rishithakar-07/3d_agent_mcp
3.2
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3D Agent MCP - Blender Integration is a server that allows AI models to interact with Blender for 3D tasks.
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# 3D Agent MCP - Blender Integration
## šÆ Overview
A Model Context Protocol (MCP) server that enables AI models like Claude to interact with Blender for 3D modeling, scene manipulation, and rendering tasks. This agent bridges the gap between natural language instructions and complex 3D operations in Blender.
## ⨠Features
- **3D Object Creation**: Generate primitive shapes and complex meshes via natural language
- **Scene Manipulation**: Move, rotate, scale, and modify objects programmatically
- **Material & Texturing**: Apply and modify materials, textures, and shaders
- **Rendering Control**: Configure and execute renders with custom settings
- **Animation Support**: Create and control keyframe animations
- **File Operations**: Import/export various 3D formats (OBJ, FBX, GLB, etc.)
- **Python Scripting**: Execute custom Blender Python scripts through the MCP interface
## š Quick Start
### Prerequisites
- Python 3.8 or higher
- Blender 3.0+ installed on your system
- Claude Desktop or any MCP-compatible client
### Installation
1. Clone the repository:
```bash
git clone https://github.com/rishithakar-07/3d_agent_mcp.git
cd 3d_agent_mcp/blender-mcp-main
- Install dependencies:
pip install -r requirements.txt
- Configure Blender path (if needed):
# Set your Blender executable path
export BLENDER_PATH="/path/to/blender"
Running the MCP Server
python server.py
The server will start on the default MCP port and wait for connections.
š” Usage Examples
Basic Object Creation
# Request to the MCP agent:
"Create a red cube at position (2, 0, 1) with size 2"
# Agent handles:
- Creates mesh primitive
- Applies material
- Sets transform properties
Complex Scene Building
# Request:
"Build a simple room with 4 walls, a floor, and a point light"
# Agent handles:
- Multiple object creation
- Proper positioning
- Lighting setup
Rendering
# Request:
"Render the current scene at 1920x1080 with cycles engine"
# Agent handles:
- Render engine configuration
- Resolution settings
- Output file management
šļø Architecture
blender-mcp-main/
āāā server.py # Main MCP server implementation
āāā blender_ops.py # Blender operation handlers
āāā mcp_tools.py # MCP tool definitions
āāā utils/ # Utility functions
āāā requirements.txt # Python dependencies
āāā examples/ # Example scripts and scenes
š ļø MCP Tools Available
create_object
- Create 3D primitives and meshestransform_object
- Move, rotate, scale objectsapply_material
- Add and modify materialsrender_scene
- Configure and execute rendersimport_file
- Import 3D modelsexport_scene
- Export to various formatsexecute_script
- Run custom Blender Python code
š§ Configuration
Configure the MCP server by editing config.json
:
{
"blender_path": "/path/to/blender",
"default_engine": "cycles",
"output_directory": "./renders",
"max_polygon_count": 1000000
}
š Integration with Claude
Add to your Claude Desktop configuration:
{
"mcp_servers": {
"blender-3d": {
"command": "python",
"args": ["/path/to/3d_agent_mcp/blender-mcp-main/server.py"],
"description": "3D modeling and rendering with Blender"
}
}
}
šØ Use Cases
- Rapid Prototyping: Quickly create 3D mockups through conversation
- Educational Content: Generate 3D visualizations for learning
- Asset Generation: Create 3D assets for games or applications
- Architectural Visualization: Build and render architectural scenes
- Animation Creation: Develop simple animations through natural language
- Batch Processing: Automate repetitive 3D tasks
š¤ Contributing
Contributions are welcome! Please feel free to submit pull requests or open issues for bugs and feature requests.
š¤ Author
Rishi Thakar
- GitHub: @rishithakar-07
š Acknowledgments
- Built using the Model Context Protocol (MCP) specification
- Powered by Blender's Python API
- Inspired by the need for accessible 3D content creation
- Used Exising Blender MCP Repo
This project demonstrates the integration of AI language models with professional 3D software, showcasing the potential for natural language-driven 3D content creation.