MCP Servers

模型上下文协议服务器、框架、SDK 和模板的综合目录。

M
Meshy MCP Server
作者 @gwizards

MCP server for Meshy.ai 3D model generation API

创建于 3/15/2026
更新于 about 3 hours ago
Repository documentation and setup instructions

Meshy MCP Server

An MCP (Model Context Protocol) server that gives AI assistants the power to generate 3D models, textures, and images through the Meshy.ai API.

Ask Claude to "create a 3D model of a medieval castle" and it will handle the entire workflow — generating previews, refining models, remeshing for export, and more — all through natural conversation.

Features

| Feature | Description | |---------|-------------| | Text to 3D | Generate 3D models from text descriptions with a preview + refine workflow | | Image to 3D | Create 3D models from a single reference image | | Multi-Image to 3D | Generate 3D from up to 4 reference images for better accuracy | | Remesh & Export | Re-mesh models and export in glb, fbx, obj, usdz, blend, or stl | | Retexture | Apply new textures to existing 3D models via text or image style reference | | Text to Image | Generate images from text (useful as input for image-to-3D pipelines) | | Rigging | Auto-rig humanoid 3D models for animation (GLB format, max 300k faces) | | Animation | Apply 500+ animations to rigged models from the Meshy animation library | | Image to Image | Transform and edit images using reference images and text prompts | | Balance | Check your Meshy credit balance |

Prerequisites

  • Node.js 18+ (uses native fetch)
  • Meshy API Key — sign up at meshy.ai and get your key from API Settings

Installation

From npm

npm install -g meshy-mcp-server

From source

git clone https://github.com/gwizards/meshy-mcp-server.git
cd meshy-mcp-server
npm install
npm run build

Configuration

Claude Code

Add to your project .mcp.json or ~/.claude/settings.json:

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

Claude Desktop

Add to your config file:

  • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
  • Windows: %APPDATA%\Claude\claude_desktop_config.json
{
  "mcpServers": {
    "meshy": {
      "command": "node",
      "args": ["/absolute/path/to/meshy-mcp-server/dist/index.js"],
      "env": {
        "MESHY_API_KEY": "your-api-key-here"
      }
    }
  }
}

Usage

Text-to-3D Workflow

The most common workflow uses wait_for_task to handle polling automatically:

  1. Generate previewtext_to_3d_create with mode: "preview" and your prompt
  2. Wait for completionwait_for_task with task_type: "text_to_3d" — returns download URLs when done
  3. Refine the modeltext_to_3d_create with mode: "refine" and the preview_task_id
  4. Wait againwait_for_task returns the final model with download URLs
  5. Export (optional) — remesh_create then wait_for_task

Image-to-3D Pipeline

Combine text-to-image with image-to-3D for a fully text-driven pipeline:

  1. Generate reference imagetext_to_image_create with your description
  2. Wait for imagewait_for_task with task_type: "text_to_image"
  3. Generate 3D from imageimage_to_3d_create with the resulting image URL
  4. Wait for 3D modelwait_for_task with task_type: "image_to_3d"

Rigging & Animation Pipeline

  1. Generate 3D model — any _create tool
  2. Rig the modelrigging_create with the task ID or model URL
  3. Wait for riggingwait_for_task with task_type: "rigging"
  4. Animateanimation_create with the rigging task ID and action ID
  5. Wait for animationwait_for_task with task_type: "animation"

Example Prompts

Once configured, you can ask Claude things like:

  • "Generate a 3D model of a low-poly fox"
  • "Create a medieval sword with PBR textures and export as FBX"
  • "Take this image and turn it into a 3D model"
  • "Retexture my model with a cyberpunk style"
  • "Rig this model and apply a walking animation"
  • "Transform this photo into a different style"
  • "How many credits do I have left?"

Available Tools

Text to 3D

| Tool | Description | |------|-------------| | text_to_3d_create | Generate 3D from text (preview or refine mode) | | text_to_3d_get | Check task status and retrieve results | | text_to_3d_list | List tasks with pagination | | text_to_3d_delete | Delete a task |

Image to 3D

| Tool | Description | |------|-------------| | image_to_3d_create | Generate 3D from a single image URL or base64 data URI | | image_to_3d_get | Check task status | | image_to_3d_list | List tasks | | image_to_3d_delete | Delete a task |

Multi-Image to 3D

| Tool | Description | |------|-------------| | multi_image_to_3d_create | Generate 3D from 1-4 reference images | | multi_image_to_3d_get | Check task status | | multi_image_to_3d_list | List tasks | | multi_image_to_3d_delete | Delete a task |

Remesh & Export

| Tool | Description | |------|-------------| | remesh_create | Remesh and export to glb, fbx, obj, usdz, blend, or stl | | remesh_get | Check task status | | remesh_list | List tasks | | remesh_delete | Delete a task |

Retexture

| Tool | Description | |------|-------------| | retexture_create | Apply new textures via text prompt or style image | | retexture_get | Check task status | | retexture_list | List tasks | | retexture_delete | Delete a task |

Text to Image

| Tool | Description | |------|-------------| | text_to_image_create | Generate images (models: nano-banana, nano-banana-pro) | | text_to_image_get | Check task status | | text_to_image_list | List tasks | | text_to_image_delete | Delete a task |

Rigging

| Tool | Description | |------|-------------| | rigging_create | Auto-rig a humanoid 3D model (GLB, max 300k faces) | | rigging_get | Check rigging task status | | rigging_delete | Delete a rigging task |

Animation

| Tool | Description | |------|-------------| | animation_create | Apply animation to a rigged model (500+ actions) | | animation_get | Check animation task status | | animation_delete | Delete an animation task |

Image to Image

| Tool | Description | |------|-------------| | image_to_image_create | Transform images with text prompts and references | | image_to_image_get | Check task status | | image_to_image_list | List tasks | | image_to_image_delete | Delete a task |

Workflow Helpers

| Tool | Description | |------|-------------| | wait_for_task | Poll any task until completion — replaces manual _get loops |

Account

| Tool | Description | |------|-------------| | get_balance | Check your Meshy credit balance |

Task Lifecycle

All generation tasks follow the same async pattern:

CREATE → PENDING → IN_PROGRESS → SUCCEEDED / FAILED
  • PENDING — Task is queued
  • IN_PROGRESS — Generation is running (progress field shows 0-100%)
  • SUCCEEDED — Complete. model_urls, texture_urls, and thumbnail_url are available
  • FAILED — Check task_error.message for details
  • CANCELED — Task was canceled

Error Handling

All tools return structured errors via MCP's isError flag instead of raw exceptions:

  • Validation errors — Missing required fields (e.g., prompt in preview mode) return clear messages
  • API errors — HTTP errors from Meshy include status code and response body
  • Network errors — Transient failures (429, 500, 502, 503, 504) are retried automatically with exponential backoff (1s, 2s, 4s — max 3 retries). 429 responses respect the Retry-After header

Project Structure

meshy-mcp-server/
├── src/
│   ├── index.ts              # MCP server setup, 36 tool definitions, validation
│   └── meshy-client.ts       # Meshy API client with retry logic
├── tests/
│   ├── meshy-client.test.ts  # Client retry/error tests
│   └── tools.test.ts         # End-to-end MCP tool tests
├── .github/workflows/ci.yml  # GitHub Actions CI (Node 18/20/22)
├── dist/                     # Compiled output (generated by npm run build)
├── CLAUDE.md                 # Project conventions for AI assistants
├── package.json
├── tsconfig.json
├── vitest.config.ts
└── README.md

Tech Stack

| Component | Technology | |-----------|-----------| | Language | TypeScript (strict mode) | | Runtime | Node.js 18+ | | MCP SDK | @modelcontextprotocol/sdk ^1.27.1 | | Validation | Zod ^4.3.6 | | Testing | Vitest | | Transport | stdio | | Module System | ES modules | | Build | tsc to ES2022 |

Development

npm run dev    # Run with tsx (auto-reload)
npm run build  # Compile TypeScript
npm test       # Run test suite
npm start      # Run compiled version

API Reference

This server wraps the Meshy API v1/v2. Key endpoints used:

| Meshy API | Server Tools | |-----------|-------------| | POST /openapi/v2/text-to-3d | text_to_3d_create | | POST /openapi/v1/image-to-3d | image_to_3d_create | | POST /openapi/v1/multi-image-to-3d | multi_image_to_3d_create | | POST /openapi/v1/remesh | remesh_create | | POST /openapi/v1/retexture | retexture_create | | POST /openapi/v1/text-to-image | text_to_image_create | | POST /openapi/v1/rigging | rigging_create | | POST /openapi/v1/animations | animation_create | | POST /openapi/v1/image-to-image | image_to_image_create | | GET /openapi/v1/balance | get_balance |

Credits

Created by Mr Polti from Wizards.

License

MIT

快速设置
此服务器的安装指南

安装包 (如果需要)

npx @modelcontextprotocol/server-meshy-mcp-server

Cursor 配置 (mcp.json)

{ "mcpServers": { "gwizards-meshy-mcp-server": { "command": "npx", "args": [ "gwizards-meshy-mcp-server" ] } } }