshAgent to each, then run the AI behavior tests." Cursor handles the Unity setup while you continue coding.
Debugging Integration: Your console shows errors but you're deep in code. "Check Unity console for the last 5 errors and cross-reference them with the current script I'm editing." Your AI provides immediate context without breaking your coding flow.
MCP Unity transforms Unity development from a series of manual operations into a conversation with an AI that understands both your codebase and your project structure. It's the difference between describing what you want to happen and actually making it happen through natural language.
Ready to skip the menu maze? Your Unity workflow is about to get a lot more efficient.