MCP server for Gaggiuino-modified espresso machines
Server has 7 tools with consistent naming (verb_noun pattern) and basic descriptions. All tools have Zod schemas with typed parameters. However, descriptions are generic and lack LLM-optimization guidance (avg ~50 chars, below 194-char baseline). Parameter descriptions exist but are minimal. Output schemas are not documented. Error handling returns generic messages without recovery guidance. Missing tool annotations (readOnlyHint, destructiveHint). No pagination support for list operations. Composition is sound, each tool has one responsibility, but descriptions don't explain WHEN to use each tool vs alternatives.
Delete a specific espresso profile
Get all available espresso profiles
Get the ID of the latest espresso shot
Get detailed data for a specific espresso shot
Get the current system status of the espresso machine
Select a specific espresso profile
Upload data for a new espresso shot
Descriptions lack LLM-optimization guidance. Most are 30-55 chars (below 194-char baseline). Missing WHEN/WHY context. E.g., 'Get the current system status' doesn't explain what status fields are returned or when to call it vs getShotData.
Output schemas not documented. Tools return JSON strings (e.g., 'JSON.stringify(status, null, 2)') but LLM has no schema to parse fields. Agents cannot reliably extract data for downstream calls.
Error handling returns generic messages ('fetching system status') without recovery guidance. No categorization (retryable vs fatal). LLM cannot determine next action on failure.
Inferred effective spec: <=2025-11-25.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | F | 49 | <=2025-11-25 | v2 |
Missing tool annotations. deleteProfile and selectProfile are WRITE/DESTRUCTIVE but lack readOnlyHint/destructiveHint annotations. Agents cannot infer safety implications.
getAllProfiles lacks pagination. No limit/offset params or total count in response. Large profile lists will blow context window.