Grr Gaggiuino
FreeNot checkedAn MCP server for Gaggiuino-modified espresso machines, enabling monitoring, shot analysis, and profile management.
About
An MCP server for Gaggiuino-modified espresso machines, enabling monitoring, shot analysis, and profile management.
README
An MCP (Model Context Protocol) server for Gaggiuino-modified espresso machines.
Monitor your machine, analyze shots, and manage brewing profiles from any MCP-compatible client.
Tools
| Tool | Description |
|---|---|
get_status |
Real-time machine state: temperature, pressure, weight, water level, active profile, brewing/steaming status |
get_shot |
Shot data with time-series curves (pressure, flow, temp, weight) and profile used. Defaults to latest shot. |
get_profiles |
List all brewing profiles with IDs and selection status |
select_profile |
Activate a brewing profile by ID |
Installation
Prerequisites
- Node.js 18+
- A Gaggiuino-modified espresso machine on your local network
Option 1: npx (easiest)
No install needed - just configure Claude Desktop to use npx:
{
"mcpServers": {
"gaggiuino": {
"command": "npx",
"args": ["grr-gaggiuino-mcp"],
"env": {
"GAGGIUINO_BASE_URL": "http://YOUR_GAGGIUINO_IP"
}
}
}
}
Option 2: Clone and Build
git clone https://github.com/sgerlach/grr-gaggiuino-mcp.git
cd grr-gaggiuino-mcp
npm install
npm run build
Claude Desktop Configuration
Add to your Claude Desktop config:
macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json
{
"mcpServers": {
"gaggiuino": {
"command": "node",
"args": ["/path/to/grr-gaggiuino-mcp/dist/index.js"],
"env": {
"GAGGIUINO_BASE_URL": "http://YOUR_GAGGIUINO_IP"
}
}
}
}
Note: If using nvm, specify the full path to Node 18+:
"command": "/Users/you/.nvm/versions/node/v20.x.x/bin/node"
Configuration
| Variable | Default | Description |
|---|---|---|
GAGGIUINO_BASE_URL |
http://192.168.3.248 |
Your Gaggiuino's IP or hostname |
REQUEST_TIMEOUT |
5000 |
API timeout in milliseconds |
Testing
# With MCP Inspector
npm run inspect
# Direct run
GAGGIUINO_BASE_URL=http://YOUR_IP npm start
Example Workflows
Quick Status Check
You: "Is my machine ready to pull a shot?"
→ get_status: temp 93°C (target 93°C), pressure stable, water level 85%
Dialing In a New Coffee
You: "I have a new bag of coffee - Ethiopian Yirgacheffe, light roast,
tasting notes of blueberry and citrus. It's 10 days off roast.
What profile should I start with?"
→ LLM recommends a profile based on the coffee characteristics
You: "OK I pulled the shot, analyze it"
→ get_shot returns pressure/flow/temp curves
You: "It tasted sour and watery"
→ LLM analyzes the shot data against your taste feedback:
"The pressure ramped too quickly and flow was high (4.2 ml/s).
Try grinding 2 steps finer. The 6:1 ratio in 24s suggests
under-extraction - aim for 28-32s."
You: "Pulled another shot after adjusting"
→ get_shot for the new shot
→ "Much better - pressure curve is smoother, 2.8 ml/s flow.
How did it taste?"
Shot Analysis & Troubleshooting
You: "My shots have been channeling lately, look at my last few shots"
→ get_shot (latest), get_shot (id: previous)
→ LLM identifies pressure spikes/instability indicating channeling
You: "Compare this shot to yesterday's good one"
→ Side-by-side analysis of shot curves
Profile Management
You: "What profiles do I have?"
→ get_profiles lists all available profiles
You: "Switch to my low-pressure blooming profile"
→ select_profile activates it
You: "Pull a shot and tell me if this profile works for my current beans"
→ get_shot + analysis based on bean characteristics you've shared
Iterative Dial-In Session
You: "Let's dial in this coffee. Medium-dark Brazilian, chocolate/nutty,
for milk drinks. 18g dose, targeting 36g out."
→ LLM suggests starting parameters and profile
[Pull shot 1]
You: "Done, check it"
→ get_shot → "23 seconds, slightly fast. Bitter finish suggests
over-extraction at the end despite short time - likely channeling.
Grind 1 step finer and improve puck prep."
[Pull shot 2]
You: "Better prep this time"
→ get_shot → "27 seconds, smooth pressure curve. How's the taste?"
You: "Really good! Balanced, nice chocolate, good body for a cortado"
→ "Great - this is your baseline. Shot data saved.
Current recipe: 18g → 36g in 27s, Profile: X"
Unit Conversions
The Gaggiuino API returns values in deci-units. This server converts them to standard units:
| Raw API | Converted |
|---|---|
| deciseconds | seconds |
| decibar | bar |
| decidegrees | °C |
| decigrams | grams |
| deci-ml/s | ml/s |
API Reference
Based on the Gaggiuino REST API.
License
MIT
Install Grr Gaggiuino in Claude Desktop, Claude Code & Cursor
unyly install grr-gaggiuino-mcpInstalls into Claude Desktop, Claude Code, Cursor & VS Code — handles npx, uvx and build-from-source repos for you.
First time? Get the CLI: curl -fsSL https://unyly.org/install | sh
Or configure manually
Run in your terminal:
claude mcp add grr-gaggiuino-mcp -- npx -y grr-gaggiuino-mcpFAQ
Is Grr Gaggiuino MCP free?
Yes, Grr Gaggiuino MCP is free — one-click install via Unyly at no cost.
Does Grr Gaggiuino need an API key?
No, Grr Gaggiuino runs without API keys or environment variables.
Is Grr Gaggiuino hosted or self-hosted?
Self-hosted: the server runs locally on your machine via the install command above.
How do I install Grr Gaggiuino in Claude Desktop, Claude Code or Cursor?
Open Grr Gaggiuino on unyly.org, pick your client tab (Claude Desktop, Claude Code, Cursor) and press Install — the config is generated automatically, no JSON editing.
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