🔌
MCP工具

Unity编辑器MCP服务器

基于 C# · 让 AI 助手直接操作你的系统与工具
英文名:funplay-unity-mcp
⭐ 64 Stars 🍴 8 Forks 💻 C# 📄 MIT 🏷 AI 7.5分
7.5AI 综合评分
UnityMCP服务器AI编程游戏开发代码执行
✦ AI Skill Hub 推荐

Unity编辑器MCP服务器 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编辑器MCP服务器 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编辑器MCP服务器,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编辑器MCP服务器 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编辑器MCP服务器 评为 AI 评分 7.5 分,属于同类工具中的优质选择。
📋 工具概览

专为Unity编辑器设计的高级MCP服务器工具,支持代码执行、提示词和资源管理等功能。集成Claude等AI模型,帮助游戏开发者通过AI辅助提高开发效率,适合使用Cursor、Claude Code等工具的Unity开发人员。

Unity编辑器MCP服务器 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
⭐ 64
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
8
📖 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」。

专为Unity编辑器设计的高级MCP服务器工具,支持代码执行、提示词和资源管理等功能。集成Claude等AI模型,帮助游戏开发者通过AI辅助提高开发效率,适合使用Cursor、Claude Code等工具的Unity开发人员。

Unity编辑器MCP服务器 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/FunplayAI/funplay-unity-mcp

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

# 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编辑器MCP服务器 执行以下任务...
Claude: [自动调用 Unity编辑器MCP服务器 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___mcp___": {
      "command": "npx",
      "args": ["-y", "funplay-unity-mcp"],
      "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 67/100 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。

简介

<p align="center"> <h1 align="center">Funplay MCP for Unity</h1> <p align="center"> <strong>The Most Advanced MCP Server for Unity Editor</strong> </p> <p align="center"> <a href="#"><img src="https://img.shields.io/badge/Unity-2022.3%2B-black?logo=unity" alt="Unity 6000.0+"></a> <a href="#"><img src="https://img.shields.io/badge/License-MIT-blue.svg" alt="License: MIT"></a> <a href="#"><img src="https://img.shields.io/badge/MCP-Compatible-green" alt="MCP Compatible"></a> <a href="#"><img src="https://img.shields.io/badge/Platform-Editor%20Only-orange" alt="Editor Only"></a> </p> <p align="center"> <a href="./README_CN.md">中文</a> | English </p> <p align="center"> <img src="./Documentation~/Text%2BLogo.png" alt="The Most Advanced MCP Server for Unity" width="100%"> </p> </p>

💖 If you find this project useful, please consider giving it a Star. It helps more Unity developers discover it and supports ongoing development.

---

Funplay MCP for Unity is an MIT-licensed Unity Editor MCP server that lets AI assistants like Claude Code, Cursor, LM Studio, Windsurf, Codex, and VS Code Copilot operate directly inside your running Unity project.

Describe your game in one sentence — your AI assistant builds it in Unity through Funplay MCP for Unity's 91 built-in tools for scene creation, script generation, runtime validation, input simulation, performance analysis, and editor automation.

"Build a snake game with a 10x10 grid, food spawning, score UI, and game-over screen" Your AI assistant handles it through Funplay MCP for Unity: creates the scene, generates all scripts, sets up the UI, and configures the game logic — all from a single prompt.

<p align="center"> <img src="./Documentation~/demo.gif" alt="Funplay MCP for Unity — 16s demo" width="100%"> </p> <p align="center"><em>16-second demo — AI generates a 3D model and integrates it into the scene end-to-end. <a href="https://github.com/FunplayAI/funplay-unity-mcp/raw/main/Documentation~/demo.mp4">Watch HD MP4</a>.</em></p>

Highlights

  • 91 Built-in Tools — Scene editing, assets, scripts, play mode control, screenshots, performance analysis, prompts, resources, structured object location, SerializedObject-based component editing, editor-state inspection, menu-item fallback, and editor automation across 20 modules
  • Structured Returns + instanceId Chaining — Tools return {success, message, data} JSON with stable instanceId fields so agents can chain by_id calls reliably instead of re-resolving by name
  • IFunplayCommand for execute_code — New snippet template with auto-Undo (ctx.RegisterObjectCreation/Modification/DestroyObject), structured logs (ctx.Log/LogWarning/LogError), and a tracked changelog returned to the agent
  • Resources & Prompts — Live project context, scene/selection/error resources, resource templates, and reusable workflow prompts
  • Input Simulation + Screenshots — Drive play mode with keyboard/mouse simulation and verify results with game/scene captures
  • Built-in Updating — Check for updates from the Unity menu and either re-pull the Git package or auto-import the latest unitypackage
  • One-Click Client Configuration — Generate MCP config entries for Claude Code, Cursor, LM Studio, VS Code, Kiro, Trae, Codex, and similar clients directly from the Unity window
  • Tool Exposure Control — Edit the exact tools exposed by core and full
  • Project Skills Manager — Configure project-level skills for supported AI clients, currently installing the default unity-mcp-workflow skill
  • Plugin Settings — Toggle verbose plugin debug logging when troubleshooting MCP connections or tool execution
  • Vendor Agnostic — Works with any AI client that supports MCP: Claude Code, Cursor, LM Studio, Windsurf, Codex, VS Code Copilot, etc.

MCP Capabilities

The current open-source package exposes four high-value capability layers:

  • Tools — 91 total tools in full, 29 focused tools in core
  • Primary executionexecute_code for rich editor/runtime orchestration
  • Prompts — workflow prompts like fix_compile_errors, runtime_validation, and create_playable_prototype
  • Resources — project context, scene summaries, selection state, compile errors, console errors, MCP interaction history, plus resource templates for scene objects, components, and asset paths

Requirements

  • Unity 2022.3 or later
  • .NET / Mono with Newtonsoft.Json

1. Install via UPM (Git URL)

In Unity, go to Window → Package Manager → + → Add package from git URL:

https://github.com/FunplayAI/funplay-unity-mcp.git
💡 Before you clone or install, a quick ⭐ on GitHub would be greatly appreciated.

5. Start Building

Open your AI client and try: "Create a 3D platformer level with 5 floating platforms"

Quick Start

If you just want to get connected fast, do these three things:

  • Install the Unity package from the Git URL
  • Start Funplay > MCP Server
  • Use the built-in one-click client configuration

3. Configure Your AI Client

Use the built-in One-Click MCP Configuration in the Funplay > MCP Server window first.

Select your target client, click Configure, and the package writes the recommended MCP config entry for you.

For Claude Code, Cursor, and Codex, click Configure + Skills to also install the default project MCP workflow skill.

If you want project-specific AI guidance for the current Unity project, open Funplay → Project Skills to choose supported platforms and install the default unity-mcp-workflow skill.

If you prefer to edit config files manually, use the examples below as fallback references:

<details> <summary>Claude Code / Claude Desktop</summary>

{
  "mcpServers": {
    "funplay": {
      "type": "http",
      "url": "http://127.0.0.1:8765/"
    }
  }
}

</details>

<details> <summary>Cursor</summary>

{
  "mcpServers": {
    "funplay": {
      "url": "http://127.0.0.1:8765/"
    }
  }
}

</details>

<details> <summary>LM Studio</summary>

LM Studio's mcp.json location can vary by version and platform. Prefer Program > Install > Edit mcp.json in LM Studio. Funplay's one-click Configure button opens LM Studio's lmstudio://add_mcp link and only updates an existing config file if one is already present, instead of creating a guessed path.

{
  "mcpServers": {
    "funplay": {
      "url": "http://127.0.0.1:8765/"
    }
  }
}

</details>

<details> <summary>VS Code</summary>

{
  "servers": {
    "funplay": {
      "type": "http",
      "url": "http://127.0.0.1:8765/"
    }
  }
}

</details>

<details> <summary>Trae</summary>

{
  "mcpServers": {
    "funplay": {
      "url": "http://127.0.0.1:8765/"
    }
  }
}

</details>

<details> <summary>Kiro</summary>

{
  "mcpServers": {
    "funplay": {
      "type": "http",
      "url": "http://127.0.0.1:8765/"
    }
  }
}

</details>

<details> <summary>Codex</summary>

[mcp_servers.funplay]
url = "http://127.0.0.1:8765/"

</details>

<details> <summary>Windsurf</summary>

Use the same JSON structure as Cursor unless your local Windsurf version requires a different MCP config format.

</details>

Comparison With Coplay

The table below compares this repository with the publicly documented behavior of Coplay's open-source unity-mcp repository on GitHub.

AreaFunplay MCP for UnityCoplay unity-mcp
Unity-side architectureEmbedded Unity Editor package with built-in HTTP MCP serverUnity bridge plus local Python MCP server
Extra local prerequisitesUnity package only for core workflowsUnity + Python 3.10+ + uv according to the public quick start
Primary workflow styleexecute_code first, then focused helper toolsBroad manage_* tool families exposed through the bridge
Default tool exposureCompact core profile with optional full expansionPublic docs emphasize a broad always-available tool surface
Built-in context modelProject resources, resource templates, workflow prompts, interaction historyPublic README emphasizes tool families and bridge/server workflow
Play mode validationBuilt-in play mode control, screenshots, logs, and input simulation in the packagePublic README emphasizes broad Unity management and automation tools
PositioningLightweight, direct, MIT-licensed Unity MCP server for AI-driven editor controlFull-featured Unity bridge maintained by Coplay with Python-backed server setup

Source for Coplay column: CoplayDev/unity-mcp

Comparison With Unity AI Assistant

The table below compares this repository with Unity Technologies' official com.unity.ai.assistant package (v2.7.0-pre.2 as of 2026-05).

AreaFunplay MCP for UnityUnity AI Assistant
Minimum Unity version2022.36000.3 (Unity 6 only)
LicenseMIT, open sourceUnity Terms of Service, proprietary
DeploymentLocal HTTP MCP server in Editor, no cloudEditor + native Relay subprocess + Unity Cloud backend
BillingFree, user brings their own AI clientCredits-based (Unity Dashboard)
Tool exposure91 tools across 20 modules, core (29) / full profiles~15 MCP tools (mostly Manage* families)
Generic escape hatchexecute_code — CodeDom in-memory compile, IFunplayCommand + Undo, no sandbox (client-side approval)RunCommand — namespace blacklist sandbox
Play mode validationFull loop: enter / simulate input / capture / read logs / exitEnter/Exit only; no input simulation
Asset generatorsNot built-in (compose external APIs via execute_code)Native Image / Mesh / PBR / Sound / Animation generators
Primary client modelBYO any MCP client (Claude Code / Cursor / LM Studio / Codex / VS Code)Built-in chat window + ACP for Claude/Gemini via Gateway
Offline-capableYes for tool calls (inference depends on chosen client)No (inference requires Unity Cloud)

For a long-form comparison of the two approaches see Funplay Unity MCP vs Unity AI Assistant detailed comparison (Chinese).

🎯 aiskill88 AI 点评 A 级 2026-05-22

融合Unity开发与AI能力的创新工具,代码执行能力强大但需防范安全风险。社区关注度中等,维护活跃度有待观察。

⚡ 核心功能
👥 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。

🔗 相关工具推荐
📚 相关教程推荐
❓ 常见问题 FAQ
funplay-unity-mcp 是一款C#开发的AI辅助工具。开源MCP工具:The Most Advanced MCP Server for Unity Editor with execute_code, prompts/resourc。⭐64 · C# 主要应用场景包括:Unity游戏开发辅助、AI代码生成与补全、编辑器自动化任务。
💡 AI Skill Hub 点评

经综合评估,Unity编辑器MCP服务器 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编辑器MCP服务器
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 funplay-unity-mcp
原始描述 开源MCP工具:The Most Advanced MCP Server for Unity Editor with execute_code, prompts/resourc。⭐64 · C#
Topics UnityMCP服务器AI编程游戏开发代码执行
GitHub https://github.com/FunplayAI/funplay-unity-mcp
License MIT
语言 C#
🔗 原始来源
🐙 GitHub 仓库  https://github.com/FunplayAI/funplay-unity-mcp

收录时间:2026-05-21 · 更新时间:2026-05-22 · License:MIT · AI Skill Hub 不对第三方内容的准确性作法律背书。