What is Gridscale Mcp

gridscale-mcp is an MCP Server that enables AI models to interact with the Gridscale API, facilitating infrastructure provisioning through AI tools.

Use cases

Use cases include automating cloud resource provisioning, managing infrastructure for AI applications, and integrating with LLMs for enhanced operational efficiency.

How to use

To use gridscale-mcp, build the program using ‘make build’, install it in your PATH, and run it with your Gridscale API credentials using the command: ‘gridscale-mcp --user-key --user-token ’.

Key features

Key features include seamless interaction with the Gridscale API, the ability to provision infrastructure via AI models, and compatibility with tools like 5ire for LLM integration.

Where to use

gridscale-mcp can be used in cloud computing environments, particularly for projects that require dynamic infrastructure management and automation through AI.

Gridscale MCP

This is a MCP Server which allows AI modells
to interact with the Gridscale API

You can use this with tools such as 5ire to let your LLM provision infrastructre as you wish.

[!CAUTION]
If you use this program, you are responsible for the consequences. You should only use this in an empty Gridscale project
where the AI model will not cause any harm like deleting your production database.

Features (Tools and Resources)

With this MCP server you can use the following tools and resources:

If you want to contribute, try adding one of the above missing tools or resources.

Building + Installation

To build this program you need a Go environment.

The recommended way is to use make:

make build

This will have created a binary called gridscale-mcp in the project directory.

Install

It simplifies things if you install the binary to a location in your $PATH, for example /usr/bin on Linux.

You can use make for that:

# Install
make install

# Uninstall
make uninstall

Usage

[!CAUTION]
If you use this program, you are responsible for the consequences. You should only use this in an empty Gridscale project
where the AI model will not cause any harm like deleting your production database.

Prerequisites

You need:

• To have a build of gridscale-mcp. Follow the steps in the Building section to first build the program.
• Public API credentials for the Gridscale API

Usage in an MCP client

To run this server you need two arguments:

gridscale-mcp --user-key <your-gs-user-key> --user-token <your-gs-user-token>

I recommend to use 5ire as desktop client to interact with an LLM
and this MCP server. You are responsible for setting up an LLM (for example Gemini).

In 5ire the MCP server is setup as tool like so:

{
  "name": "Gridscale",
  "key": "gridscale",
  "command": "gridscale-mcp",
  "args": [
    "--user-key",
    "...",
    "--user-token",
    "..."
  ]
}

Debugging

You can directly communicate with you MCP server as with any other API server.

The MCP Inspector is a great tool for this.

If you have Node.js installed, simply run:

make inspect