Cronometer MCP

add_food_entry

Logs a food serving into a Cronometer diary using food and measure IDs, grams, date, meal slot, and time for accurate nutrition tracking.

Instructions

Add a food entry to the Cronometer diary.

Use search_foods to find food_id and measure_id, then get_food_details to confirm serving sizes and gram weights.

Args: food_id: Numeric food ID from search_foods results. measure_id: Measure/unit ID from get_food_details. grams: Weight of the serving in grams. Real grams for recipes too: the conversion to Cronometer's batch units happens here. date: Date to log as YYYY-MM-DD (defaults to today). translation_id: Translation ID from search results (usually 0). diary_group: Meal slot -- one of "auto", "breakfast", "lunch", "dinner", "snacks" (case-insensitive, default "auto"). time: Time of day as HH:MM or HH:MM:SS. Defaults to now. Pass the real eating time when logging after the fact; an "auto" diary_group then follows that hour instead of the current one.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "food_id": "<food_id>",
      "measure_id": "<measure_id>",
      "grams": "<grams>"
    },
    "name": "add_food_entry"
  }
}

Input Schema

Name	Required	Default
`date`	No
`time`	No
`grams`	Yes
`food_id`	Yes
`measure_id`	Yes
`diary_group`	No	auto
`translation_id`	No

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv2.1.0Nov 14, 2026

TDQS

A4.6/5.0

Behavior4/5

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

Annotations only indicate read/write and idempotency hints, so the description carries meaningful behavioral weight. It adds valuable details beyond the schema: grams are real grams including recipes, date and time defaults, case-insensitive diary_group values, and how an 'auto' diary_group responds to a passed time. This is substantial and consistent with the annotations.

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

Conciseness5/5

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

The description is front-loaded with the core purpose, followed by a short prerequisite workflow, then a structured Args list. Every sentence adds information; there is no fluff or repetition of schema properties.

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?

With seven parameters and three required, the description covers all of them and their edge cases. The output schema exists, so return-value documentation is not the description's responsibility. The prerequisite lookup steps make the tool safely usable without additional investigation.

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%, but the description fully compensates by explaining every parameter, including formats, defaults, allowed values, and provenance. For example, it defines date as YYYY-MM-DD, time as HH:MM[:SS], diary_group as a closed set, and translation_id as usually 0.

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: 'Add a food entry to the Cronometer diary.' This clearly distinguishes it from sibling tools like edit_food_entry, remove_food_entry, and add_custom_food by framing it as a diary-entry creation operation. The prerequisite workflow with search_foods and get_food_details further anchors the tool's specific role.

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?

The description gives clear procedural context: users must first use search_foods to find food_id and measure_id, then get_food_details to confirm serving sizes and gram weights. It does not explicitly discuss alternatives or exclusions, but the workflow makes the intended usage unambiguous.

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

Deploy Server