dsphper/lanhu-mcp: README-based editorial guide

dsphper/lanhu-mcp describes itself in the README as "⚡ 需求分析效率提升 200%！全球首个为 AI 编程时代设计的团队协作 MCP 服务器，自动分析需求自动编写前后端代码，下载切图". This article keeps to facts that can be checked in the repository. Stars, forks, and promotional badges are signals of attention, not proof of quality. Under "🎨 Lanhu MCP Server | 蓝湖MCP服务器2.0", the README says: lanhumcp | 蓝湖mcp | lanhu-mcp | 蓝湖AI助手 | 蓝湖skills | Lanhu AI Integration. That establishes the project's stated boundary, not a production test.

The README's "🌟 项目亮点" section gives a useful starting point for deciding whether the project fits: 🎨 UI设计支持：自动下载设计稿，智能提取切图，语义化命名；设计图分析可获取尺寸/间距/颜色/字体等精确参数，并得到转换后的 HTML+CSS 代码参考. If that problem is not yours, popularity is a poor reason to adopt it. Project names, commands, and component names are kept as written so a reader can return to the primary source without guessing at terminology. Another checkable README item is: 📋 智能需求分析：自动提取 Axure 原型，三种分析模式（开发/测试/探索），需求分析准确率>95%. It can shape a first test, but it does not replace testing in the intended environment.

The operating model is spread across sections such as "🚀 快速开始". The source evidence includes: > ⚠️ 重要提示：必须使用支持视觉功能的AI模型！ > > 本项目需要AI模型具备图像识别和分析能力，推荐使用以下2026年主流视觉模型： > - 🤖 Claude (Anthropic) > - 🌟 GPT (OpenAI) > - 💎 Gemini (Google) > - 🚀 Kimi (月之暗面) > - 🎯 Qwen (阿里巴巴) > - 🧠 DeepSeek (深度求索) > > 不支持纯文本模型（如 GPT-3.5、Claude Instant. This article does not turn missing architecture, performance, or security details into claims. A real deployment still needs a look at the repository layout, configuration files, and release history.

Start installation from the README's documented entry point. A command that can be checked in the source is: # 1. 克隆项目 git clone https://github.com/dsphper/lanhu-mcp.git cd lanhu-mcp # 2. 配置环境（会引导你输入 Cookie） bash setup-env.sh # Linux/Mac # 或 setup-env.bat # Windows # 3. 启动服务 docker-compose up -d When the README contains no runnable command, this article does not invent one. Open its "🌟 项目亮点" section and confirm system dependencies, default ports, and first-run initialization before using a public server.