OpenVan MCP Server

Get Food Price Index

get_country_food_prices

Read-onlyIdempotent

Retrieve a country's food price index and yearly history to answer questions about grocery costs or how expensive food and living are there.

Instructions

Food price index for one country (world average = 100): how expensive groceries are there, with its yearly history. Use it when someone asks how expensive food, groceries or living is in a country.

Input Schema

Name	Required	Description	Default
`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.
`country_code`	Yes	ISO 3166-1 alpha-2 country code.

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedv0.9.7Oct 25, 2026
- removedInput schema / additionalProperties
```
Removed value: -false
```
- changedOutput schema / additionalProperties
```
Previous value: -trueNew value: +{}
```
Addedv0.6.4Oct 15, 2026

TDQS

A4/5.0

Behavior4/5

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

Annotations already declare readOnly/idempotent/openWorld, so safety is covered; the description adds genuinely non-obvious behavior – the index is normalized to a world average of 100 and the response carries a yearly history rather than a single point value. It stops short of describing pagination or history span, which keeps it off a 5.

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, zero waste, and the scale anchor is front-loaded before the usage cue. Nothing here repeats the name or title verbatim.

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?

An output schema exists, so return values need not be spelled out; the description supplies the interpretive key (100 = world average) that makes the numbers meaningful. Coverage of the locale parameter's purpose is left entirely to the schema, a minor gap for a 2-parameter 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%, and the description adds nothing about country_code (ISO alpha-2) or the locale parameter's effect on language and units. With the schema doing all the parameter work, baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

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

States a specific verb+resource ('Food price index for one country') and adds the scale (world average = 100) plus the fact that yearly history is included. The 'one country' framing implicitly separates it from compare_food_prices/rank_food_prices, but neither sibling is named outright.

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?

Gives an explicit trigger: 'Use it when someone asks how expensive food, groceries or living is in a country.' That is clear context, but it names no alternatives or exclusions even though compare_food_prices and rank_food_prices exist and would be the natural competitors for multi-country questions.

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