grr-gaggiuino-mcp
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@grr-gaggiuino-mcpwhat's my current machine status?"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
grr-gaggiuino-mcp
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 |
| Real-time machine state: temperature, pressure, weight, water level, active profile, brewing/steaming status |
| Shot data with time-series curves (pressure, flow, temp, weight) and profile used. Defaults to latest shot. |
| List all brewing profiles with IDs and selection status |
| Activate a brewing profile by ID |
Related MCP server: DevServer MCP
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 buildClaude 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 |
|
| Your Gaggiuino's IP or hostname |
|
| API timeout in milliseconds |
Testing
# With MCP Inspector
npm run inspect
# Direct run
GAGGIUINO_BASE_URL=http://YOUR_IP npm startExample 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 curvesProfile 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 sharedIterative 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
This server cannot be installed
Maintenance
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