Gaggiuino MCP Server

@AndrewKlement

Basic information

About Gaggiuino MCP Server

Gaggiuino MCP server

Gaggiuino MCP Server config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "gaggiuino": {
      "command": "uv",
      "args": [
        "--directory",
        "/ABSOLUTE/PATH/TO/PARENT/FOLDER/gaggiuino-mcp",
        "run",
        "gaggiuino.py"
      ]
    }
  }
}

Gaggiuino MCP Server tools

Tool list not available yet

This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is gaggiuino-mcp?

gaggiuino-mcp is a lightweight Model Context Protocol (MCP) server built for Gaggiuino, the open-source espresso machine controller for the Gaggia Classic. It is designed to integrate easily with AI clients that want to display or analyze data from the Gaggiuino system in real time.

How to use gaggiuino-mcp?

Configure the server in your MCP client (e.g., Claude Desktop) using the uv command pointing to the gaggiuino.py script in the cloned repository. Alternatively, install it automatically via Smithery with npx -y @smithery/cli install @AndrewKlement/gaggiuino-mcp --client claude. The server exposes three tools: getStatus, getLatestShotId, and getShotData.

Key features of gaggiuino-mcp

Real-time access to shot telemetry
Retrieve current espresso machine status
Access the latest espresso shot ID
Fetch detailed shot data for a given ID
Designed for local network access
Lightweight and easy to set up

Use cases of gaggiuino-mcp

Analyzing latest espresso shot data with an AI assistant
Monitoring machine status (temperature, pressure) in real time
Automating shot logging and performance evaluation
Integrating espresso machine data into custom dashboards or workflows

Frequently asked questions

What does gaggiuino-mcp do?

It reads real-time data from a Gaggiuino-controlled espresso machine — including current status, latest shot ID, and full shot data — and makes it available to AI clients via the Model Context Protocol.

What are the runtime dependencies?

The server runs as a Python script using `uv`. You need Python and `uv` installed, and the repository cloned locally.

Where does the data come from and where is it stored?

Data is fetched live from the Gaggiuino system on the local network. No external cloud storage is used; all data remains within the local network.

Are there any known limits or constraints?

The README does not mention specific limits. The server is designed for local network access only, and reliable operation depends on network connectivity to the Gaggiuino controller.

What transport and authentication does it use?

It uses standard MCP stdio transport (launched as a subprocess). No authentication is described; access is restricted by network boundaries (local network).

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