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Crawlora MCP

popeyes_locations

Read-only

Popeyes 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. Restaurant market: US (default) or CA.
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.

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

B3.3/5.0
Behavior2/5

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

Annotations declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. Beyond that, the description adds the field list (address, phone, hours) but says nothing about result ordering, pagination, how radius filtering works, or whether the response is capped (max_results is in schema though). No auth, rate limit, or freshness context. Minimal added behavioral value.

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 with zero filler. It names the resource, the spatial constraint, and the returned fields in one compact line. Nothing extra to trim.

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?

The tool is a read-only location search with a complete schema, an output schema, and annotations covering safety. The description covers what is returned and the spatial constraint but leaves usage routing (vs popeyes_location) and result behavior (ordering, empty handling, country coverage) unspecified. Adequate but incomplete for an agent selecting among many Popeyes siblings.

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 every parameter is fully documented in the schema. The description adds the concept of 'near a location' and the return field list, but adds no extra semantics for latitude/longitude/radius/market/max_results beyond the schema. Baseline 3 is appropriate when the schema does the heavy lifting.

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 ('restaurants near a location') and resource (Popeyes restaurants), and enumerates the fields returned (address, coordinates, phone, amenity flags, per-service hours). It distinguishes itself from popeyes_location (singular detail) and popeyes_menu, but doesn't name them explicitly. Clear but no sibling differentiation.

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

Usage Guidelines3/5

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

The name and description imply usage: find Popeyes near a lat/long. However, there is no explicit when/when-not guidance, no mention of alternatives like popeyes_location for a specific restaurant, and no note about the market parameter (US vs CA) being the mechanism to handle regional availability. Usage is implied.

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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