Rhino 3D

🚀 Rhino MCP Server

This project aims to enable AI-assisted 3D modeling in Rhino through the MCP protocol, allowing users to create and manipulate 3D objects via AI assistants like Claude.

⚠️ Important Note

This project is currently under active development and not yet fully operational. There are issues with the Rhino plugin when creating objects.

We are actively seeking community help, especially from developers familiar with the Rhino API, C# plugins, or MCP integration.

🚀 Quick Start

This project is in the development phase. It aims to achieve AI-assisted modeling in Rhino 3D through the MCP protocol, enabling users to create and manipulate 3D objects with an AI assistant (such as Claude). However, there are still some problems, particularly the stability of the plugin during object creation.

✨ Features

1. MCP Server Implementation

• combined_mcp_server.py: The core server implementation supports the following tools:
  • geometry_tools.create_sphere: Create a sphere with a specified center and radius.
  • geometry_tools.create_box: Create a cuboid with specified dimensions.
  • geometry_tools.create_cylinder: Create a cylinder with specified parameters.
  • scene_tools.get_scene_info: Get information about the current scene.
  • scene_tools.clear_scene: Clear all objects in the scene.
  • scene_tools.create_layer: Create a new layer in the document.

2. Plugin Development

• Rhino Plugin: Responsible for interacting with Rhino. Currently, there are the following issues:
  • Object creation fails and requires further debugging and fixing.

📦 Installation

No installation steps provided in the original document.

💻 Usage Examples

No code examples provided in the original document.

📚 Documentation

System Architecture

The project structure is as follows:

1. Python Scripts:

   • combined_mcp_server.py: The main MCP server implementation.
   • diagnose_rhino_connection.py: A diagnostic tool for testing the Rhino connection status.
   • log_manager.py: Manages log files and provides analysis functions.

2. Shell Scripts:

   • server_launcher.sh: A unified startup script supporting multiple server modes.

3. Directory Structure:

   • logs/: Stores log files for all components.

Log System

The project uses a unified logging framework to record the following:

• Server logs.
• Plugin logs.
• AI workstation logs.
• Diagnostic logs.

All logs are stored in the logs/ directory by component and follow a consistent format. Log viewing, analysis, and report generation can be achieved through log_manager.py.

Development Guide

Project Structure

.
├── combined_mcp_server.py       # The main MCP server implementation.
├── diagnose_rhino_connection.py # A diagnostic tool for testing the Rhino connection status.
├── log_manager.py               # A log management tool.
└── server_launcher.sh           # A unified startup script.

Adding New Features

1. Adding New Tools:

   • Add new functional methods to combined_mcp_server.py.
   • Ensure compliance with the existing logging specifications.

2. Diagnosis and Repair:

   • Use diagnose_rhino_connection.py to test the connection status between the plugin and Rhino.
   • Fix the current object creation issues to ensure the stable operation of the plugin.

3. Log Management:

   • Update the logging framework to support new functional modules.
   • Ensure that all log outputs follow a unified format.

Troubleshooting

Common Issues

1. Connection Failure:

   • Check if there are old processes occupying ports or resources.
   • Use server_launcher.sh help to restart the relevant services.

2. Log Analysis:

   • Check the detailed logs in the logs/ directory to locate the problem.
   • Use log_manager.py report to generate an error report.

3. Plugin Debugging:

   • Enable developer mode in Rhino and check the plugin loading status.
   • Ensure that all API calls are correct.

🔧 Technical Details

The project uses a unified logging framework to record server, plugin, AI workstation, and diagnostic logs. All logs are stored in the logs/ directory by component and follow a consistent format. Log viewing, analysis, and report generation can be achieved through log_manager.py.

📄 License

This project is licensed under the MIT License. See the LICENSE file for details.