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MAQAMI Travel

get_data_flights_airports

Read-onlyIdempotent

Overview

Search for airports by name, city, or IATA code using a text query. Returns matching airports for use in autocomplete and search inputs.

When to Use

  • Airport autocomplete - Power origin/destination search inputs with type-ahead suggestions

  • Airport discovery - Find airports in a city or region by name

  • Search validation - Look up airports before constructing a flight search request

What You Get

  • Matching airports ranked by relevance to the query

  • IATA codes for legs[].origin and legs[].destination on POST /flights/rates

  • City and country details for display purposes

  • Geographic coordinates for map-based interfaces

Quick Start

Provide a q query string (minimum 2 characters) to search by airport name, city, or code. Returns matching airports ordered by relevance.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qYesSearch query (minimum 2 characters, e.g., 'JFK' or 'New York')

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare this a safe, idempotent, open-world read, so the safety profile is covered. The description goes beyond them by disclosing that results are relevance-ranked and what fields come back (IATA code, city/country, coordinates), though it says nothing about empty-result behavior, rate limits, or pagination.

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?

Markdown headers make it scannable and the core instruction is front-loaded in the Overview and Quick Start. The 'What You Get' and 'When to Use' sections are somewhat padded for a one-parameter lookup, but each section carries usable information.

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 no output schema, the description usefully describes the return contents and downstream usage (IATA codes feeding legs[].origin/destination), which is the right compensation. It omits result-limit and error handling details, but nothing critical to calling the tool correctly is missing.

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% for the single parameter, so the schema already documents the query string, its 2-character minimum, and examples. The description repeats the 2-character minimum and adds example formats, but adds no syntax or matching semantics beyond the schema – baseline 3.

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?

The description states a specific verb and resource: 'Search for airports by name, city, or IATA code using a text query.' Scope (returns matching airports for autocomplete/search) is clear. It stops short of explicitly distinguishing itself from close siblings like get_data_flights_airports_iatas or get_data_iatacodes, so an agent must infer the boundary.

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?

A dedicated 'When to Use' section gives three concrete scenarios (autocomplete, discovery, pre-search validation), which is clear context for invocation. However, it never names an alternative tool or states when NOT to use this one, leaving the sibling-selection decision to inference.

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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