Meshy AI MCP Server

Name: Meshy AI MCP Server
Author: pasie15

@pasie15

关于 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.

基本信息

分类

其他

运行时

python

传输方式

stdio

发布者

pasie15

配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "meshy-ai-mcp-server": {
      "command": "python",
      "args": [
        "-m",
        "venv",
        ".venv"
      ]
    }
  }
}

工具

未检测到工具

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is Meshy AI MCP Server?

Meshy AI MCP Server is a Model Context Protocol (MCP) server that provides tools for interacting with the Meshy AI API. It allows developers to generate 3D models from text prompts or images, apply textures, and remesh models, all through a standardized MCP interface compatible with AI‑assisted coding environments.

How to use Meshy AI MCP Server?

Clone the repository, set up a Python virtual environment, install the mcp package and dependencies, then add your Meshy AI API key to a .env file. Start the server with python src/server.py or with the MCP CLI (mcp run config.json). Configure the server in your editor’s MCP settings (e.g., Cline, Roo‑Cline, Cursor, VS Code) by pointing to the server script.

Key features of Meshy AI MCP Server

Generate 3D models from text prompts
Generate 3D models from images
Apply textures to 3D models using text prompts
Remesh and optimize 3D models
Stream task progress in real time
List, retrieve, and monitor tasks
Check Meshy AI account balance

Use cases of Meshy AI MCP Server

Quickly prototype 3D assets from textual descriptions
Convert reference images into full 3D models
Add or update textures on existing 3D models
Optimize 3D model geometry through remeshing
Automate 3D asset generation pipelines in AI‑powered IDEs

FAQ from Meshy AI MCP Server

What does Meshy AI MCP Server do?

It is an MCP server that exposes Meshy AI’s 3D generation, texturing, and remeshing capabilities as tools and resources usable by any MCP client, such as AI‑assisted coding editors.

What are the dependencies and runtime requirements?

Python 3.9+ is recommended, along with the mcp package and the dependencies listed in requirements.txt. A valid Meshy AI API key is required.

How do I configure and start the server?

Set the MESHY_API_KEY environment variable in a .env file. Start the server with python src/server.py or via the MCP CLI. Optionally, use mcp dev src/server.py for debugging with the MCP inspector.

Which tools does the server provide?

It offers creation tools (text‑to‑3D, image‑to‑3D, text‑to‑texture, remesh), retrieval tools (get task details), listing tools (list tasks), streaming tools (real‑time progress), and a utility tool to check account balance.

How can I stream task progress?

Use the streaming tools (e.g., stream_text_to_3d_task) to subscribe to updates for a specific task. The server supports real‑time progress via the task timeout configuration.