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Cars

cars
Read-onlyIdempotent

API Ninjas cars: vehicle specifications by make, model, year, or fuel type. Returns a list of { make, model, year, fuel_type, cylinders, transmission, drive, city_mpg, highway_mpg, class }. Example: cars({ make: "toyota", model: "camry", year: 2020 }).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
makeNoVehicle manufacturer, e.g. 'toyota', 'ford'
yearNoModel year, e.g. 2020
limitNoMax results to return (default 5, max 50)
modelNoVehicle model, e.g. 'camry', 'mustang'
_apiKeyNoOptional — your own API Ninjas key for higher limits; omit to use the shared Pipeworx key.
fuel_typeNoFuel type, e.g. 'gas', 'diesel', 'electricity'

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / examples
      Previous value: -[
      -  {
      -    "_apiKey": "your-api-ninjas-api-key",
      -    "make": "toyota",
      -    "model": "camry",
      -    "year": 2020
      -  },
      -  {
      -    "_apiKey": "your-api-ninjas-api-key",
      -    "fuel_type": "gas",
      -    "limit": 10,
      -    "make": "ford"
      -  }
      -]New value: +[
      +  {
      +    "make": "toyota",
      +    "model": "camry",
      +    "year": 2020
      +  },
      +  {
      +    "fuel_type": "gas",
      +    "limit": 10,
      +    "make": "ford"
      +  }
      +]
  2. Added

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already establish read-only, idempotent, non-destructive behavior. The description adds the result shape, the filtering dimensions, and a concrete invocation example, going beyond the structured metadata. It does not mention pagination or external API rate limits, but those are secondary given the annotation coverage.

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 short sentences front-load the tool's purpose, list the return shape, and give a realistic invocation. There is no filler or redundancy.

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 read-only lookup tool with all parameters documented, the description supplies enough context to call it correctly: what it returns, the example inputs, and the underlying data source. The absence of an output schema is compensated by the explicit field list.

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%, so the description does not need to repeat parameter definitions and receives the baseline score. Its example and filter phrase map loosely to the parameters but add no semantic detail beyond the schema.

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 names a concrete resource (API Ninjas vehicle specifications) and the lookup dimensions (make, model, year, fuel type), and explicitly states the returned fields. This gives an agent a precise, actionable model of what the tool does, and it is distinguishable from unrelated sibling tools.

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?

There is no guidance about when to choose this over alternatives or when not to use it. The sibling list includes other API Ninjas-style data lookups (animals, exercises, commodity_price), but the description does not draw any boundary between them.

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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