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Pradumnasaraf

Aviationstack MCP Server

by Pradumnasaraf
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

random_aircraft_type

Get a random sample of aircraft types with names and IATA codes from the Aviationstack catalog. Useful for exploring data or testing integrations.

Instructions

Return a random sample of aircraft types from the Aviationstack reference catalog. Each record has aircraft_name and iata_code. Records are drawn from a random offset, so repeated calls return different rows. This samples the catalog and cannot look up a specific model: there is no search parameter.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
number_of_aircraftYesNumber of random aircraft types to sample, from 1 to 100.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.8.1
    • changedInput schema / properties / number_of_aircraft / description
      Previous value: -"Number of random aircraft types to return."New value: +"Number of random aircraft types to sample, from 1 to 100."
  2. Changed1 schema field changedv1.7.0
    • addedInput schema / properties / number_of_aircraft / maximum
      Added value: +100
  3. Changed4 schema fields changedv1.6.0
    • addedInput schema / properties / number_of_aircraft / description
      Added value: +"Number of random aircraft types to return."
    • addedInput schema / properties / number_of_aircraft / exclusiveMinimum
      Added value: +0
    • changedInput schema / title
      Previous value: -"random_aircraft_typeArguments"New value: +"random_aircraft_type_toolArguments"
    • changedOutput schema / title
      Previous value: -"random_aircraft_typeOutput"New value: +"random_aircraft_type_toolOutput"
  4. First observed

TDQS

A4.5/5.0
Behavior5/5

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

With no annotations, the description carries the full burden and does so well. It discloses the random-offset mechanism, that repeated calls return different rows, and that the tool only samples without a search parameter. This goes well beyond a generic 'returns random data'.

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?

Three sentences front-load the main purpose, then record fields, then the behavioral caveat. Every sentence earns its place; no redundancy or filler.

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?

For a simple one-parameter sampler, the description covers all essential behaviors: random selection, record fields, non-determinism across calls, and the impossibility of lookup. The presence of an output schema means return-value detail does not need to be restated.

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%: the schema fully describes number_of_aircraft as an integer 1-100 with exclusiveMinimum 0. The description does not add material parameter information beyond confirming this is a sample count, so the baseline 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 opens with a specific action and resource: 'Return a random sample of aircraft types from the Aviationstack reference catalog.' It also defines the record shape and explicitly states a non-goal: 'cannot look up a specific model,' which distinguishes it from lookup-oriented tools.

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 provides clear context: use when you need a random sample, and it explicitly says there is no search parameter, telling the agent when not to use it. However, it does not name a specific alternative tool for lookups, so it stops short of full 5-level guidance.

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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