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lzinga

US Government Open Data MCP

by lzinga

nhtsa_recalls

Read-onlyIdempotent

Search NHTSA recalls for a vehicle by make, model, and model year to identify safety issues affecting your specific car.

Instructions

Search NHTSA vehicle recalls by make, model, and model year. All three parameters are required by the NHTSA API. Use nhtsa_models to find valid models for a make, or nhtsa_recall_detail for a specific campaign.

Example: make='tesla', model='model 3', model_year=2024

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
makeYesVehicle make: 'toyota', 'ford', 'tesla', 'honda'
modelYesVehicle model: 'camry', 'f-150', 'model 3', 'civic'
model_yearYesModel year: 2020, 2023, 2024

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed7 schema fields changedv2026.4.11
    • removedInput schema / additionalProperties
      Removed value: -false
    • changedInput schema / properties / make / description
      Previous value: -"Vehicle make (e.g. 'honda', 'toyota', 'ford', 'tesla')"New value: +"Vehicle make: 'toyota', 'ford', 'tesla', 'honda'"
    • changedInput schema / properties / model / description
      Previous value: -"Vehicle model (e.g. 'civic', 'camry', 'f-150', 'model 3')"New value: +"Vehicle model: 'camry', 'f-150', 'model 3', 'civic'"
    • changedInput schema / properties / model_year / description
      Previous value: -"Model year (e.g. 2020, 2023)"New value: +"Model year: 2020, 2023, 2024"
    • addedInput schema / properties / model_year / maximum
      Added value: +9007199254740991
    • addedInput schema / properties / model_year / minimum
      Added value: +-9007199254740991
    • changedInput schema / properties / model_year / type
      Previous value: -"number"New value: +"integer"
  2. First observedv2026.3.9

TDQS

A4.2/5.0
Behavior3/5

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

Annotations already cover the safety profile (readOnlyHint, idempotentHint, destructiveHint). The description adds the API requirement that all parameters are mandatory, but does not disclose other behavioral aspects such as response format or error handling. Given the annotation coverage, a 3 is appropriate – it adds some value but not deep behavioral context.

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 concise (two sentences plus an example) and front-loaded with the purpose. It avoids redundancy and places the key information first. Every sentence earns its place.

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?

The tool is simple, the schema fully documents parameters, and annotations cover safety. The description does not mention what the return payload looks like, but for a straightforward search tool this is not a critical omission. It is complete enough for an agent to call it correctly with the required parameters and example.

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%, so the schema already explains each parameter. The description restates that all three are required (already in schema) and provides a concrete example, which adds a bit of practical value. However, it does not go beyond the schema in explaining parameter semantics, so a baseline 3 is fitting.

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 states a specific action ('Search NHTSA vehicle recalls') with a clear resource and parameters. It also names alternative sibling tools (nhtsa_models, nhtsa_recall_detail), effectively distinguishing this tool from them. An agent can immediately understand what this tool does.

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

Usage Guidelines5/5

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

The description explicitly states that all three parameters are required and provides guidance on when to use sibling tools: nhtsa_models to find valid models and nhtsa_recall_detail for a specific campaign. This gives clear conditions for selecting this tool versus alternatives.

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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