Paxaver MCP Server

Official

by Smartoire

Overview Schema Source Related Servers Discussions Admin

TypeScript

Remote

Get Lunch Menu

get_lunch_menu

Read-only

Retrieve your school's orderable lunch menu with item names, prices, dietary tags, and remaining quantity. Specify a date or month for per-day listings; returns menu_item_id needed for placing orders.

Instructions

Returns the orderable lunch menu for the user's active school - item names, prices, dietary tags, and remaining quantity. Pass date for a single day or month for a per-day listing across the whole month (today if neither is given); if both are passed, date wins. The menu_item_id values returned are required by create_lunch_order_draft. For orders already placed, use list_my_lunch_orders.

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_lunch_menu"
  }
}

Input Schema

Name	Required	Description	Default
`date`	No	Single day to show, YYYY-MM-DD; omit when using month
`month`	No	Calendar month to show, YYYY-MM; omit when using date. Today is used when neither is given

Output Schema

Name	Required	Description	Default
`date`	No	Date this menu applies to, YYYY-MM-DD
`menuItems`	No	Items orderable on that date

Schema Changelog

Changes observed during successful MCP inspections.

Addedv2.5.1Sep 25, 2026

TDQS

A4.5/5.0

Behavior4/5

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

Annotations already declare the tool as read-only and non-destructive. The description adds value by specifying the precedence rule (date wins over month) and the default behavior (today when neither is provided), which are behavioral traits not captured by annotations. It does not mention pagination or response structure, but output schema is present.

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 concise and well-structured, front-loading the primary purpose and key details. It covers parameter usage, defaults, and alternative tools in three sentences without redundant phrasing. Every sentence adds value.

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 2 optional parameters, a comprehensive schema with 100% coverage, an output schema, and full annotations, the description is complete. It covers usage rules, parameter precedence, defaults, and cross-references to related tools. No critical information is missing for an agent to call this tool correctly.

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 schema already fully documents both parameters. The description adds a small clarification about the precedence rule (date wins if both are passed), but otherwise does not introduce new semantic meaning beyond what the schema provides. This aligns with the baseline of 3.

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 the tool returns the orderable lunch menu for the active school, including specific details (item names, prices, dietary tags, remaining quantity). It distinguishes itself from related tools like list_restaurant_menu_items and list_my_lunch_orders, so the agent can easily identify its unique purpose.

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

Usage Guidelines5/5

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

The description explicitly explains when to use this tool versus alternatives: it is for the orderable lunch menu, while list_my_lunch_orders is for already placed orders. It also provides clear usage logic for date vs. month parameters, including default behavior when neither is given.

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