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Crawlora MCP

burgerking_locations

Read-only

Burger King restaurants near a location: address, coordinates, phone, amenity flags and per-service hours (dining room, drive-thru, delivery, curbside).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
marketNoOptional. RBI market to search, one of US, CA. Default US.
radiusNoOptional. Search radius in meters, 1-50000, default 8000.
latitudeYesRequired. Search center latitude.
longitudeYesRequired. Search center longitude.
max_resultsNoOptional. Maximum restaurants to return, 1-50, default 20.
delivery_onlyNoOptional. Restrict to restaurants that actually deliver to this coordinate, per RBI's own delivery-zone match (distinct from the has_delivery amenity flag). Default false. Cannot be combined with include_availability.
include_availabilityNoOptional. Include each restaurant's live per-channel open/closed status. Default false.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYesThe tool result payload (shape varies per tool; see each tool's docs resource).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.4/5.0
Behavior3/5

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

readOnlyHint=true and openWorldHint=true already tell the agent this is a safe, external-data read. The description adds the returned field set (address, phone, amenity flags, per-service hours), but discloses no rate limits, auth needs, or fallback behavior beyond what annotations and the output schema provide.

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?

A single front-loaded sentence that names the resource first and then the payload, with no filler. Every clause conveys distinct information.

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?

With an output schema covering returns, full schema descriptions on all 7 params, and read-only/open-world annotations, the description is sufficient for correct invocation. It could note the delivery_only/include_availability exclusivity, but that constraint already lives in the 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 parameters like radius, market, delivery_only, and include_availability are fully documented in the schema. The description adds no syntax or constraint detail beyond that, so the baseline of 3 applies.

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 ('Burger King restaurants near a location') and enumerates the returned fields, which clearly sets it apart from burgerking_menu, product, and availability siblings. It stops short of naming those siblings explicitly, but the resource identity is unambiguous.

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?

The description says nothing about when to choose this over alternatives such as burgerking_availability, nor about exclusions or preconditions. 'Near a location' implies the search context, but there is no explicit when/when-not guidance.

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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