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:

Type	Name	Note	Supported	Support Wanted
Tool	create_ip		Yes
Tool	delete_ip		Yes
Tool	create_storage	Not all parameters are supported	Partially
Tool	create_server		No	Yes
Tool	create_network		No	Yes
Res	get_storage_templates		Yes

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