Crawlora MCP

grubhub_availability

Read-only

Check ordering availability for up to 20 Grubhub restaurants, including channel status, delivery, flags, distance, ETA, fees, minimums, and next orderable time. Use grubhub_search to find restaurants, grubhub_restaurant_menu for items, or grubhub_timepicker for a restaurant's schedule.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "restaurant_ids": "<restaurant_ids>",
      "latitude": "<latitude>",
      "longitude": "<longitude>"
    },
    "name": "grubhub_availability"
  }
}

Input Schema

Name	Required	Description
`latitude`	Yes	Required. Diner location latitude -- availability is relative to it.
`longitude`	Yes	Required. Diner location longitude.
`restaurant_ids`	Yes	Required. Comma-separated Grubhub restaurant ids, up to 20.

Output Schema

Name	Required	Description	Default
`data`	Yes	The tool result payload (shape varies per tool; see each tool's docs resource).

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 5, 2026

TDQS

A4/5.0

Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds the list of returned fields (channel status, delivery, flags, ETA, fees, minimums), but that overlaps with the output schema and adds little behavioral context beyond the annotations.

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?

Two sentences, zero waste: the purpose and scope are front-loaded, and the sibling routing follows. Nothing redundant or padded.

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 present, return values need not be explained, and all params are documented in the schema. The description covers purpose, scope, and sibling routing; it is essentially complete, though it could mention that availability is relative to the supplied coordinates.

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 all three parameters are already documented, including the 20-id cap and the location-relative nature of latitude/longitude. The description's 'up to 20' merely repeats the schema, so baseline 3 is appropriate.

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

Purpose5/5

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

States a specific verb (Check) and resource (ordering availability) with an explicit scope (up to 20 Grubhub restaurants) plus an enumeration of returned fields. An agent can distinguish it from grubhub_search, grubhub_restaurant, and grubhub_timepicker without opening any schema.

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

Usage Guidelines4/5

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

Explicitly routes the agent to alternatives: grubhub_search to find restaurants, grubhub_restaurant_menu for items, grubhub_timepicker for a schedule. This implies the restaurant_ids must come from search first, but no explicit when-not condition or prerequisite ordering is spelled out.

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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