OpenVan MCP Server

Rank Countries By Food Prices

rank_food_prices

Read-onlyIdempotent

Compare countries by food price index across a region or worldwide to identify cheaper or pricier grocery destinations.

Instructions

Rank countries by food price index (world average = 100) in a region or worldwide: the cheapest first, or with order=most_expensive the most expensive first. Use it when someone asks where food or groceries are cheapest or most expensive.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "rank_food_prices"
  }
}

Input Schema

Name	Required	Description	Default
`limit`	No	How many countries to return.
`order`	No	cheapest first (default) or most_expensive first.	cheapest
`locale`	No	Language the user writes in (en, ru, de, fr, es, pt, tr). Set it on every call: the answer and the interactive card are shown in this language and units; without it the card falls back to the app's interface language.
`region`	No	Only countries of this region. Default: world.	world

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

Changed3 schema fields changedv0.9.7Oct 25, 2026
- removedInput schema / additionalProperties
```
Removed value: -false
```
- removedInput schema / properties / limit / default
```
Removed value: -10
```
- changedOutput schema / additionalProperties
```
Previous value: -trueNew value: +{}
```
Addedv0.6.4Oct 15, 2026

TDQS

A4.2/5.0

Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint and destructiveHint=false, so the safety profile is covered. The description adds genuine context beyond that by defining the index baseline (world average = 100), which tells the agent how to interpret the ranking values. Return format is left to the output schema.

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 filler: the ranking semantics and sort direction come first, followed by the usage trigger. Every sentence carries information the agent needs.

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, annotations covering the safety profile, and full schema coverage of all parameters, the description needs only to establish purpose and usage, which it does. The minor gap is that it does not note the limit interplay with ranking (top-N cheapest), though that is largely inferable.

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 four parameters (limit, order, locale, region) are already documented in the schema. The description only restates the order behavior ('order=most_expensive'), adding no syntax or constraint detail beyond what the schema provides, 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?

The description gives a specific verb (rank), resource (countries by food price index), the scale semantics (world average = 100), and scope (region or worldwide). This clearly separates it from sibling tools like compare_food_prices and get_country_food_prices, which per their names retrieve or compare rather than rank.

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?

It states the triggering question explicitly: 'Use it when someone asks where food or groceries are cheapest or most expensive.' That is a clear use-case signal, though it does not name a specific alternative (e.g., compare_food_prices) or state when not to use it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.