Hyperbolic MCP
H

Hyperbolic MCP

The Hyperbolic GPU MCP server is a Node.js - based tool that allows users to manage and rent GPU resources on the Hyperbolic cloud platform via an API, including functions such as viewing available GPUs, renting instances, SSH connection, and running GPU workloads.
2.5 points
7.4K

What is the Hyperbolic GPU MCP Server?

The Hyperbolic GPU MCP server is an interface connected to the Hyperbolic cloud platform, allowing users to view, rent, and manage GPU resources. It supports connecting to GPU instances via SSH and executing computing tasks.

How to use the Hyperbolic GPU MCP Server?

Users can connect to and operate the server by configuring environment variables or using the Claude for Desktop tool. An API key and an SSH private key (optional) are required for authentication.

Applicable Scenarios

Suitable for users who need to access cloud GPU resources for high - performance computing tasks such as machine learning training, deep learning model development, and scientific computing.

Main Features

GPU Resource Management
Allows users to view, rent, and terminate GPU instances, helping them manage computing resources flexibly.
SSH Connection Support
Allows users to connect to rented GPU instances via SSH to execute remote commands or transfer files.
Command - Line Interaction
Provides various commands, such as listing available GPUs, renting instances, and checking SSH status, to facilitate direct interaction with the server.
Integration with Claude for Desktop
Allows users to configure and use the server directly in Claude for Desktop, enhancing the user experience.
Advantages
Simplifies access to and management of GPU resources on the Hyperbolic cloud platform.
Supports SSH connection, enabling users to directly control GPU instances.
Easy to integrate into tools such as Claude for Desktop, improving work efficiency.
Provides detailed documentation and examples for quick start.
Limitations
Requires a valid Hyperbolic API token and an SSH key, which may be a bit challenging for beginners.
Cannot handle password - protected SSH keys. Ensure that the private key has no password.
Depends on a Hyperbolic account and sufficient balance. Recharge in advance is required.
Does not support a graphical interface and is entirely command - line - based.

How to Use

Install the Server
Clone the repository and install the dependencies. Make sure Node.js and npm/yarn are installed.
Start the Server
Run the server to start receiving and processing requests.
Configure Claude for Desktop
Add the server to the configuration of Claude for Desktop and provide the necessary environment variables.
Use the Tool
Interact with the server using the provided commands, such as listing GPUs, renting instances, and executing remote commands.

Usage Examples

Rent a GPU Instance
A user wants to rent 4 GPUs for training a deep - learning model.
Connect to a GPU Instance
A user needs to connect to a rented GPU instance via SSH to run code.
Terminate a GPU Instance
A user needs to terminate a GPU instance to save costs after completing a task.

Frequently Asked Questions

What prerequisites do I need to use the Hyperbolic GPU MCP Server?
How can I obtain a Hyperbolic API token?
Why does my SSH connection fail?
Can I use a graphical interface?
Is there a charge for renting GPUs?

Related Resources

Hyperbolic Official Documentation
The official website of the Hyperbolic platform, containing account registration, API documentation, and detailed instructions.
GitHub Repository
The source - code repository of the Hyperbolic GPU MCP server, containing the project structure and configuration instructions.
Claude for Desktop Configuration Guide
The official guide on how to configure the MCP server in Claude for Desktop.

Installation

Copy the following command to your Client for configuration
{
  "mcpServers": {
    "hyperbolic-gpu": {
      "command": "node",
      "args": ["/path/to/hyperbolic-mcp-server/build/index.js"],
      "env": {
        "HYPERBOLIC_API_TOKEN": "your-hyperbolic-api-token",
        "SSH_PRIVATE_KEY_PATH": "/path/to/your/privatekey" 
      }
    }
  }
}
Note: Your key is sensitive information, do not share it with anyone.

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