Mise — Meal Planner, Grocery List & Calories

Weekly Meal Planner

plan_week

Read-onlyIdempotent

Plan my meals for the week. Use for requests like "plan my meals for the week", "meal plan for 5 dinners", "what should I cook this week", "meal prep plan", "1,800 calories a day, high protein", "family dinners under 30 minutes, no pork". Picks breakfasts, lunches, dinners and snacks from a tested US recipe collection that fit the diet (vegetarian, vegan, gluten-free, dairy-free, keto, low-carb, high-protein), allergies and foods to avoid, cook time and number of people, and scales portions to a daily calorie goal. Calories and macros come from USDA FoodData Central, never estimated. Returns a day-by-day plan plus a plan_id; then call build_shopping_list with the plan_id for the grocery list and checkout link.

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": "plan_week"
  }
}

Input Schema

Name	Required	Description
`days`	No	How many days to plan (1-7). '5 dinners' = days 5, meals ['dinner'].
`diet`	No	Diet preferences every meal must satisfy.
`seed`	No	Change to get a different plan with the same constraints.
`meals`	No	Which meals to plan each day.
`people`	No	How many people you're cooking for (scales the grocery list).
`exclude`	No	Foods to leave out, in plain words: "pork", "shellfish", "dairy", "gluten", "peanuts", "mushrooms", "cilantro". Matches allergen tags and ingredient names.
`cuisines`	No	Preferred cuisines, e.g. ["Mexican", "Italian"]. Soft preference.
`daily_calories`	No	Calorie goal per person per day, e.g. 2000. Portions are scaled to hit it.
`max_cook_minutes`	No	Max total prep + cook time per meal, e.g. 30 for quick weeknight meals.

Output Schema

Name	Required	Description
`days`	Yes
`notes`	Yes
`people`	Yes
`plan_id`	Yes	Pass to build_shopping_list to get the grocery list and checkout link.
`nutrition_source`	Yes
`daily_calorie_goal`	Yes
`average_daily_per_person`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 21, 2026

TDQS

A4.2/5.0

Behavior4/5

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

The annotations already declare readOnlyHint, idempotentHint, openWorldHint=false, and destructiveHint=false, and the description is consistent with all of them. It adds useful behavioral context beyond annotations: recipes come from a 'tested US recipe collection,' calories and macros come from USDA FoodData Central and are 'never estimated,' and the tool returns a day-by-day plan plus a plan_id for the shopping-list handoff. It does not mention determinism or seed behavior, but that is documented in the schema.

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 front-loaded with purpose, then examples, then behavioral details, and every part contributes to correct invocation. It is slightly long and repetitive in the example list ('plan my meals for the week' echoes both the title and the first sentence), but not enough to be a structural problem.

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 a nine-parameter tool with a full output schema, the description covers purpose, natural-language use cases, data provenance, output handoff, and the next tool to call. Nothing an agent needs in order to invoke this correctly is missing, and return-value details are appropriately left to the output schema.

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

Parameters3/5

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

Schema description coverage is 100%, so the parameters are already fully documented. The description restates how diet, exclusions, cook time, people, and calorie goals shape the plan, but it does not add syntax, interaction rules, or format details beyond what the schema already provides. The baseline of 3 is appropriate.

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 states a specific verb and resource ('Plan my meals for the week') and immediately distinguishes the tool from its sibling by explaining that build_shopping_list is the follow-up step for the grocery list. An agent can tell exactly what this tool produces without opening the schema.

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 strong natural-language routing examples ('meal plan for 5 dinners', '1,800 calories a day, high protein') and names the next tool to call with the returned plan_id. However, it does not state when not to use it or contrast it with siblings like generate_recipe or log_calories, so the exclusion side of the guideline is missing.

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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