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Crawlora MCP

ubereats_store

Read-only

Fetch one Uber Eats store's public profile, contact details, rating, hours, and menu when present. Use ubereats_search to find stores, ubereats_store_menu for menu-only data, or ubereats_store_reviews for customer reviews.

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": {
      "storeUuid": "<storeUuid>"
    },
    "name": "ubereats_store"
  }
}

Input Schema

NameRequiredDescriptionDefault
storeUuidYesUberEats store UUID, as returned by the search endpoint's storeUuid field.

Output 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

A4.3/5.0
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 that the menu is returned 'when present' (a conditional behavior), but omits permissions, rate limits, or errors. With annotations present the bar is lower and the added value is modest.

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, front-loaded with the fetch scope followed by sibling routing. No filler or redundancy.

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

Completeness5/5

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 no explanation), the sole parameter is fully documented, annotations cover the safety profile, and sibling alternatives are named. Nothing needed to call it correctly is missing.

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% and the single parameter storeUuid is already documented in the schema as the UUID from the search endpoint. The description adds no parameter-level detail beyond that, so the baseline 3 applies.

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 (Fetch) and resource (one Uber Eats store) and enumerates what is returned: public profile, contact details, rating, hours, and menu. It explicitly names the sibling tools it is not, so an agent can distinguish it immediately.

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

Usage Guidelines5/5

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

Names three concrete alternatives and the condition selecting each: ubereats_search to find stores, ubereats_store_menu for menu-only data, ubereats_store_reviews for reviews. This is explicit routing guidance rather than implied usage.

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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