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papajohns_india_menu

Retrieve Papa John's India menu with live prices in INR, including categories, deals, dietary tags, and blackout availability. Filter by category, tag, or store/channel/day, and optionally expand full item options.

Instructions

Get the Papa John's India priced menu (INR). Returns Papa John's India menu with live prices in Indian Rupees, from papajohns.in's own ordering backend. This is the India market only -- prices, items, and availability are India-specific and are not comparable to Papa John's US/Canada data (see GET /papajohns/nutrition for US national reference data). Returns every category with its items and deals: list price, strike-through price where a discount is active, dietary tags (Veg, Non Veg, Spicy), images, and the store/channel/day combinations where an item is blacked out. Set include_options=true to also get each item's full size, crust, topping, sauce, and drizzle tree with per-option prices -- this makes the response very large, so prefer GET /papajohns/india/menu/item for one item's options. Pricing is franchise-wide rather than per-store; store_id, channel_id, and day filter item availability, not price, and only take effect when all three are supplied.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dayNoWeekday. One of: 0 (Sunday), 1 (Monday), 2 (Tuesday), 3 (Wednesday), 4 (Thursday), 5 (Friday), 6 (Saturday). Only applies together with store_id and channel_id.
tagNoReturn only items carrying this tag, e.g. Veg, Non Veg, Spicy. Case-insensitive.
store_idNoHide items blacked out at this store id (see GET /papajohns/india/stores). Only applies together with channel_id and day.
channel_idNoOrder channel. One of: 1 (Delivery), 2 (Take Away), 3 (Dine In), 4 (Drive Through Pickup). Only applies together with store_id and day.
category_idNoReturn only this category id
include_optionsNoInclude every item's full size/crust/topping option tree with prices. Default false.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv1.17.5
    • addedInput schema / properties / channel_id / enum
      Added value: +[
+  "1",
+  "2",
+  "3",
+  "4"
+]
    • addedInput schema / properties / day / enum
      Added value: +[
+  "0",
+  "1",
+  "2",
+  "3",
+  "4",
+  "5",
+  "6"
+]
  2. Addedv1.16.2

TDQS

A4.6/5.0
Behavior4/5

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

With no annotations present, the description carries the full burden and largely succeeds. It discloses the return contents (categories, items, deals, prices, strike-through prices, dietary tags, images, and blackout combinations), the large response when include_options=true, the franchise-wide pricing model, and that store_id/channel_id/day only filter availability—not price—and only when all three are provided. It does not explicitly state read-only or rate limits, but the nature of 'Get' plus the detailed behavior is strong.

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?

The description is longer than average but each sentence earns its place: purpose, return contents, include_options caveat, and pricing/filter semantics. It is front-loaded with the primary purpose and avoids unnecessary fluff. The only minor redundancy is repeating the 'only together' constraint that already exists in the schema descriptions, but it adds value by emphasizing it.

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?

Given 6 parameters, no output schema, and no annotations, the description is exceptionally complete. It covers what data is returned, how to handle the large-option scenario, the pricing model, and the exact semantics of the store/channel/day filters. It also points to the item-level endpoint for narrower queries, so an agent can invoke this tool correctly with no further investigation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the baseline is 3. The description adds substantive meaning beyond the schema by explaining that include_options returns a very large option tree (and recommending the item endpoint instead), and by clarifying that store_id, channel_id, and day filter availability rather than price and only take effect together. This goes beyond mere restating of parameter names.

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?

The description uses a specific verb 'Get' with a clearly defined resource: Papa John's India priced menu in INR. It explicitly states the India-only scope and differentiates from US/Canada data by referring to GET /papajohns/nutrition. It also distinguishes this from the item-level endpoint, making the purpose unmistakable among siblings like papajohns_menu and papajohns_india_menu_item.

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?

The description gives explicit when-to-use guidance: it is for India-only menu data, and if include_options would make the response too large, it instructs the agent to prefer GET /papajohns/india/menu/item for a single item's options. It also points to /papajohns/nutrition for US reference data, providing clear exclusions and alternatives.

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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