Crawlora MCP

swiggy_restaurant_menu

Read-only

Fetch one Swiggy restaurant's full menu grouped into category and item records, including prices and availability. Use swiggy_search to discover a restaurant or swiggy_restaurant for its profile.

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_id": "<restaurant_id>",
      "latitude": "<latitude>",
      "longitude": "<longitude>"
    },
    "name": "swiggy_restaurant_menu"
  }
}

Input Schema

Name	Required	Description
`latitude`	Yes	Caller latitude (required by Swiggy's own menu API).
`longitude`	Yes	Caller longitude (required by Swiggy's own menu API).
`restaurant_id`	Yes	Restaurant id, from /swiggy/search's id field (required).

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

A4.3/5.0

Behavior4/5

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

Annotations cover the safety profile (readOnlyHint=true, openWorldHint=true), and the description adds useful behavioral detail about the return: a full menu grouped into category and item records with prices and availability. It doesn't discuss auth, rate limits, or pagination, but it meaningfully extends 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 tight sentences with zero waste. The purpose and result shape are front-loaded, and the routing hint follows, which is the correct ordering for an agent scanning for a tool.

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?

With an output schema present, the description needn't enumerate return fields, and it still summarizes the grouping. Purpose, routing, and result shape are all covered, so nothing needed to invoke 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 description coverage is 100% – all three parameters are documented, including that restaurant_id comes from /swiggy/search's id field and that lat/long are required by Swiggy's own API. The description adds nothing beyond the schema, 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 Swiggy restaurant's full menu) and describes the shape of the result (grouped into category and item records, including prices and availability). It also names the sibling tools (swiggy_search, swiggy_restaurant) so the agent can distinguish this from discovery/profile tools.

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: use swiggy_search to discover a restaurant or swiggy_restaurant for its profile, implying this tool is for pulling the menu once you have the restaurant_id. Clear context for use, though it doesn't state an explicit when-not or prerequisite sequence.

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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