WxstV2

WxstV2 / robloxstudio-mcp

Public
19
0
89% credibility
Found May 31, 2026 at 19 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
AI Summary

This project connects AI assistants like Claude and Gemini to Roblox Studio, letting game developers control playtests, inspect game code, and make changes through simple conversations. It includes both a read-only inspection mode for safe exploration and a full control mode for making edits. The tool adds special features that make AI-controlled playtesting actually work reliably, unlike other similar tools.

How It Works

1
🔍 Discovering the Project

A game developer learns they can use AI assistants to help build and test their Roblox games more efficiently.

2
📦 Installing the Studio Plugin

They download and install a special plugin into Roblox Studio that lets it communicate with AI assistants.

3
🔗 Connecting to an AI Assistant

They set up their AI assistant (like Claude, Gemini, or Codex) to talk to their Roblox Studio plugin.

4
🎮 Starting a Playtest with AI Help

With everything connected, they ask their AI assistant to start a game test and watch it launch automatically.

5
Choosing Your Workflow
👀
Read-Only Mode

Safely browse game structure, review scripts, and inspect things without accidentally changing anything.

✏️
Full Control Mode

Create objects, edit scripts, and modify properties directly through conversations with the AI.

6
💬 Asking Questions and Getting Results

They ask questions like 'What's in this game?' or 'Find scripts using old APIs' and get instant answers with working code.

🚀 Faster Development, Fewer Headaches

The AI can inspect running games, find bugs, and help optimize code while the developer focuses on being creative.

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AI-Generated Review

What is robloxstudio-mcp?

This is a Model Context Protocol server that hooks AI coding assistants like Claude and Gemini directly into Roblox Studio. It exposes 46 tools for reading game structure, editing scripts, driving playtests, and inspecting runtime state. Built on TypeScript and distributed via npm, it solves the problem of getting AI agents to actually talk to a running Roblox game across all execution contexts (edit, server, and client peers).

Why is it gaining traction?

The hook here is that per-peer `execute_luau` and `stop_playtest` actually work out of the box. The fork fixes four bugs in the upstream project, most notably enabling `target=client-N` to route through a server-peer broker and making `stop_playtest` call `StudioTestService:EndTest` properly. Unlike the official Roblox MCP, this lets AI agents run code inside the live game VM rather than a sandboxed plugin context, so you can inspect module state that changes during playtest execution.

Who should use this?

Roblox developers who want AI agents to drive actual development and debugging workflows, not just read static scripts. Game designers can spawn test NPCs, capture screenshots, or inspect memory categories via `get_memory_breakdown`. Scripters debugging networking or module loading issues benefit from runtime state inspection. If you just need to browse script files, the official Roblox MCP suffices.

Verdict

This is a niche tool for a specific workflow, but it executes that workflow with care. The 0.899% credibility score reflects its newness (19 stars) and the fact that it is a fork, not a primary project. Documentation is thorough for its scope, and the verification recipe gives you a clear test plan. If you need AI agents to control running Roblox games, this is the most complete option available.

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