ZapifyAPI MCP Server

get_country_info

Retrieve country details including capital, population, languages, and flag by providing a country name or ISO code.

Instructions

Get country information (capital, population, languages, flag).

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": {
      "country": "<country>"
    },
    "name": "get_country_info"
  }
}

Input Schema

Name	Required	Description	Default
`country`	Yes	Country name or ISO code

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Aug 3, 2026

TDQS

B3.4/5.0

Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states what information is returned, but does not mention whether it makes a network request, handles missing countries, has rate limits, or any other behavioral traits. This is a significant gap for a tool with no annotation support.

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?

The description is a single, well-structured sentence that front-loads the primary action ('get country information') and then specifies the key result fields. It is appropriately sized with no wasted words.

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?

For a simple tool with one parameter and no output schema, the description adequately covers what the tool does and what it returns. However, it omits important contextual details such as accepted ISO code formats (e.g., alpha-2 vs alpha-3) and behavior for invalid or unrecognized country names, which would improve completeness.

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?

The schema already covers the parameter semantics with a description of 'Country name or ISO code' for the 'country' parameter, giving 100% coverage. The tool description does not add any additional meaning to the parameter beyond what the schema provides, so the baseline score of 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 clearly states the verb 'Get' and the resource 'country information', and specifically enumerates the data types covered (capital, population, languages, flag). This is specific enough to distinguish from sibling tools like convert_currency or ip_geolocation, which are clearly different in scope.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives, no prerequisites, and no exclusions. While the tool name implies a purpose, the description itself does not offer any decision-making context for an AI agent deciding between tools.

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