About Gridscale MCP
Gridscale MCP lets AI models interact with the Gridscale API through MCP, for cloud infrastructure tasks. It currently supports creating and deleting IPs, retrieving storage templates, and partially creating storage.
Key features
- 01Create IPs
- 02Delete IPs
- 03Retrieve storage templates
- 04Partial storage creation support
Use cases
- 01Creating Gridscale IPs through an AI model
- 02Deleting IPs in Gridscale
- 03Checking available storage templates
MCP support
The MCP server exposes selected Gridscale API operations as tools and resources to MCP clients.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEGridscale 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
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.