Supports Angular framework for AI-driven component design and code generation, enabling automated creation of Angular components from natural language requirements
Utilizes Mermaid diagrams for visualizing the core workflow and architecture of the component design process
Manages dependencies and package installation for the Node.js-based MCP server
Supports local AI model deployment through Ollama for component design and code generation tasks
Integrates with OpenAI's GPT models for AI-driven component analysis, design, and automated code generation
Alternative package manager option for installing and managing project dependencies
Supports React framework for AI-driven component design and code generation, enabling automated creation of React components from natural language requirements
Generates fully type-safe TypeScript code for components with complete type definitions and industry best practices
Supports Vue.js framework for AI-driven component design and code generation, enabling automated creation of Vue components from natural language requirements
🚀 mcp-garendesign - AI-driven component design and code generation toolkit
From requirements to code: an intelligent automated pipeline 🎯
📋 Table of Contents
🎯 Overview
mcp-garendesign is an AI-driven component design service based on the Model Context Protocol (MCP). It focuses on intelligent design and generation of frontend components, enabling end-to-end automation from user requirements to a complete code project.
🌟 Core Value
- 🚀 Productivity: Improve development efficiency by 50%+
- 🎯 Quality: Use shared state and a shared component library
- 🔧 Maintainability: Standardized code structure and API design
- 🎨 Consistency: Unified design system and component library
🔄 Core Workflow
📝 Workflow Details
1️⃣ User Requirements 🎤
Users describe their needs in natural language. The system extracts the core requirements.
2️⃣ Requirement Analysis 🔍
Analyze and structure requirements: functional, non-functional, user stories, and business logic.
3️⃣ Decomposition 🧩
Split into manageable components, determine component types, complexity, and dependencies.
4️⃣ Component Content & API Design 🎨
Design detailed specs for each component: Props, Events, Slots, and styles.
5️⃣ IDE Code Generation ⚡
Generate code from the design: component files, type definitions, styles, tests.
6️⃣ Iterative Validation 🔄
Monitor generation status, adjust polling intervals, handle timeouts and errors.
7️⃣ Module Integration 🔗
Integrate components into full pages: layout, data flow, and state management.
8️⃣ IDE Code Integration 🚀
Produce a complete project: structure, configs, build scripts, deployment.
💡 Key Features
🎯 Intelligent Requirement Understanding
- NLP: Understand user intent
- Context awareness: Map to business scenarios
- Requirement validation: Ensure completeness
🧩 Smart Component Decomposition
- Complexity analysis: Auto-evaluate component complexity
- Dependency management: Handle component dependencies smartly
- Token optimization: Efficient AI usage
⚡ Efficient Code Generation
- Multi-framework: Vue, React, Angular
- Type safety: Full TypeScript support
- Best practices: Industry standards
🔄 Intelligent Monitoring
- Adaptive polling: Auto-adjust frequency
- Error recovery: Retry mechanisms
- Performance: Resource optimization
🎨 Design System Integration
- Component libraries: Private library integration
- Design guidelines: Unified standards
- Theming: Multiple themes
🏗️ Architecture
🚀 Getting Started
1. Install dependencies
2. Configure environment
3. Configure AI providers
Edit data/config.json
:
Supported AI providers:
- Anthropic Claude:
https://api.anthropic.com
or proxies - OpenAI GPT:
https://api.openai.com/v1
or proxies - DeepSeek:
https://api.deepseek.com
or proxies - Ollama:
http://localhost:11434
(local models)
4. Start the service
5. Use the workflow
📚 Usage Guide
MCP Tools
design_component
Design frontend components from user requirements.
query_component
Query detailed information for a component.
Basic Example
🗂️ Project Structure
🔧 Troubleshooting
Common Issues
- Configuration files not found
- Invalid API key
- Service failed to start
- Permission issues
Debug mode
🛠️ Development Guide
Add a new tool
- Create a tool file under
src/tools/
- Register it in
src/mcp-server.ts
- Update the tool handlers
Add a new resource
- Add a resource function in
src/resources/index.ts
- Register it in
src/mcp-server.ts
- Update resource handlers
📄 License
MIT License
mcp-garendesign - Make AI a powerful assistant for every engineering team 🤖
Enables AI-driven frontend component design and code generation from natural language requirements. Supports Vue, React, and Angular with intelligent component decomposition, API design, and complete project generation.
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