Meshy Ai Mcp Server
БесплатноПоддерживаетсяA Model Context Protocol server that wraps the Meshy AI API with TypeScript and Node.js tools, including rigging and animation endpoints.
Описание
A Model Context Protocol server that wraps the Meshy AI API with TypeScript and Node.js tools, including rigging and animation endpoints.
README
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:
Clone the repository:
git clone <repository-url> cd meshy-ai-mcp-serverInstall dependencies:
npm installBuild the project:
npm run buildConfigure your MCP Client:
Add the following to your MCP client configuration (e.g.,
claude_desktop_config.jsonor 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.
- Get your API key from the Meshy Dashboard.
- Set the
MESHY_API_KEYenvironment 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:300000aka 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
Установить Meshy Ai Mcp Server в Claude Desktop, Claude Code, Cursor
unyly install meshy-ai-mcp-serverСтавит в Claude Desktop, Claude Code, Cursor и VS Code — сам разбирается с npx, uvx и сборкой из исходников.
Впервые? Поставь CLI: curl -fsSL https://unyly.org/install | sh
Или настроить вручную
Выполни в терминале:
claude mcp add meshy-ai-mcp-server --env MESHY_API_KEY="" -- npx -y meshy-ai-mcp-serverFAQ
Meshy Ai Mcp Server MCP бесплатный?
Да, Meshy Ai Mcp Server MCP бесплатный — установка в пару кликов через Unyly без оплаты.
Нужен ли API-ключ для Meshy Ai Mcp Server?
Да, требуются переменные окружения: MESHY_API_KEY. Unyly подставит их в конфиг при установке.
Meshy Ai Mcp Server — hosted или self-hosted?
Self-hosted: сервер запускается локально на твоей машине командой из раздела установки.
Как установить Meshy Ai Mcp Server в Claude Desktop, Claude Code или Cursor?
Открой Meshy Ai Mcp Server на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.
Похожие MCP
Fetch
Web content fetching and conversion for efficient LLM usage.
AWS KB Retrieval
Retrieval from AWS Knowledge Base using Bedrock Agent Runtime.
автор: modelcontextprotocolSpring AI MCP Server
Provides auto-configuration for setting up an MCP server in Spring Boot applications.
llm-analysis-assistant
A very streamlined mcp client that supports calling and monitoring stdio/sse/streamableHttp, and can also view request responses through the /logs page. It also
автор: xuzexin-hzCompare Meshy Ai Mcp Server with
Не уверен что выбрать?
Найди свой стек за 60 секунд
Автор?
Embed-бейдж для README
Похожее
Все в категории ai
