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Unity CLI Loop

基于 C# · 让 AI 助手直接操作你的系统与工具
英文名:unity-cli-loop
⭐ 368 Stars 🍴 32 Forks 💻 C# 📄 MIT 🏷 AI 7.5分
7.5AI 综合评分
aiautomationclimcpunityc#
✦ AI Skill Hub 推荐

Unity CLI Loop 是 AI Skill Hub 本期精选MCP工具之一。综合评分 7.5 分,整体质量较高。我们推荐使用将其纳入你的 AI 工具库,帮助提升工作效率。

📚 深度解析
Unity CLI Loop 是一款基于 MCP(Model Context Protocol)标准协议的 AI 工具扩展。MCP 协议由 Anthropic 开发并开源,旨在建立 AI 模型与外部工具之间的标准化通信接口,目前已被 Claude Desktop、Claude Code、Cursor 等主流 AI 工具采纳。

通过安装 Unity CLI Loop,你的 AI 助手将获得额外的工具调用能力,可以用自然语言直接操控该工具的功能,无需学习复杂的命令行语法。MCP 工具的核心价值在于"一次配置,永久增强"——配置完成后,每次与 AI 对话时都可以无缝调用这些工具。

在技术实现上,MCP 工具通过标准的 JSON-RPC 协议与 AI 客户端通信,工具的功能以"工具列表"的形式暴露给 AI 模型,AI 可以按需调用。Unity CLI Loop 提供了结构化的工具调用接口,使 AI 模型能够精确地理解和使用每个功能点,显著降低 AI 在工具使用上的错误率。

与传统的 API 集成相比,MCP 工具的优势在于无需编写代码——用户只需在配置文件中添加几行 JSON,即可让 AI 获得全新能力。AI Skill Hub 将 Unity CLI Loop 评为 AI 评分 7.5 分,属于同类工具中的优质选择。
📋 工具概览

让 AI 驱动 Unity,从编辑器到游戏模式。

Unity CLI Loop 是一款遵循 MCP(Model Context Protocol)标准协议的 AI 工具扩展。通过 MCP 协议,它可以让 Claude、Cursor 等主流 AI 客户端直接访问和操作外部工具、数据源和服务,实现 AI 能力的无缝扩展。无论是文件操作、数据库查询还是 API 调用,都可以通过自然语言在 AI 对话中直接触发,极大提升生产效率。

GitHub Stars
⭐ 368
开发语言
C#
支持平台
Windows / macOS / Linux
维护状态
轻量级项目,按需更新
开源协议
MIT
AI 综合评分
7.5 分
工具类型
MCP工具
Forks
32
📖 中文文档
以下内容由 AI Skill Hub 根据项目信息自动整理,如需查看完整原始文档请访问底部「原始来源」。

让 AI 驱动 Unity,从编辑器到游戏模式。

Unity CLI Loop 是一款遵循 MCP(Model Context Protocol)标准协议的 AI 工具扩展。通过 MCP 协议,它可以让 Claude、Cursor 等主流 AI 客户端直接访问和操作外部工具、数据源和服务,实现 AI 能力的无缝扩展。无论是文件操作、数据库查询还是 API 调用,都可以通过自然语言在 AI 对话中直接触发,极大提升生产效率。

📌 核心特色
  • 通过标准 MCP 协议与 Claude、Cursor 等主流 AI 客户端深度集成
  • 提供结构化工具调用接口,显著降低 AI 集成复杂度
  • 支持 Claude Desktop 和 Claude Code 无缝接入,开箱即用
  • 可与其他 MCP 工具组合叠加,构建完整 AI 工作站
  • 轻量无侵入设计,不影响现有系统架构
🎯 主要使用场景
  • 在 Claude Desktop 对话中直接调用本地工具,实现 AI 与系统的深度联动
  • 通过自然语言驱动复杂的多步骤自动化任务,代替繁琐手动操作
  • 将多个 MCP 工具组合使用,构建个人专属 AI 工作站
以下安装命令基于项目开发语言和类型自动生成,实际以官方 README 为准。
安装命令
# 方式一:通过 Claude Code CLI 一键安装
claude skill install https://github.com/hatayama/unity-cli-loop

# 方式二:手动配置 claude_desktop_config.json
{
  "mcpServers": {
    "unity-cli-loop": {
      "command": "npx",
      "args": ["-y", "unity-cli-loop"]
    }
  }
}

# 配置文件位置
# macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
# Windows: %APPDATA%/Claude/claude_desktop_config.json
📋 安装步骤说明
  1. 确认已安装 Node.js(v18 或以上版本)
  2. 打开 Claude Desktop 或 Claude Code 的 MCP 配置文件
  3. 按「交给 Agent 安装 → Claude Desktop」标签中的 JSON 配置填入 mcpServers 字段
  4. 保存配置文件并重启 Claude 客户端
  5. 重启后,在对话中即可使用本工具
以下用法示例由 AI Skill Hub 整理,涵盖最常见的使用场景。
常用命令 / 代码示例
# 安装后在 Claude 对话中直接使用
# 示例:
用户: 请帮我用 Unity CLI Loop 执行以下任务...
Claude: [自动调用 Unity CLI Loop MCP 工具处理请求]

# 查看可用工具列表
# 在 Claude 中输入:"列出所有可用的 MCP 工具"
以下配置示例基于典型使用场景生成,具体参数请参照官方文档调整。
配置示例
// claude_desktop_config.json 配置示例
{
  "mcpServers": {
    "unity_cli_loop": {
      "command": "npx",
      "args": ["-y", "unity-cli-loop"],
      "env": {
        // "API_KEY": "your-api-key-here"
      }
    }
  }
}

// 保存后重启 Claude Desktop 生效
📑 README 深度解析 真实文档 完整度 81/100 查看 GitHub 原文 →
以下内容由系统直接从 GitHub README 解析整理,保留代码块、表格与列表结构。

description: "Description of what the tool does and when to use it."

Key Features

Installation

[!WARNING] The following software is required - Unity 2022.3 or later - Node.js 22.0 or later - Required for CLI execution - Install via the official site or your preferred version manager

Step 1: Install the CLI

Select Window > Unity CLI Loop > Settings. A dedicated window will open — confirm that the CLI button is highlighted in blue.

Press the Install CLI button. <img width="277" height="306" alt="1" src="https://github.com/user-attachments/assets/0e25c327-73bf-4af6-997b-eebb3c26b372" />

If you see the following display, the installation was successful. <img width="272" height="309" alt="2" src="https://github.com/user-attachments/assets/ec14f73b-53be-4435-af95-84bb9125e3e4" />

<details> <summary>To install from terminal</summary>

npm install -g uloop-cli

See uloop-cli on npm for details. </details>

Step 2: Install Skills

Select your target (Claude Code, Codex, etc.) and press the Install Skills button. <img width="272" height="306" alt="3" src="https://github.com/user-attachments/assets/492e9680-726a-425b-8bf1-e5983f4f15a5" />

<details> <summary>To install from terminal</summary>

```bash

Install for Claude Code project

uloop skills install --claude

Install for OpenAI Codex project

uloop skills install --codex

Or install globally

uloop skills install --claude --global

</details>

That's it! After installing Skills, LLM tools can automatically handle instructions like these:

| Your Instruction | Skill Used by LLM Tools |
|---|---|
| "Launch Unity for this project" | `/uloop-launch` |
| "Fix the compile errors" | `/uloop-compile` |
| "Run the tests and tell me why they failed" | `/uloop-run-tests` + `/uloop-get-logs` |
| "Check the scene hierarchy" | `/uloop-get-hierarchy` |
| "Play the game and bring Unity to the front" | `/uloop-control-play-mode` + `/uloop-focus-window` |
| "Bulk-update prefab parameters" | `/uloop-execute-dynamic-code` |
| "Take a screenshot of Game View and adjust the UI layout" | `/uloop-screenshot` + `/uloop-execute-dynamic-code` |
| "Record my gameplay input" | `/uloop-record-input` |
| "Replay the recorded input" | `/uloop-replay-input` |


<details>
<summary>All 16 Bundled Skills</summary>

- `/uloop-launch` - Launch Unity with correct version
- `/uloop-compile` - Execute compilation
- `/uloop-get-logs` - Get console logs
- `/uloop-run-tests` - Run tests
- `/uloop-clear-console` - Clear console
- `/uloop-focus-window` - Bring Unity Editor to front
- `/uloop-get-hierarchy` - Get scene hierarchy
- `/uloop-find-game-objects` - Find GameObjects
- `/uloop-screenshot` - Capture EditorWindow
- `/uloop-simulate-mouse-ui` - Simulate mouse click, long-press, and drag on PlayMode UI elements
- `/uloop-simulate-mouse-input` - Simulate mouse input in PlayMode via Input System
- `/uloop-simulate-keyboard` - Simulate keyboard input in PlayMode via Input System
- `/uloop-record-input` - Record keyboard and mouse input during PlayMode
- `/uloop-replay-input` - Replay recorded input during PlayMode
- `/uloop-control-play-mode` - Control Play Mode
- `/uloop-execute-dynamic-code` - Execute dynamic C# code

</details>

<details>
<summary>Direct CLI Usage (Advanced)</summary>

You can also call the CLI directly without using Skills:
bash

Launch with build target (Android, iOS, StandaloneOSX, etc.)

uloop launch -p Android

Compile and wait for Domain Reload to complete

uloop compile --wait-for-domain-reload true

1. compile - Execute Compilation

Performs AssetDatabase.Refresh() and then compiles, returning the results. Can detect errors and warnings that built-in linters cannot find. You can choose between incremental compilation and forced full compilation. With WaitForDomainReload=true, results are returned after Domain Reload completes, regardless of the ForceRecompile value.

→ Execute compile, analyze error and warning content
→ Automatically fix relevant files
→ Verify with compile again

Quickstart

8. screenshot - Take a Screenshot of EditorWindow

Take a screenshot of any EditorWindow as a PNG. Specify the window name (the text displayed in the title bar/tab) to capture. When multiple windows of the same type are open (e.g., 3 Inspector windows), all windows are saved with numbered filenames. Supports three matching modes: exact (default), prefix, and contains - all case-insensitive.

→ screenshot (WindowName: "Console")
→ Save Console window state as PNG
→ Provide visual feedback to AI

Add completion script to shell config (auto-detects shell)

uloop completion --install

Unity CLI Loop

日本語

Unity License<br> ClaudeCode Cursor Codex Antigravity GitHubCopilot

<p align="center"> <img height="450" alt="logo-black-bg" src="https://github.com/user-attachments/assets/fca3047f-9042-4bf9-83bd-58b03f061082" /><br> <sub>(Logo inspired by Daft Punk's <i>Discovery</i> album art)</sub> </p>

Let an AI agent compile, test, and operate your Unity project from popular LLM tools via CLI.

Designed to keep AI-driven development loops running autonomously inside your existing Unity projects.

Note: This project was formerly known as uLoopMCP.

Tool Reference

For detailed specifications of all tools (parameters, responses, examples), see TOOL_REFERENCE.md.

Unity CLI Loop Extension Development

Unity CLI Loop enables efficient development of project-specific tools without requiring changes to the core package. The type-safe design allows for reliable custom tool implementation in minimal time. (If you ask AI, they should be able to make it for you soon ✨)

You can publish your extension tools on GitHub and reuse them across other projects. See uLoopMCP-extensions-sample for an example.

[!TIP] For AI-assisted development: Detailed implementation guides are available in .claude/rules/mcp-tools.md for tool development and .claude/rules/cli.md for CLI/Skills development. These guides are automatically loaded by Claude Code when working in the relevant directories.
[!IMPORTANT] Security Settings Project-specific tools require enabling Allow Third Party Tools in the uLoopMCP window "Security Settings". When developing custom tools that involve dynamic code execution, also consider the Dynamic Code Security Level setting.

<details> <summary>View Implementation Guide</summary>

Step 1: Create Schema Class (define parameters):

using System.ComponentModel;

public class MyCustomSchema : BaseToolSchema
{
    [Description("Parameter description")]
    public string MyParameter { get; set; } = "default_value";

    [Description("Example enum parameter")]
    public MyEnum EnumParameter { get; set; } = MyEnum.Option1;
}

public enum MyEnum
{
    Option1 = 0,
    Option2 = 1,
    Option3 = 2
}

Step 2: Create Response Class (define return data):

public class MyCustomResponse : BaseToolResponse
{
    public string Result { get; set; }
    public bool Success { get; set; }

    public MyCustomResponse(string result, bool success)
    {
        Result = result;
        Success = success;
    }

    // Required parameterless constructor
    public MyCustomResponse() { }
}

Step 3: Create Tool Class:

using System.Threading;
using System.Threading.Tasks;

[McpTool(Description = "Description of my custom tool")]  // ← Auto-registered with this attribute
public class MyCustomTool : AbstractUnityTool<MyCustomSchema, MyCustomResponse>
{
    public override string ToolName => "my-custom-tool";

    // Executed on main thread
    protected override Task<MyCustomResponse> ExecuteAsync(MyCustomSchema parameters, CancellationToken cancellationToken)
    {
        // Type-safe parameter access
        string param = parameters.MyParameter;
        MyEnum enumValue = parameters.EnumParameter;

        // Check for cancellation before long-running operations
        cancellationToken.ThrowIfCancellationRequested();

        // Implement custom logic here
        string result = ProcessCustomLogic(param, enumValue);
        bool success = !string.IsNullOrEmpty(result);

        // For long-running operations, periodically check for cancellation
        // cancellationToken.ThrowIfCancellationRequested();

        return Task.FromResult(new MyCustomResponse(result, success));
    }

    private string ProcessCustomLogic(string input, MyEnum enumValue)
    {
        // Implement custom logic
        return $"Processed '{input}' with enum '{enumValue}'";
    }
}

[!IMPORTANT] Important Notes: - Thread Safety: Tools execute on Unity's main thread, so Unity API calls are safe without additional synchronization.

Please also refer to Custom Tool Samples.

</details>

Unity CLI Loop Files

UserSettings/UnityMcpSettings.json stores per-user editor session state and should always remain local-only.

The .uloop/ directory at the project root stores CLI cache, tool registry, and runtime outputs. Most of its contents are local-only, but some files can optionally be git-tracked for team sharing.

FilePurposeGit-track?
settings.permissions.jsonTeam-wide security policy (third-party tool access, dynamic code security level)Optional
settings.tools.jsonPer-tool enable/disable preferencesOptional
tools.jsonAuto-generated MCP tool registryNo
outputs/Runtime outputs (test results, screenshots, hierarchy dumps)No
[!TIP] Recommended .gitignore pattern
> **/.uloop/*
> !**/.uloop/settings.permissions.json
> !**/.uloop/settings.tools.json
> 
This ignores auto-generated files and runtime outputs while allowing team-shared configuration to be tracked. Adjust the ! lines to match your team's needs — you can remove either line if you don't need to share that file.

Via Unity Package Manager

1. Open Unity Editor 2. Open Window > Package Manager 3. Click the "+" button 4. Select "Add package from git URL" 5. Enter the following URL:

https://github.com/hatayama/unity-cli-loop.git?path=/Packages/src

If you installed via git URL before v1.0.0: The repository was renamed from uLoopMCP to unity-cli-loop in v1.0.0. Please update your manifest.json:
> Old: https://github.com/hatayama/uLoopMCP.git?path=/Packages/src
> New: https://github.com/hatayama/unity-cli-loop.git?path=/Packages/src
> 
The old URL still works via GitHub redirect, but updating is recommended. OpenUPM users are not affected.

Using Scoped registry in Unity Package Manager

1. Open Project Settings window and go to Package Manager page 2. Add the following entry to the Scoped Registries list:

Name: OpenUPM
URL: https://package.openupm.com
Scope(s): io.github.hatayama.uloopmcp

  1. Open Package Manager window and select OpenUPM in the My Registries section. Unity CLI Loop will be displayed.
[!NOTE] com.unity.inputsystem is now an optional dependency. Install it only if you want Input System features such as simulate-keyboard, simulate-mouse-input, record-input, replay-input, and the Recordings window. com.unity.test-framework is also optional. Install it only if you want the run-tests tool to execute Unity Test Runner.
🎯 aiskill88 AI 点评 A 级 2026-05-25

该项目提供了一个开源的 MCP 工具,支持 Unity 的 AI 驱动功能,虽然代码质量较高,但仍需要进一步优化和测试。

📚 实用指南(长尾问题)
适合谁
  • 需要让 Claude / Cursor 操作本地工具的 AI 工程师
  • 构建多智能体协作系统的 Agent 开发者
最佳实践
  • 配置 MCP 服务器时建议使用 stdio 传输 + JSON-RPC,避免暴露公网
  • Agent 任务先做 dry-run 验证工具调用链,再开启自主执行
常见错误
  • API key 直接提交到 git 仓库(请用 .env 并加入 .gitignore)
  • MCP 配置路径拼错或权限不足,重启 Claude Desktop 才生效
部署方案
  • CLI:直接 npm install -g / pip install,命令行调用
  • 云端托管:可放在 Vercel / Railway / Fly.io 等 PaaS 平台
相关搜索
unity-cli-loop 中文教程unity-cli-loop 安装报错怎么办unity-cli-loop MCP 配置unity-cli-loop Agent 工作流unity-cli-loop 与同类工具对比unity-cli-loop 最佳实践unity-cli-loop 适合谁用
⚡ 核心功能
👥 适合谁
  • 需要让 Claude / Cursor 操作本地工具的 AI 工程师
  • 构建多智能体协作系统的 Agent 开发者
⭐ 最佳实践
  • 配置 MCP 服务器时建议使用 stdio 传输 + JSON-RPC,避免暴露公网
  • Agent 任务先做 dry-run 验证工具调用链,再开启自主执行
⚠️ 常见错误
  • API key 直接提交到 git 仓库(请用 .env 并加入 .gitignore)
  • MCP 配置路径拼错或权限不足,重启 Claude Desktop 才生效
👥 适合人群
Claude Desktop / Claude Code 用户AI 工具开发者需要扩展 AI 能力的专业人士自动化工程师
🎯 使用场景
  • 在 Claude Desktop 对话中直接调用本地工具,实现 AI 与系统的深度联动
  • 通过自然语言驱动复杂的多步骤自动化任务,代替繁琐手动操作
  • 将多个 MCP 工具组合使用,构建个人专属 AI 工作站
⚖️ 优点与不足
✅ 优点
  • +MIT 协议,可免费商用
  • +标准化 MCP 协议,生态互联性强
  • +与 Claude 官方生态无缝对接
  • +即插即用,配置简单快捷
⚠️ 不足
  • 依赖 Claude 客户端,非 Claude 用户无法使用
  • MCP 协议仍在持续演进,接口可能变更
  • 需要一定的配置步骤
⚠️ 使用须知

AI Skill Hub 为第三方内容聚合平台,本页面信息基于公开数据整理,不对工具功能和质量作任何法律背书。

建议在沙箱或测试环境中充分验证后,再部署至生产环境,并做好必要的安全评估。

📄 License 说明

✅ MIT 协议 — 最宽松的开源协议之一,可自由商用、修改、分发,仅需保留版权声明。

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📰 相关 AI 新闻
🍿 AI 圈相关吃瓜
🗺️ 相关解决方案
🧩 你可能还需要
基于当前 Skill 的能力图谱,自动补全的工具组合
❓ 常见问题 FAQ
unity-cli-loop 是一款C#开发的AI辅助工具。开源MCP工具:Let AI Drive Unity, from Editor to Play Mode.。⭐368 · C# 主要应用场景包括:用于 Unity 开发的 AI 驱动工具,支持从编辑器到游戏模式的自动化发布。。
💡 AI Skill Hub 点评

经综合评估,Unity CLI Loop 在MCP工具赛道中表现稳健,质量良好。如果你已有明确的使用需求,可以直接上手体验;如果还在评估阶段,建议对比同类工具后再做决策。

⬇️ 获取与下载
⬇ 下载源码 ZIP

✅ MIT 协议 · 可免费商用 · 直接从 aiskill88 服务器下载,无需跳转 GitHub

📚 深入学习 Unity CLI Loop
查看分步骤安装教程和完整使用指南,快速上手这款工具
🌐 原始信息
原始名称 unity-cli-loop
原始描述 开源MCP工具:Let AI Drive Unity, from Editor to Play Mode.。⭐368 · C#
Topics aiautomationclimcpunityc#
GitHub https://github.com/hatayama/unity-cli-loop
License MIT
语言 C#
🔗 原始来源
🐙 GitHub 仓库  https://github.com/hatayama/unity-cli-loop

收录时间:2026-05-25 · 更新时间:2026-05-26 · License:MIT · AI Skill Hub 不对第三方内容的准确性作法律背书。