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Mcp_3d_relief

Mcp_3d_relief

Local
github.com/BigchxMedia & Design24Updated 78w ago

About Mcp_3d_relief

An MCP server that converts 2D images into STL-format 3D relief models for 3D printing or rendering. It offers control over model dimensions, an optional base, and depth inversion.

Key features

  1. 01Converts images into 3D relief models
  2. 02Configurable model width and thickness
  3. 03Optional base under the model
  4. 04Inverted depth relief option
  5. 05Returns file paths for generated outputs

Use cases

  1. 01Preparing photos for 3D printing as reliefs
  2. 02Generating STL models for rendering
  3. 03Adjusting size and base before export

MCP support

The project runs as an MCP server that exposes an image-to-relief tool to MCP clients. The tool accepts a local path or URL and returns paths to the depth map and STL file.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

No install method listed yet

We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.

Repository

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

MCP STL 3D Relief Generator

This project provides a MCP server that converts 2D images into 3D relief models in STL format, suitable for 3D printing or rendering.

Features

  • Convert any image to a 3D relief model
  • Control model dimensions (width, thickness)
  • Add optional base to the 3D model
  • Invert depth for different relief effects
  • Fast processing with immediate download links

Installation

Prerequisites
  • Python 3.10+
  • uv
Option 1: Local Installation
  1. Clone the repository:
git clone https://github.com/bigchx/mcp_3d_relief.git
cd mcp_3d_relief
  1. Install dependencies:
uv pip sync requirements.txt
  1. Run/Inspect the server:
mcp run server.py
mcp dev server.py

Usage

JSON Configuration
{
  "mcpServers": {
    "mcp_3d_relief": {
      "command": "uv",
      "args": ["--directory", "{fill_in_your_path_here}", "run", "server.py"]
    }
  }
}
MCP Tool Parameters
  • image_path: Local path or web URL to the input image file
  • model_width: Width of the 3D model in mm (default: 50.0)
  • model_thickness: Maximum thickness/height of the 3D model in mm (default: 5.0)
  • base_thickness: Thickness of the base in mm (default: 2.0)
  • skip_depth: Whether to use the image directly or generate a depth map (default: true)
  • invert_depth: Invert the relief (bright areas become low instead of high) (default: false)
  • detail_level: Controls the resolution of the processed image (default: 1.0). At detail_level = 1.0, the image is processed at 320px resolution, producing an STL file typically under 100MB. Higher values improve detail quality but significantly increase both processing time and STL file size. For example, doubling the detail_level can increase file size by 4x or more. Use with caution.
Response

The MCP Tool returns a JSON response with:

{
  "status": "success",
  "depth_map_path": "path/to/yourimage_depth_map.png",
  "stl_path": "path/to/yourimage.stl"
}

Where LLMs can access the generated files from this MCP server, using the provided URLs.

Command Line

You can also use the script directly from the command line to generate a relief model from an image:

python3 relief.py path/to/your/image.jpg
External Depth Map Generation

For higher quality depth maps, you can use external depth map generation services like Depth-Anything-V2. This service can generate more accurate depth maps that you can then use with this project:

  1. Visit https://huggingface.co/spaces/depth-anything/Depth-Anything-V2
  2. Upload your image to generate a depth map
  3. Download the generated depth map
  4. Use this depth map with our converter by setting skip_depth=false

This approach can provide better 3D relief models, especially for complex images.

How It Works

  1. The image is processed to create a depth map (darker pixels = lower, brighter pixels = higher)
  2. The depth map is converted to a 3D mesh with triangular facets
  3. A base is added to the bottom of the model
  4. The model is saved as an STL file

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