Garmin MCP Server

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delete_food_log

Remove a logged food item from your Garmin nutrition log by providing its log ID and meal date. Permanently deletes both quick-add and regular entries.

Instructions

Delete a food log entry

Permanently removes a logged food item from the nutrition log. Works for both QUICK_ADD and REGULAR_LOG entry types. Use get_nutrition_daily_food_log to find the logId and date.

Args: log_id: Log entry ID to delete — a 32-char hex UUID (from get_nutrition_daily_food_log) meal_date: Date of the log entry in YYYY-MM-DD format

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": {
      "log_id": "<log_id>",
      "meal_date": "<meal_date>"
    },
    "name": "delete_food_log"
  }
}

Input Schema

Name	Required	Description	Default
`log_id`	Yes
`meal_date`	Yes

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 4, 2026

TDQS

A4.4/5.0

Behavior4/5

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

The description explicitly says 'Permanently removes', disclosing the destructive and irreversible nature. It also clarifies that it works for both QUICK_ADD and REGULAR_LOG entry types. Since no annotations are provided, the description carries the full burden and does it well.

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?

Three concise sentences plus a compact Args list. The description is free of fluff and delivers the essential information in a well-organized structure, making it easy for an agent to parse.

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?

Covers the core action, parameter sourcing, and format. It doesn't mention error handling or return values, but for a delete operation the description provides enough context for an agent to invoke it correctly. The absence of an output schema in the prompt reduces the need for return details.

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?

The input schema has no descriptions (0% coverage). The tool description compensates by explaining log_id as the entry ID from get_nutrition_daily_food_log, and meal_date in YYYY-MM-DD format. It also specifies log_id is a 32-char hex UUID. This adds meaningful detail beyond the raw 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?

States exactly what it does: delete a food log entry. The verb 'Delete' and resource 'food log entry' are specific, and it distinguishes from siblings like delete_weigh_ins or delete_course by targeting the nutrition log.

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?

Provides a clear prerequisite: 'Use get_nutrition_daily_food_log to find the logId and date.' This tells the agent how to obtain the required parameters. It doesn't explicitly say when not to use this tool, but the guidance is actionable and sufficient for a delete operation.

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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