</>MCP Agents Market
MCP Server

lanhu-mcp

by dsphper2.3kPythonUpdated 2026-09-02

⚡ 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

Claude CodeClaude DesktopCursorWindsurfCline

Lanhu MCP Server is a Model Context Protocol server that integrates AI development tools with the Lanhu design collaboration platform. It enables AI assistants like Cursor, Windsurf, and Claude Code to automatically extract and analyze Axure prototypes, download UI design assets and slices, and share team knowledge through a collaborative message board. The server provides intelligent requirement analysis with three modes (development, testing, exploration), achieving >95% accuracy, and supports semantic naming for design assets. It bridges the gap between design specifications and AI-assisted development by making design documents and prototypes directly accessible to AI coding assistants.

Key Features

Intelligent requirement analysis with three perspectives: development (detailed field rules, business logic), testing (test scenarios, edge cases), and exploration (core features, dependencies)
Automatic Axure prototype extraction and analysis with four-stage workflow: global scan, grouped analysis, reverse verification, and deliverable generation
UI design support including batch design image download, detailed parameter extraction (dimensions, spacing, colors, fonts), and automatic HTML+CSS code generation from design schemas
Smart slice extraction with semantic file naming based on layer paths and automatic project type detection (React/Vue/Flutter)
Team collaboration message board with five message types (normal, task, question, urgent, knowledge) for sharing AI analysis results across team members
Intelligent version-based caching with incremental updates and concurrent processing for improved performance
Feishu (Lark) webhook integration for @mention notifications and team transparency tracking
Collaborator tracking to record which team members' AI assistants have accessed specific requirements

Use Cases

  • 01Automatically analyze Axure prototypes to generate detailed development requirements, test cases, or review documents without manual parsing
  • 02Download design assets and slices from Lanhu with semantic naming for direct use in front-end development projects
  • 03Share requirement analysis results and development insights across team AI assistants to eliminate duplicate work
  • 04Enable testing engineers' AI assistants to access backend developers' requirement analysis without re-reading documentation
  • 05Extract precise design parameters (spacing, colors, font sizes) and reference HTML+CSS code for pixel-perfect UI implementation
  • 06Track team collaboration by recording which developers' AI assistants have reviewed specific requirements or designs

Related MCP Servers

View more

markitdown

Python tool for converting files and office documents to Markdown.

MCP Server187.8k

firecrawl

The context API to search, scrape, and interact with the web at scale. 🔥

MCP Server187.2k

prompts.chat

f.k.a. Awesome ChatGPT Prompts. Share, discover, and collect prompts from the community. Free and open source — self-host for your organization with complete privacy.

MCP Server171.7k

langflow

Langflow is a powerful tool for building and deploying AI-powered agents and workflows.

MCP Server155.4k

lanhu-mcp — FAQ

What is Lanhu MCP Server and what does it do?+

Lanhu MCP Server is a Model Context Protocol server that connects AI development tools (Cursor, Windsurf, Claude Code, etc.) to the Lanhu design collaboration platform. It enables AI assistants to automatically extract Axure prototypes, analyze requirements, download UI designs and slices, and share knowledge across team members through a unified message board.

How do I install and configure Lanhu MCP Server?+

Clone the repository and run the setup script (setup-env.sh or easy-install.sh) which will guide you through obtaining your Lanhu cookie and configuring the environment. You can deploy via Docker (docker-compose up -d) or run from source (python lanhu_mcp_server.py). The server runs on http://localhost:8000/mcp by default.

Which AI clients work with this MCP server?+

It works with any MCP-compatible AI development tool including Cursor, Windsurf, Claude Code, Claude Desktop, Cline, OpenClaw, ClawBot, Trae, and Tongyi Lingma (通义灵码). Configuration examples are provided for both HTTP-based and stdio-based connections.

Do I need a Lanhu account or API key?+

Yes, you need a valid Lanhu account and must extract your authentication cookie from a logged-in browser session. The cookie is required to access Lanhu's web interface for extracting prototypes and design assets. No separate API key is needed; authentication uses the LANHU_COOKIE environment variable.

Is Lanhu MCP Server free to use?+

Yes, the MCP server itself is free and open-source under the MIT license. However, you need access to the Lanhu platform (which may have its own pricing) and must use AI models with vision capabilities (Claude, GPT, Gemini, Kimi, Qwen, or DeepSeek) which may incur their own costs.

What AI model capabilities are required?+

The server requires AI models with vision/image recognition capabilities to analyze design screenshots and prototypes. Supported models include Claude, GPT, Gemini, Kimi, Qwen, and DeepSeek. Pure text models like GPT-3.5 or Claude Instant are not supported.

How do I install lanhu-mcp?+

Open the source repository on GitHub and follow its README. lanhu-mcp is a mcp server — MCP Agents Market links you directly to the official repo.

Is lanhu-mcp free?+

lanhu-mcp is an open-source project hosted on GitHub. Check the repository for its license and any usage requirements.

Related searches

Design MCP ServersDeveloper Tools MCP ServersProductivity & Workflow MCP ServersBest SkillsBest PluginsBest AgentsTop rated listingsClaude Code toolsBrowse all categories