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aserper

grubhub-mcp

by aserper

search_restaurants

Search for restaurants near a location by latitude and longitude. Filter by cuisine, restaurant name, or dish, and choose delivery or pickup with pagination and sorting.

Instructions

Search for restaurants near a location.

Args: latitude: Latitude of the delivery address longitude: Longitude of the delivery address query: Optional search query (cuisine, restaurant name, dish) page_size: Number of results per page (default 20) page_num: Page number for pagination (1-based, default 1) sort_type: Optional sort — leave empty for default relevance location_mode: DELIVERY or PICKUP (default DELIVERY)

Input Schema

NameRequiredDescriptionDefault
queryNo
latitudeYes
page_numNo
longitudeYes
page_sizeNo
sort_typeNo
location_modeNoDELIVERY

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.1.7

TDQS

B3.1/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It never states auth requirements, pagination termination behavior, result limits, or whether an empty query returns all restaurants. It only documents the input parameters, leaving behavior opaque.

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?

Purpose is front-loaded in one line, followed by an efficient parameter list. No filler or repetition, though the args block could note which params are required.

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

Completeness3/5

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 params are documented. But with no annotations and no usage guidance, the definition omits the behavioral and routing context an agent needs to pick this over autocomplete_search.

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 document all seven parameters with real semantics—latitude/longitude tied to the delivery address, query examples (cuisine, name, dish), page_size default, 1-based page_num, and location_mode enum values. It stops short of enumerating valid sort_type values or query syntax.

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+resource: 'Search for restaurants near a location.' This distinguishes it from most siblings (get_restaurant, get_menu, add_to_cart), though it doesn't differentiate from the similarly-named autocomplete_search sibling, which an agent might confuse with it.

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 guidance, no exclusions, and no reference to alternatives such as autocomplete_search or get_restaurant. The usage context is only implied by the tool name.

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