Crawlora MCP

swiggy_restaurant

Read-only

Fetch a Swiggy restaurant in India by ID with address, cuisines, cost for two, rating, delivery time, and open status. Use swiggy_search to find a restaurant or swiggy_restaurant_menu for its menu.

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"
  }
}

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

A4.2/5.0

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 and open-world nature are covered. The description adds the geographic scope (Swiggy restaurants in India) and the retrieved fields, but discloses nothing about auth requirements, rate limits, or failure modes; with annotations carrying the safety profile this is adequate but shallow.

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: the capability and its return payload first, then routing guidance. Zero filler and the identity/scope constraint is front-loaded.

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 the field enumeration is technically redundant, but harmless and helps a scanning agent. Sibling routing and scope are complete; only minor behavioral context (e.g., what an unknown ID returns) is absent, which is low-stakes for a simple read tool.

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 restaurant_id, latitude and longitude are already documented in the schema (including the note that lat/long are required by Swiggy's own API). The description adds no parameter syntax or format detail beyond 'by ID', which is the correct baseline 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.

Purpose5/5

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

States a specific verb+resource (fetch a Swiggy restaurant by ID) and enumerates the returned attributes, making it instantly distinguishable from swiggy_restaurant_menu (menu) and swiggy_search (discovery). An agent can identify the tool without opening the schema.

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?

Explicitly routes the agent: use swiggy_search to find a restaurant and swiggy_restaurant_menu for its menu. This is a clear when-to-use-this vs when-to-use-alternatives statement with no inference required.

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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