ai-develop-assistant

# 🚀 MCP AI Development Assistant > MCP tool to assist AI developers in intelligent requirements analysis and architecture design ## ✨ Core Features - **Intelligent Requirement Clarification**: Automatically identifies project types and generates targeted questions - **Branch-Aware Management**: Tracks project goals, functional design, technical preferences, UI design, and other dimensions - **Automatic Architecture 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 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" } } } } ``` 3. **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 complete document 11. **view_requirements_status** - View requirement status #### Configuration (Copy directly to your tools via remote connection, replace 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 Flow ### 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("Online education platform architecture") ``` 5. **Export Document** ``` export_final_document() ``` ## 🚀 Get Started ### Quick Start 1. **Configure Claude Desktop** (Refer to the configuration method above) 2. **Restart Claude Desktop** 3. **Start Intelligent Requirement Analysis**: ``` requirement_clarifier("Describe your project idea") ``` 4. **Follow AI's intelligent guidance** to gradually improve each requirement branch 5. **Export Complete Document**: ``` export_final_document() ``` ### Best Practices - 💬 **Trust AI's Branch Management**: Let AI guide you through all requirement branches - 🎯 **Clearly Express Preferences**: Clearly express preferences for technology selection, UI style, etc. - 📊 **Regularly Check Status**: Use `view_requirements_status` to understand progress - 🤖 **Appropriately Authorize AI**: For uncertain parts, you can say "use the conventional solution" --- **🎯 Now you have a truly intelligent AI development assistant that remembers every detail and guides you through a complete requirements analysis!** ## 💬 Communication Group <div align="center"> <img src="./assets/qr-code.jpg" width="200" alt="Communication Group"> <br> Communication Group </div>