io.github.rwestergren/cronometer-api-mcp

add_food_entry

Add a food item to your Cronometer diary using its food ID, measure ID, and gram weight to accurately track daily nutrition.

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. 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").

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
`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 observedv0.1.0Jul 28, 2026

TDQS

A4.5/5.0

Behavior4/5

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

Annotations already indicate readOnlyHint=false (mutation) and openWorldHint=true. The description adds behavioral context by explaining parameter sources (food_id from search_foods, etc.) and effect (adds entry to diary), going beyond annotations.

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 well-structured with an Args section and clear sentences. It could be slightly more concise (e.g., default values could be omitted from text since schema shows them), but it remains effective.

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 tool has 6 parameters, 3 required, and an output schema (present but not shown), the description covers all parameters, workflow, and usage context comprehensively. It is complete for a mutation tool with these complexities.

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?

With 0% schema description coverage, the description fully compensates by explaining the meaning and source of each parameter (e.g., food_id from search_foods, date format YYYY-MM-DD, diary_group enum values). This adds significant value beyond the 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 clearly states 'Add a food entry to the Cronometer diary', uses a specific verb (add) and resource (food entry), and distinguishes from sibling tools like search_foods (for finding) and get_food_details (for confirming).

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 explicitly instructs to use search_foods and get_food_details before calling this tool, providing clear context. It lacks explicit when-not-to-use statements, but the workflow guidance is sufficient.

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