lanhu-mcp-codex
This server provides read-only access to Lanhu (蓝湖/BlueLake) design projects, enabling AI agents to consume design context for code restoration. Key capabilities:
lanhu_parse_url: Parses a Lanhu project, design, or detail URL to extract constituent parts —pid,tid,image_id,docType, and route fields.lanhu_list_project_images: Retrieves the full list of design boards/images from a Lanhu project (by URL,pid, ortid) in a read-only manner, without writing any files to disk.lanhu_get_design_context: Generates localcontext.mdandcontext.jsonfiles from a Lanhu URL, with optional thumbnail downloads, giving AI agents structured design context for UI code restoration. Supports focusing on a specific artboard (targetImageId/targetImageName) or a particular component/region (targetDescription/targetRegion), a custom output directory, and toggling image downloads. Output is stored in.lanhu-mcp.local/runs/{timestamp}-{pidShort}/.
The server is strictly read-only and does not modify any data on the Lanhu platform.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@lanhu-mcp-codexgenerate design context from Lanhu link https://lanhuapp.com/pid/123"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
lanhu-mcp-codex
蓝湖只读 MCP 服务,用于把蓝湖项目/设计稿链接转换成 Codex 或其他 AI Agent 可消费的设计上下文。
项目第一原则:辅助 Codex 基于蓝湖设计文稿进行代码还原。
当前能力
解析蓝湖链接中的
pid、tid、image_id、docType等参数。通过蓝湖 Web API 只读获取项目画板列表。
下载可访问的画板缩略图。
生成本地
context.md和context.json。提供 stdio MCP 工具,适合 Codex 本地接入。
Related MCP server: pymupdf4llm-mcp
快速开始
npm install
npm run build
npm test设置蓝湖 Cookie:
LANHU_COOKIE="从蓝湖请求中复制的 Cookie 请求头"启动 MCP:
node dist/index.jsCodex MCP 配置示例
推荐把 LANHU_COOKIE 设置为 Windows 用户环境变量,不把 Cookie 明文写入 config.toml:
setx LANHU_COOKIE "从蓝湖请求中复制的 Cookie 请求头"将路径替换为本机仓库绝对路径。下面的 wrapper 会在 MCP 启动时从用户/系统环境变量读取 LANHU_COOKIE:
[mcp_servers.lanhu-readonly]
type = "stdio"
cwd = "C:\\path\\to\\lanhu-mcp-codex"
command = "powershell"
args = ["-NoLogo", "-NoProfile", "-ExecutionPolicy", "Bypass", "-Command", "$cookie = [Environment]::GetEnvironmentVariable('LANHU_COOKIE', 'User'); if ([string]::IsNullOrWhiteSpace($cookie)) { $cookie = [Environment]::GetEnvironmentVariable('LANHU_COOKIE', 'Machine') }; $env:LANHU_COOKIE = $cookie; & node dist/index.js"]修改 MCP 配置或用户环境变量后,需要重启 Codex 桌面端。
MCP 工具
lanhu_parse_url:解析蓝湖链接。lanhu_list_project_images:读取项目画板列表,不落盘。lanhu_get_design_context:生成本地上下文与缩略图资源,支持目标画板和组件级还原聚焦。
lanhu_get_design_context 常用参数:
url:蓝湖项目、画板或详情链接。includeImages:是否下载缩略图,默认true。targetImageId/targetImageName:显式指定要还原的目标画板。targetDescription:描述只需要实现的局部组件。targetRegion:描述局部组件区域,包含x/y/width/height/coordinateSpace。
生成的 context 会包含 schema.schemaVersion、restoration.targetFocus、本地图片真实像素尺寸、API 到像素倍率和业务落地检查清单。更新代码并重新 npm run build 后,需要重启 Codex/MCP 才能让长进程读取最新构建。
默认产物目录:
.lanhu-mcp.local/runs/{timestamp}-{pidShort}/
├── context.json
├── context.md
└── images/多 Agent 协作入口
新用户或新 AI Agent 接手前,按顺序阅读:
README.mdAGENTS.mddocs/PROJECT.mddocs/STATUS.mddocs/ROADMAP.mddocs/HANDOFF.mddocs/DECISIONS.mddocs/CODE_STANDARDS.md
每次阶段性开发结束前,需要:
跑
npm run typecheck、npm test、npm run build。更新
docs/STATUS.md和docs/HANDOFF.md。如果变更影响路线或架构,更新
docs/ROADMAP.md或docs/DECISIONS.md。如果出现新的建议,先按项目第一原则评估;不冲突且能提升蓝湖读取、设计理解、资源准备、还原质量或协作效率的建议,写入对应文档。
使用中文 Conventional Commits 提交,例如
feat: 增强蓝湖画板规范化逻辑。
已有本地仓库恢复工作时:
git status --short --branch
git pull --ff-only
npm install
npm run typecheck
npm test
npm run build拉取后重新阅读 AGENTS.md、docs/STATUS.md、docs/HANDOFF.md、docs/ROADMAP.md、docs/DECISIONS.md,再继续开发。
安全边界
不提交真实 Cookie、Token、账号信息。
不打印、不保存、不写入
LANHU_COOKIE。.lanhu-mcp.local/、dist/、node_modules/、work/、outputs/不提交。V1 不做任何蓝湖写操作。
Maintenance
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