Gaggiuino MCP Server

Gaggiuino MCP Server is a lightweight bridge that exposes the telemetry and control surface of an open‑source espresso machine controller (Gaggiuino) to any AI assistant that understands the Model Context Protocol. By turning the machine’s real‑time sensor data into a set of simple, declarative tool calls, developers can build conversational agents that monitor brewing status, retrieve shot histories, or even suggest adjustments on the fly—all without writing custom integration code.

The server solves a common pain point for makers and baristas who want to leverage AI in the kitchen: existing MCP clients expect a uniform API, but espresso controllers typically expose bespoke serial or HTTP interfaces. Gaggiuino MCP translates those low‑level signals into three high‑value tools—, , and . These tools let an assistant report whether the machine is idle, what temperature or pressure it’s currently at, and provide a full time‑series of pressure, flow, and temperature for any shot. Because the data is streamed directly from the controller, responses are fresh and can be used for real‑time diagnostics or post‑shot analysis.

Key capabilities include:

• Real‑time telemetry: Access pressure, flow, and temperature readings as they happen, enabling live dashboards or AI‑driven alerts.
• Shot history retrieval: Quickly pull the most recent shot ID or any historical shot by its identifier, making it trivial to compare batches or track consistency over time.
• Local‑network focus: Designed for home or lab environments, the server runs on a single machine connected to the espresso controller, keeping all data private and low‑latency.

Typical use cases span from a home barista’s voice‑controlled assistant that can say “How was my last shot?” to a research lab workflow where an AI system automatically logs and analyses thousands of shots per day. In a commercial setting, the same tools could feed into quality‑control dashboards or trigger maintenance alerts when pressure curves deviate from expected profiles.

Integration is straightforward for any MCP‑compliant client. A developer simply registers the server in their assistant’s configuration, and the assistant can invoke the three tools as part of a conversation or scripted workflow. The server’s minimal footprint and clear API surface mean that adding Gaggiuino telemetry to a Claude, Gemini, or other LLM‑based assistant requires only a few lines of configuration—no custom code or API keys needed.