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aserper

grubhub-mcp

by aserper

get_menu

Retrieve the full menu for a Grubhub restaurant, including categories, items, and prices, by providing its restaurant ID and optional location coordinates.

Instructions

Get the full menu for a restaurant including categories, items, and prices.

This is the same as get_restaurant — the v4 endpoint returns the full menu.

Args: restaurant_id: The Grubhub restaurant ID latitude: Optional latitude for availability longitude: Optional longitude for availability

Input Schema

NameRequiredDescriptionDefault
latitudeNo
longitudeNo
restaurant_idYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.1.7

TDQS

A3.5/5.0
Behavior3/5

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

With no annotations, the description carries the full burden, and it does add some context: the v4 endpoint returns the full menu, and latitude/longitude affect availability. It still says nothing about authentication requirements, failure modes for an invalid restaurant_id, rate limits, or caching behavior.

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?

Front-loads the purpose in one sentence, then adds the sibling equivalence and a compact Args block restricted to the three parameters. No filler or restated title.

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?

An output schema exists, so return values need not be explained, and all three parameters are described. The main remaining gap is behavioral: auth/prerequisite context and the consequences of an unknown restaurant_id.

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?

Schema description coverage is 0%, so the description must compensate, and it does: restaurant_id is identified as the Grubhub restaurant ID and latitude/longitude as optional coordinates for availability. It gives meaning beyond the bare schema types, though it doesn't specify format ranges or interaction between the coordinate pair.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Get the full menu for a restaurant') and enumerates the payload (categories, items, prices). It also explicitly compares itself to the sibling get_restaurant, telling the agent the two are equivalent at the v4 endpoint — useful differentiation even if it implies redundancy.

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 when-to-use, when-not-to-use, or preference rule is given. Saying 'this is the same as get_restaurant' tells the agent the tools are interchangeable, which removes any basis for choosing between them rather than clarifying selection.

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