1. Conduid
  2. Developer Tools
  3. Meshy AI MCP Server
MCP server · Developer Tools

Meshy AI MCP Server

This is a Model Context Protocol (MCP) server for interacting with the Meshy AI API. It provides tools for generating 3D models from text and images, applying textures, and remeshing models.

Unclaimed last commit 9 months ago devtools
51Fair

Scored 3 days ago · breakdown

About Meshy AI MCP Server

Meshy AI MCP Server is an MCP server published by pasie15 in the Developer Tools category: this is a Model Context Protocol (MCP) server for interacting with the Meshy AI API. It provides tools for generating 3D models from text and images, applying textures, and remeshing models. It has been installed 0 times through Conduid.

The repository has 20 stars and 8 forks, with the last commit 9 months ago. Six months or more without a commit doesn't mean the server is broken, but check the open issues (0) before depending on it in production.

Install

Install
npx meshy-ai-mcp-server

This server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.

Ask AI

Ask AI about Meshy AI MCP Server

Powered by Claude · Grounded in docs

I know everything about Meshy AI MCP Server. Ask me about installation, configuration, usage, or troubleshooting.

Security checks

  • ·README presentNot checked yet.
  • ·License declaredNot checked yet.
  • ·Tests presentNot checked yet.
  • ·Dependencies pinnedNot checked yet.
  • ·No dynamic code executionNot checked yet.
  • !Scoped permissionsDoesn't declare a permission scope. Assume it can do anything its process can.

Releases

v1.2.2v1.2.2
v1.2.1v1.2.1
v1.2.0v1.2.0
v1.1.0v1.1.0

README

Meshy AI MCP Server

This is a Model Context Protocol (MCP) server that wraps the Meshy AI API. It enables MCP clients (like Claude Desktop, Cursor, Cline) to interact with Meshy's generative 3D tools directly.

Features

  • Text-to-3D: Generate 3D models from text prompts.
  • Image-to-3D: Create 3D models from reference images.
  • Multi-Image-to-3D: Create 3D models from multiple reference images.
  • Text-to-Texture: Apply textures to existing models using text prompts.
  • Retexture: Apply new textures to existing 3D models.
  • Text-to-Image: Generate images from text prompts.
  • Image-to-Image: Generate new images from input images.
  • Model Optimization: Remesh and optimize geometry.
  • Rigging: Auto-rig 3D characters for animation.
  • Animation: Apply animations to rigged characters.
  • Streaming: Real-time progress updates for long-running tasks.
  • Task Deletion: Delete tasks across all API categories.

Installation

Option 1: Run directly with npx (Recommended)

You can run the server directly using npx without installing it globally.

{
  "mcpServers": {
    "meshy-ai": {
      "command": "npx",
      "args": [
        "-y",
        "meshy-ai-mcp-server"
      ],
      "env": {
        "MESHY_API_KEY": "your_meshy_api_key_here"
      }
    }
  }
}

Option 2: Clone and Build Locally

If you want to modify the code or run it from a local source:

  1. Clone the repository:

    git clone <repository-url>
    cd meshy-ai-mcp-server
    
  2. Install dependencies:

    npm install
    
  3. Build the project:

    npm run build
    
  4. Configure your MCP Client:

    Add the following to your MCP client configuration (e.g., claude_desktop_config.json or VS Code settings):

    {
      "mcpServers": {
        "meshy-ai": {
          "command": "node",
          "args": [
            "/absolute/path/to/meshy-ai-mcp-server/dist/index.js"
          ],
          "env": {
            "MESHY_API_KEY": "your_meshy_api_key_here"
          }
        }
      }
    }
    

Configuration

You need a Meshy AI API key to use this server.

  1. Get your API key from the Meshy Dashboard.
  2. Set the MESHY_API_KEY environment variable in your MCP client configuration (as shown above).

Optional Environment Variables

  • MESHY_API_BASE: Override the API base URL (default: https://api.meshy.ai/openapi).
  • MESHY_STREAM_TIMEOUT_MS: Timeout for streaming responses in milliseconds (default: 300000 aka 5 minutes).

Troubleshooting

If your MCP client reports that the server closed during initialize, check that the client configuration passes MESHY_API_KEY into the server process. The server can start without the key so clients can inspect available tools, but Meshy API tool calls will fail until the key is configured.

Development

To run the server in development mode with auto-reloading:

# Create a .env file
echo "MESHY_API_KEY=your_key_here" > .env

# Run in dev mode
npm run dev

Available Tools

  • Text to 3D: create_text_to_3d_task, retrieve_text_to_3d_task, list_text_to_3d_tasks, stream_text_to_3d_task, delete_text_to_3d_task
  • Image to 3D: create_image_to_3d_task, retrieve_image_to_3d_task, list_image_to_3d_tasks, stream_image_to_3d_task, delete_image_to_3d_task
  • Multi-Image to 3D: create_multi_image_to_3d_task, retrieve_multi_image_to_3d_task, list_multi_image_to_3d_tasks, stream_multi_image_to_3d_task, delete_multi_image_to_3d_task
  • Texturing: create_text_to_texture_task, retrieve_text_to_texture_task, list_text_to_texture_tasks, stream_text_to_texture_task, delete_text_to_texture_task
  • Retexture: create_retexture_task, retrieve_retexture_task, list_retexture_tasks, stream_retexture_task, delete_retexture_task
  • Text to Image: create_text_to_image_task, retrieve_text_to_image_task, list_text_to_image_tasks, stream_text_to_image_task, delete_text_to_image_task
  • Image to Image: create_image_to_image_task, retrieve_image_to_image_task, list_image_to_image_tasks, stream_image_to_image_task, delete_image_to_image_task
  • Remeshing: create_remesh_task, retrieve_remesh_task, list_remesh_tasks, stream_remesh_task, delete_remesh_task
  • Rigging: create_rigging_task, retrieve_rigging_task, list_rigging_tasks, stream_rigging_task, delete_rigging_task
  • Animation: create_animation_task, retrieve_animation_task, list_animation_tasks, stream_animation_task, delete_animation_task
  • Utility: get_balance

License

MIT

README mirrored from the source repository 3 days ago. The original is authoritative.

Questions

About Meshy AI MCP Server

How do I install Meshy AI MCP Server?

Run npx meshy-ai-mcp-server, then add the server to your MCP client's configuration. Conduid has recorded 0 installs, so the command is known to work with current clients.

Is Meshy AI MCP Server safe to use with an AI agent?

Its trust score is 51 out of 100 (fair). It passes 0 of 1 static security checks; the failures are listed above. It has no ConduID identity yet, so agent calls to it are not receipted.

Is Meshy AI MCP Server still maintained?

The last commit was 9 months ago, with 0 open issues. That's long enough that you should check whether the maintainer is responding to issues before depending on it.