funplay-unity-mcp
Reduces iteration cycles in Unity development by enabling Claude to execute code, capture screenshots, and automate play mode testing directly within the edi…
The Most Advanced MCP Server for Unity Editor with execute_code, prompts/resources, input simulation, screenshots, and play mode automation.
- Ask Claude to screenshot your Unity scene and describe what's currently visible in the editor
- Generate C# code snippets and have Claude execute them directly in your Unity project
- Automate repetitive Unity editor tasks like creating game objects or adjusting component settings
Reduces iteration cycles in Unity development by enabling Claude to execute code, capture screenshots, and automate play mode testing directly within the editor, eliminating manual context-switching and enabling faster feedback loops.
Game development teams integrating AI-assisted debugging, testing, and asset management into their Unity workflow.
https://github.com/FunplayAI/funplay-unity-mcp
By FunplayAI
How to Get It
claude mcp add funplay-unity-mcp -- npx -y funplay-unity-mcp
Tip: Paste this into a Claude Code conversation. Verify command matches your Claude Code version.
Auto-generated from the tool's public listing — not hands-on verified. Cross-check against the source repo's README before running.
Once it’s connected, paste this into Claude:
Screenshot my Unity scene and describe what's currently visible in the editor
Trust Signals Auto-scanned
Data & Access
Community Pulse New
No community discussions found yet. This doesn't mean the tool isn't good — it may be new or serve a niche use case.
Reviewer notes
Auto-scanned review. These are observations, not a security certification.
Scored from trust signals (evidence-eval-v1): 214 GitHub stars; contributors unknown; last commit 0d ago; license MIT.
Things to check
- Scanned, not hands-on tested — this entry was auto-scanned from public metadata (GitHub metrics, license, security flags). No reviewer has run it, and no tool-specific limitations have been documented yet.
How to evaluate tools before deploying →
Data shown here comes from public APIs and automated scanning. Reviewer notes reflect one person's experience. This is not a security certification or legal recommendation. Always evaluate tools according to your own organization's policies.
Evaluation
Scored from trust signals (evidence-eval-v1): 214 GitHub stars; contributors unknown; last commit 0d ago; license MIT.