Context3D - AI-Powered 3D Model Generation with MCP

<div align="center"> <h3>Generating production-ready 3D models and PBR textures from text and images with MCP Integration</h3> </div>

---

🔍 Overview

This repository contains the Context3D MCP Server, a specialized component that integrates the advanced Context3D AI-powered 3D asset generation capabilities with the Model Context Protocol (MCP). While the core Context3D services handle the complex process of generating production-ready 3D models from text prompts or reference images using proprietary diffusion models and extensive datasets, this MCP server provides a standardized interface to access these capabilities via MCP.

The core Context3D services leverage a multi-stage pipeline for 3D asset generation, including input processing, feature extraction, latent space modeling, and asset generation components. This results in high-quality, CG-friendly assets compatible with Unity, Unreal Engine, Maya, and other industry-standard platforms.

This repository's focus is the MCP server, which includes a secure authentication layer that can use blockchain technology to verify users based on their token holdings before allowing access to the underlying Context3D generation services.

Key Features of the Context3D Platform:

• Text-to-3D: Generate detailed 3D models from text descriptions
• Image-to-3D: Convert reference images into 3D models with matching textures
• Hyper-realistic PBR textures: Auto-generated diffuse, normal, roughness, and metallic maps
• Production-ready output: Optimized topology and UV mapping for immediate use
• Multi-platform compatibility: Export to common formats (.fbx, .obj, .gltf, .usd)
• Facial specialization: Advanced capabilities for human facial asset generation

Key Features of this MCP Server:

• MCP Integration: Full compatibility with the Model Context Protocol for accessing Context3D services.
• Blockchain Authentication: Secure access control based on token holdings for using the Context3D services via MCP.
• File Management Tools: Built-in MCP tools for managing generated assets.
• Customization Options: MCP interface for controlling core Context3D model generation parameters.

---

🏗️ Technical Architecture

This repository focuses on the MCP Server component, which interacts with the core Context3D Cloud Service.

Core Context3D Cloud Service Pipeline (Detailed in plant.md)

The core Context3D Cloud Service utilizes a multi-stage pipeline:

graph TD
    A[Context3D Architecture] --> B[Input Processing]
    B --> C[Feature Extraction]
    C --> D[Latent Space Modeling]
    D --> E[Asset Generation]

    subgraph "Input Processing"
        B1[Text Input Processing]
        B2[Image Input Processing]
        B3[Parameter Config]
        B1 <--> B2
        B2 <--> B3
    end

    subgraph "Feature Extraction"
        C1[Semantic Encoder]
        C2[Visual Encoder]
        C3[Style Encoder]
        C1 <--> C2
        C2 <--> C3
    end

    subgraph "Latent Space Modeling"
        D1[3D Diffusion Model]
        D2[Multi-view Consistency]
        D3[Geometry Refinement]
        D1 <--> D2
        D2 <--> D3
    end

    subgraph "Asset Generation"
        E1[Mesh Generation]
        E2[Texture Generation]
        E3[UV Mapping]
        E4[Topology Optimization]
        E5[PBR Material Creation]
        E6[Export Pipeline]
        E1 <--> E2
        E2 <--> E3
        E1 <--> E4
        E2 <--> E5
        E3 <--> E6
        E4 <--> E5
        E5 <--> E6
    end

    B --> B1
    B --> B2
    B --> B3
    C --> C1
    C --> C2
    C --> C3
    D --> D1
    D --> D2
    D --> D3
    E --> E1
    E --> E2
    E --> E3
    E --> E4
    E --> E5
    E --> E6

Note: This diagram represents the core Context3D Cloud Service pipeline, not the MCP Server in this repository.

MCP Server Communication Flow

This diagram illustrates the communication flow between an MCP client and the server, including interaction with the core Context3D Cloud Service:

sequenceDiagram
    participant Client as MCP Client
    participant Server as Context3D MCP Server
    participant CloudService as Context3D Cloud Service

    Client->>+Server: Execute generate_3d_model tool
    Server->>Server: Perform Authentication/Verification (if enabled)
    Server->>+CloudService: Forward generation request to Cloud Service API Gateway
    CloudService->>CloudService: Process Generation (Input, Feature, Latent, Asset stages)
    CloudService-->>-Server: Return task UUID and status
    Server-->>-Client: Return confirmation with task UUID

    alt With Blockchain Authentication
        Client->>+Server: Execute generate_rodin_model_with_auth tool
        Server->>Server: Verify Ethereum signature & token balance
        Server->>+CloudService: Forward authenticated request to Cloud Service API Gateway
        CloudService->>CloudService: Process Authenticated Generation
        CloudService-->>-Server: Return authenticated response
        Server-->>-Client: Return confirmation with task UUID
    end

    Client->>+Server: Execute download_rodin_results_with_auth tool
    Server->>Server: Verify Ethereum signature & token balance
    Server->>+CloudService: Request download URLs from Cloud Service API Gateway
    CloudService->>CloudService: Retrieve Download URLs
    CloudService-->>-Server: Return authenticated URLs
    Server-->>-Client: Return download links

Authentication Flow (within MCP Server)

The blockchain authentication process within the MCP Server works as follows:

graph TD
    A[User Signs Message] --> B[Generate Ethereum Signature]
    B --> C[Send Request with x-api-key Header to MCP Server]
    C --> D[MCP Server Verifies Signature]
    D --> E[Recover Ethereum Address]
    E --> F[Check Token Balance on Blockchain]
    F --> G{Sufficient Balance?}
    G -- Yes --> H[Proceed with Request to Cloud Service]
    G -- No --> I[Return Error: Insufficient Tokens]

---

MCP Integration Guide

Adding the MCP Server to Claude Desktop

Follow these steps to integrate the Context3D MCP server with Claude Desktop:

1. Install Claude Desktop:

   • Download the latest version of Claude Desktop from the official website (https://claude.ai/download)
   • Follow the installation prompts for your operating system (Windows, macOS)
   • Complete the installation and launch Claude Desktop
   • Sign in with your Anthropic account credentials if prompted

2. Configure Claude Desktop:

   • Install Node.js (version 16 or higher) from https://nodejs.org
   • Clone the Context3D MCP server repository:

     git clone https://github.com/Context3D/context3d-model-mcp-server
     cd context3d-model-mcp-server
     

   • Install dependencies using your preferred package manager:

     npm install
     # or
     pnpm install
     # or
     yarn install
     

   • Build the MCP server:

     pnpm build
     

   • Create or update the Claude configuration file. On Windows, this is typically located at %APPDATA%\Claude\claude_desktop_config.json. On macOS, it's at ~/Library/Application Support/Claude/claude_desktop_config.json.
   • Add the following JSON configuration, making sure to replace the path with your actual build directory path:

     {
       "mcpServers": {
         "filesystem": {
           "command": "node",
           "args": [
             "/full/path/to/context3d-model-mcp-server/build/index.js"
           ],
           "env": {
             "SAVE_TO_DESKTOP": "true"
           }
         }
       }
     }
     

   • Save the configuration file and restart Claude Desktop
   • Verify the MCP server is running by checking for the Context3D tools in the tools panel

3. Using the Server:

• https://x.com/Context3D/status/1922998936219873558

---

<div align="center"> <p>© 2025 Context3D AI | <a href="https://context3d.ai">https://context3d.ai</a></p> </div>