Skip to main content
Glama
Sign In
Nutriscan MCP connector

Nutriscan MCP connector

by si-essence
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Hybrid

meal_log_add

Append an eaten food to the local meal log, optionally snapshotting Open Food Facts nutrients by barcode and grams or servings. Use it to track daily meals privately, with no upload.

Instructions

Append one eaten food to the local meal log (a JSON file on disk; nothing is uploaded). Pass a barcode to snapshot Open Food Facts nutrients, plus grams or servings. Without a barcode, pass a name and grams (nutrients are then omitted from totals). Optional meal slot and UTC date (YYYY-MM-DD).

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "meal_log_add"
  }
}

Input Schema

NameRequiredDescriptionDefault
dateNoUTC calendar date YYYY-MM-DD. Defaults to today (UTC).
mealNoMeal slot: breakfast, lunch, dinner, or snack.
nameNoFood name. Required when barcode is omitted. Overrides the product name when both are set.
noteNoOptional short note stored only in the local log.
gramsNoAmount eaten, in grams. Required unless servings is set with a barcode.
barcodeNoOpen Food Facts barcode. When set, nutrients are snapshotted for the amount eaten.
servingsNoNumber of label servings. Requires a barcode whose serving size is known. Ignored when grams is set.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.3/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare the write/idempotency profile, and the description adds real context beyond them: the log is a local on-disk JSON file with nothing uploaded, and entries without a barcode silently contribute no nutrients. It stops short of stating what a call returns or that repeated appends create duplicate entries, which matters given idempotentHint=false.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Four tight sentences, front-loaded with the action and the local-only constraint before the parameter decision tree. Only minor waste, mainly repeating the date format already documented in the schema.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 7-parameter, zero-required mutation with no output schema, the description covers the input paths and the key side effect (omitted nutrients) well. It leaves the response shape unstated, so an agent cannot predict what comes back or how to confirm success.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so baseline would be 3, but the description adds cross-parameter logic the schema cannot express: barcode+grams/servings share a path, and name-only entries lose nutrient totals. The parenthetical "(YYYY-MM-DD)" restates the schema without adding anything, keeping it from a 5.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb+resource: "Append one eaten food to the local meal log," and immediately bounds scope (a JSON file on disk, nothing uploaded), which separates it from meal_log_list and meal_log_day_total without the agent needing to open schemas.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives a clear conditional decision rule: with a barcode, nutrients are snapshotted and can use grams or servings; without a barcode, pass name plus grams and nutrients are omitted from totals. That's strong when-to-use guidance, though it never names a sibling tool or the case where the user wants to correct/remove an entry instead of appending.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Deploy Server

Other Tools