purdue-mcp

Get a dining court menu

dining_menu

Retrieve full menus for any Purdue dining location, filtered by meal period and dietary tags like vegan or allergen-free, for a specific date.

Instructions

Full menu for one Purdue dining location on a date, by meal period and station, with dietary tags. Source: Purdue HFS dining API (live).

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": {
      "location": "<location>"
    },
    "name": "dining_menu"
  }
}

Input Schema

Name	Required	Description
`date`	No	YYYY-MM-DD. Defaults to today on campus.
`meal`	No	Filter to one meal period, e.g. 'Breakfast', 'Lunch', 'Dinner', 'Late Lunch'.
`location`	Yes	Location name or code, e.g. 'Wiley', 'Earhart', 'Hillenbrand', 'WILY'.
`vegan_only`	No
`vegetarian_only`	No
`exclude_allergens`	No	Drop items containing any of these, e.g. ['Peanuts','Gluten','Milk'].

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.3.0Aug 18, 2026

TDQS

C2.9/5.0

Behavior2/5

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

No annotations are provided, so the description must carry the full burden. It mentions a live API source, but does not disclose behavioral traits like rate limits, authentication, pagination, error handling, or output format. The phrase 'by meal period and station' is ambiguous—station is not a parameter in the schema, which could mislead an agent about available filters.

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 a single sentence with no wasted words. However, the inclusion of 'station' is ambiguous and slightly detracts from clarity. Still, it is appropriately concise for a simple tool.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 6 parameters, no output schema, and no annotations, the description is insufficient. It does not explain the return format, how dietary filters interact, or what happens if no menu is available for a given date/meal. The mention of 'station' without a corresponding parameter creates confusion. An agent would likely need to infer behavior from arbitrary examples.

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

Parameters2/5

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

Schema description coverage is 67% (4 of 6 parameters documented). The description reinforces the purpose of 'date', 'meal', and dietary tags, but does not add meaning for the undocumented 'vegan_only' and 'vegetarian_only' parameters. It also mentions 'station' which is not a parameter, reducing clarity. The description fails to compensate for gaps in 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 the tool returns a 'Full menu for one Purdue dining location on a date, by meal period and station, with dietary tags.' This distinguishes it from siblings like dining_locations (lists locations), dining_find_item (search specific item), dining_item_nutrition (nutrition info), and dining_line_length (wait times). The verb 'Get' in the title is aligned.

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

Usage Guidelines2/5

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

No explicit guidance on when to use this tool vs. alternatives. The description implies use when you want a full menu with dietary filters, but does not contrast with dining_find_item (for searching across locations) or dining_line_length (for wait times). With many dining siblings, explicit usage guidance is missing.

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