Gaggimate MCP Server
Gaggimate espresso machine control through nine specialized tools and eight resources.
Data last scanned 2 days ago · Reviewed 2 days ago
Overview
The Gaggimate MCP Server transforms AI models into interactive barista coaches by providing direct control over your Gaggimate espresso machine. It enables AI agents to read shot history, monitor pressure and temperature curves, manage brewing profiles, and log tasting feedback without manual input. Beyond machine control, the server acts as an intelligent assistant for your coffee routine. It tracks grind settings, maintains brewing journals for different coffee beans, and provides access to structured knowledge files on extraction theory and espresso diagnostics.
Our verdict
This repository holds a high risk security score of 35/100, primarily because the authentication and OAuth implementations have not yet been reviewed for safety. Given that it is a community-maintained project rather than an official vendor release, users should exercise caution before granting this server access to their hardware. It is best suited for hobbyists comfortable with experimental software who understand the risks of connecting AI tools to physical equipment.
- Zero direct dependencies reduce potential supply-chain vulnerabilities
- Provides nine distinct tools for granular hardware interaction
- Includes comprehensive documentation on the dialing flow
- MIT license permits modification and personal use
- High risk score due to unreviewed OAuth and authentication
- Lacks official maintenance by the Gaggimate hardware manufacturer
- Read-only capabilities remain unverified for security purposes
Tools
| Tool | Description | Risk |
|---|---|---|
| manage_profile | Create, update, and list brewing profiles directly on your device. | medium |
| manage_coffee | Create and update coffee tracking files with brewing journal. | medium |
| manage_user_setup | Store and retrieve equipment and preferences. | medium |
| manage_grind_map | Track successful grind settings across coffees. | medium |
| manage_brewing_insights | Accumulate cross-coffee patterns and learnings. | medium |
| analyze_shot | Compute puck resistance, channeling risk scoring, temperature deviation, and other shot diagnostics. | low |
| read_shot_data | Access temperature curves, pressure readings, flow rates, and extraction timing. | low |
| list_recent_shots | Browse shot history with filtering. | low |
| diagnose_connection | Automated connection troubleshooting. | low |
| manage_shot_notes | Record ratings (0-5 stars), tasting notes, and brewing parameters for any shot. | medium |
Compatibility
| Client | Local | Docker | Remote | Read-only |
|---|---|---|---|---|
| ChatGPT | ||||
| Claude Desktop | ||||
| Cursor | ||||
| VS Code | ||||
| Windsurf |
Frequently asked questions
›What functionality does this MCP server provide?
The server offers nine tools and eight resources that enable your AI agent to read shot history, manage Gaggimate brewing profiles, record tasting feedback, and diagnose espresso extraction issues.
›What is included to help the AI understand espresso preparation?
The repository contains 10 knowledge files covering topics like extraction theory, tasting vocabulary, pressure guides, bean freshness, and brewing parameters.
›Can the AI automate the creation and adjustment of brewing profiles?
Yes, the MCP server allows your LLM agent to create, update, and list brewing profiles directly on your device based on your shot history and tasting results.
›Are there specific skills provided for the Claude Desktop app?
Yes, there are five Claude Desktop skills including tools for profile creation, coffee tracking, shot telemetry diagnosis, feedback loops, and knowledge lookup.
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