Content
# 🚀 MCP AI Development Assistant
> A tool to assist AI developers in intelligent requirement analysis and architecture design.
## ✨ Core Features
- **Intelligent Requirement Clarification**: Automatically identifies project types and generates targeted questions.
- **Branch-Aware Management**: Tracks dimensions such as project goals, feature design, technical preferences, and UI design.
- **Architecture Auto-Generation**: Generates technical architecture solutions based on complete requirements.
- **Persistent Storage**: Automatically saves analysis results and supports document export.
## 📁 Quick Configuration
### Old Version Configuration
1. **Clone the Code**
```bash
git clone https://github.com/jiemobasixiangcai/ai-develop-assistant.git
```
2. **Recommended Virtual Environment**
```bash
python -m venv venv
source venv/bin/activate # Unix/Linux/MacOS
venv\Scripts\activate # Windows
```
3. **Install Dependencies**
```bash
pip install -r requirements.txt
```
4. **Configuration File Location**
```
Windows: %APPDATA%\Claude\claude_desktop_config.json
macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
```
5. **Add Configuration**
```json
{
"mcpServers": {
"ai-develop-assistant": {
"command": "python",
"args": ["path/to/AIDevlopStudy.py"],
"env": {
"MCP_STORAGE_DIR": "./mcp_data"
}
}
}
}
```
6. **Restart Claude Desktop**
### New Version Configuration
#### 🔧 Core Tools
1. **start_new_project** - Start a new project
2. **create_requirement_blueprint** - Create a requirement blueprint
3. **requirement_clarifier** - Get requirement clarification prompts
4. **save_clarification_tasks** - Save clarification tasks
5. **update_branch_status** - Update branch status
6. **requirement_manager** - Requirement document manager
7. **check_architecture_prerequisites** - Check architecture prerequisites
8. **get_architecture_design_prompt** - Get architecture design prompts
9. **save_generated_architecture** - Save generated architecture design
10. **export_final_document** - Export the complete document
11. **view_requirements_status** - View requirement status
#### Configuration (Copy the remote direct connection to your tool, replacing MCP_STORAGE_DIR with your local directory)
```json
{
"mcpServers": {
"ai-develop-assistant": {
"command": "uvx",
"args": ["ai-develop-assistant@latest"],
"env": {
"MCP_STORAGE_DIR": "/path/to/your/storage"
}
}
}
}
```
## 🎯 Usage Process
### Basic Steps
1. **Requirement Clarification**
```
requirement_clarifier("I want to create an online education platform")
```
2. **Requirement Management**
```
requirement_manager("Target users: students and teachers", "Project overview")
```
3. **View Status**
```
view_requirements_status()
```
4. **Architecture Design**
```
architecture_designer("Architecture for the online education platform")
```
5. **Export Document**
```
export_final_document()
```
## 🚀 Getting Started
### Quick Start
1. **Configure Claude Desktop** (Refer to the configuration methods above)
2. **Restart Claude Desktop**
3. **Start Intelligent Requirement Analysis**:
```
requirement_clarifier("Describe your project idea")
```
4. **Follow AI's intelligent guidance** to gradually refine each requirement branch.
5. **Export the complete document**:
```
export_final_document()
```
### Best Practices
- 💬 **Trust AI's branch management**: Let AI guide you through all requirement branches.
- 🎯 **Clearly express preferences**: Clearly state preferences for technology choices, UI styles, etc.
- 📊 **Regularly check status**: Use `view_requirements_status` to understand progress.
- 🤖 **Empower AI appropriately**: For uncertain parts, you can say "use conventional solutions."
---
**🎯 Now you have a truly intelligent AI development assistant that remembers every detail and guides you through complete requirement analysis!**
## 💬 Communication Group
<div align="center">
<img src="./assets/qr-code.jpg" width="200" alt="Communication Group">
<br>
Communication Group
</div>
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