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Crawlora MCP

justeat_search

Read-only

Just Eat (UK) restaurant search near a UK postcode: unique_name, name, image, rating, delivery time window, and open-now status.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoRestaurants to return, clamped to 100. Default 20.
filterNoOptional, repeatable. Just Eat's own area-page filter slugs, passed through as-is and OR'd together (e.g. "pizza" and "chinese" together return restaurants matching either cuisine, not both). Also reaches Just Eat's non-restaurant categories -- groceries, alcohol, pharmacy, electronics, flowers, gifts, and more -- via the same mechanism (e.g. filter=groceries); these use /justeat/restaurant/menu's shop-type-store fallback. See notes/justeat-maintenance.md's 'Filters' section for the confirmed 150+ slug list. An unrecognized slug is not rejected client-side; it narrows to a smaller or empty result rather than erroring, matching the upstream's own behavior.
sort_byNoOptional. One of best_match (default), review_rating, distance, delivery_time, minimum_order_value, delivery_fee.
postcodeYesUK postcode to search near (required).

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

B3.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so safety is covered. The description adds little beyond that: it does not characterize result ordering, pagination, or what happens with unrecognized input. Some field-level context is given, which nudges it above a 2.

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?

One tight sentence, front-loaded with the verb and scope, and it lists the return fields without waste. Nothing is padded, though the field enumeration is slightly more like output documentation than usage guidance.

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?

With an output schema present, the description need not explain return values, and the schema covers all params. However, it omits any routing guidance relative to siblings, which is the main remaining gap for a search tool in a dense namespace.

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 coverage is 100%, so the schema already documents all four parameters in depth. The description adds no parameter semantics at all, which is the baseline-3 case, not a penalty.

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 clear verb (search) and resource (Just Eat UK restaurants) scoped to a UK postcode, and enumerates the returned fields. It does not contrast with siblings like justeat_restaurant or justeat_search_filters, but the scope 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?

No when-to-use guidance, no mention of when this is preferable to justeat_search_filters or justeat_restaurant, and no exclusions. The agent must infer that this is the entry-point discovery tool from the name alone.

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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