Cronometer MCP

get_food_log

Read-onlyIdempotent

Retrieve all food and non-food diary entries for a given date, including each food's scaled nutrients plus daily calorie target, consumed, and remaining totals.

Instructions

Get all diary entries for a given date.

Returns every food entry logged for the day. Each "Serving" entry is enriched (best-effort) with the food's name, source, the serving measure (unit name and grams per unit), the number of servings, and that food's own nutrient profile scaled to the amount eaten. Non-food entries (exercise, biometrics) carry their own name.

Note: the per-entry "nutrients" are each food's individual contribution, which is distinct from the day-level nutrition_summary aggregate below.

Also returns a top-level energy_summary field with pre-computed values most relevant to the user:

total_target_kcal: daily calorie target dynamically adjusted for expenditure and weight goal (equivalent to Cronometer's "Total Target" in the Energy Summary screen)
consumed_kcal: total calories consumed
remaining_kcal: calories remaining to stay on target (total_target_kcal - consumed_kcal). Always report this when summarizing the user's day. Prefer this over manually deriving values from the burn breakdown fields.

Also returns a nutrition_summary field with consumed totals for every nutrient eaten that day:

macros: flat macro totals (energy, protein, carbs, net_carbs, fat, fiber, alcohol)
nutrients: every nutrient with amount, unit and tracked, which says whether it has a target set in Cronometer. Untracked ones were still eaten; they just have nothing to measure against, so report them as plain figures and never as over or under target.

Args: date: Date as YYYY-MM-DD (defaults to today). include_untracked: Leave true for everything eaten. False restricts the summary to nutrients with targets, matching the app's own summary.

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": "get_food_log"
  }
}

Input Schema

Name	Required	Description	Default
`date`	No
`include_untracked`	No

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv2.1.0Nov 14, 2026

TDQS

A4.5/5.0

Behavior5/5

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

The description adds substantial behavioral detail beyond the annotations: enrichment is 'best-effort,' non-food entries carry their own name, per-entry nutrients differ from day-level nutrition_summary, and untracked nutrients should be reported as plain figures rather than over/under target. This greatly helps an agent interpret results correctly.

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?

The description is longer than average but well-organized with clear bullets and purposeful sections. It front-loads the core purpose and adds needed field semantics without obvious redundancy. A few phrases could be tightened, but every major point earns its place.

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

Completeness5/5

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

Given the output schema exists, the description does not need to restate return types, but it adds critical interpretive context: how to present remaining_kcal, how to treat untracked nutrients, and the distinction between per-entry and aggregate nutrition. This makes the tool fully usable for correct agent behavior.

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

Parameters5/5

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

Schema description coverage is 0%, so the description must compensate. It fully explains both parameters: date format is YYYY-MM-DD with a default of today, and include_untracked controls whether the summary is restricted to nutrients with targets. This goes well beyond the bare schema.

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 and resource: 'Get all diary entries for a given date,' and clarifies it returns every food entry logged for the day. This cleanly distinguishes it from sibling tools like get_daily_nutrition or get_food_details, whose purpose is implied to be different.

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

Usage Guidelines3/5

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

The context of use is clear: retrieve a day's food log and summarize the user's day. It also gives guidance to always report remaining_kcal and prefer it over deriving from burn fields. However, it does not explicitly say when to choose this tool over siblings like get_daily_nutrition or list_biometrics, leaving some selection guidance implicit.

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

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