Novita MCP Server
novita-mcp-server is a Model Context Protocol (MCP) server that provides seamless interaction with Novita AI platform resources. We recommend accessing this server through Claude Desktop, Cursor, or any other compatible MCP client.
Features
⚠️ Beta Notice:
novita-mcp-serveris currently in beta and only supports GPU instance management. Additional resource types will be supported in future releases.
Currently, novita-mcp-server enables management the resources of GPU instances product.
Supported operations are as follows:
- Cluster(/Region): List;
- Product: List;
- GPU Instance: List, Get, Create, Start, Stop, Delete, Restart;
- Template: List, Get, Create, Delete;
- Container Registry Auth: List, Create, Delete;
- Network Storage: List, Create, Update, Delete;
Installation
You can install the package using npm, or Smithery:
Using npm
bashnpm install -g @novitalabs/novita-mcp-server
Using Smithery
Visit the https://smithery.ai/server/@novitalabs/novita-mcp-server and follow the "Install" instructions to install the server.
Configuration to use novita-mcp-server
First, you need to get your Novita API key from the Novita AI Key Management.
And next, you can use the following configuration for both Claude Desktop and Cursor:
📌 Tips
For Claude Desktop, you can refer to the Claude Desktop MCP Quickstart guide to learn how to configure the MCP server.
For Cursor, you can refer to the Cursor MCP Quickstart guide to learn how to configure the MCP server.
json{ "mcpServers": { "@novitalabs/novita-mcp-server": { "command": "npx", "args": ["-y", "@novitalabs/novita-mcp-server"], "env": { "NOVITA_API_KEY": "your_api_key_here" } } } }
Examples
Here are some examples of how to use the novita-mcp-server to manage your resources with Claude Desktop or Cursor:
List clusters
txtList all the Novita clusters
List products
txtList all available Novita GPU instance products
List GPU instances
txtList all my running Novita GPU instances
Create a new GPU instance
txtCreate a new Novita GPU instance: Name: test-novita-mcp-server-01 Product: any available product GPU Number: 1 Image: A standard public PyTorch/CUDA image Container Disk: 60GB
Testing
This project uses Jest for testing. The tests are located in the src/tests directory.
You can run the tests using one of the following commands:
bashnpm test



