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� Update README to reflect main branch workflow and enhanced MCP integration details

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  ## 🚀 About
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- Agent2Robot is an intelligent design assistant that leverages AI to create optimized vehicle designs for various applications. Built specifically for the MCP Hackathon 2024, this tool demonstrates the power of AI-assisted engineering and design automation.
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  ## 🎯 Features
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  1. Select your vehicle type from the dropdown
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  2. Describe your design requirements and specifications
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- 3. Click "Generate Design" to create optimized specifications
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  4. Review the detailed design report and technical specifications
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  ## 🏆 MCP Hackathon Integration
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- This project showcases how AI can be integrated into engineering workflows to:
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- - Automate design specification generation
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- - Optimize performance parameters
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- - Generate comprehensive technical documentation
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- - Accelerate the design-to-deployment pipeline
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  ## 🔧 Technical Implementation
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  - **Framework**: Gradio for interactive interface
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- - **AI Processing**: Advanced algorithm simulation
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- - **Output Formats**: Human-readable reports + JSON specifications
 
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  - **Deployment**: HuggingFace Spaces compatible
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  Built with ❤️ for MCP Hackathon 2024
 
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  ## 🚀 About
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+ Agent2Robot is an intelligent design assistant that leverages AI to create optimized vehicle designs for various applications. Built specifically for the MCP Hackathon 2024, this tool demonstrates the power of AI-assisted engineering and design automation with **Model Context Protocol integration**.
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  ## 🎯 Features
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  1. Select your vehicle type from the dropdown
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  2. Describe your design requirements and specifications
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+ 3. Click "Generate Design with MCP" to create optimized specifications
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  4. Review the detailed design report and technical specifications
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  ## 🏆 MCP Hackathon Integration
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+ This project showcases how **Model Context Protocol (MCP)** can be integrated into engineering workflows to:
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+ - Automate design specification generation through MCP server communication
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+ - Optimize performance parameters using context-aware AI
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+ - Generate comprehensive technical documentation with MCP validation
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+ - Accelerate the design-to-deployment pipeline through modular architecture
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  ## 🔧 Technical Implementation
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  - **Framework**: Gradio for interactive interface
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+ - **MCP Integration**: `mcp_client.py` for server communication
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+ - **Design Engine**: `design_tools.py` with MCP-enhanced processing
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+ - **Architecture**: Clean modular structure following MCP best practices
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  - **Deployment**: HuggingFace Spaces compatible
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+ ## 📂 Repository Structure
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+ ```
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+ ├── app.py # Main Gradio interface
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+ ├── mcp_client.py # MCP server communication
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+ ├── design_tools.py # Core design functionality
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+ ├── requirements.txt # Dependencies
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+ └── backup/ # Development files
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+ ```
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+ **Development Branch**: `main` (primary development branch)
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  Built with ❤️ for MCP Hackathon 2024