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VIN Decoder + Safety Recalls (NHTSA)

Server Details

Decode any VIN (NHTSA vPIC) and list safety recalls for that make, model and year. x402.

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Status
Healthy
Last Tested
Transport
Streamable HTTP · MCP 2025-11-25
URL

TDQS

A4.2/5.0

Scored across 1 tool

Disambiguation5/5

Only one tool exists, so there is no possibility of confusion or misselection among tools. The tool's purpose is clearly stated and distinct within the server.

Naming Consistency5/5

With a single tool named 'vin_decode', naming is trivially consistent. The snake_case convention is clear, and no mixed styles or vague verbs exist.

Tool Count4/5

One tool for a focused VIN decoder and recall lookup is minimal but sufficient. It combines two related features (decoding and recalls) into a single call, which is slightly less modular but not inappropriate.

Completeness4/5

The tool covers VIN decoding and safety recalls comprehensively for a given VIN, including error notes and recall details. Minor gaps include no batch decoding or direct recall search by make/model/year without a VIN, but these are outside the stated VIN-centric purpose.

Available Tools

1 tool
vin_decodeAInspect

Decode a 17-character VIN with NHTSA vPIC: make, model, model year, trim, body class, engine, fuel, drive type, transmission, plant, plus checksum validation and NHTSA error notes, and the NHTSA safety recall campaigns for that make, model and year (component, summary, remedy, park-it and park-outside flags). Use when an agent must identify a vehicle from its VIN (make, model, year, engine, plant) and check open safety recalls before a purchase, listing, insurance quote or repair. Paid per call via x402 (USDC on Base).

ParametersJSON Schema
NameRequiredDescriptionDefault
vinNo17-character Vehicle Identification Number
recallsNoInclude recalls (default true)
payment_signatureNox402 v2 PAYMENT-SIGNATURE header value. Omit to receive payment requirements.

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: it discloses the commercial model ('Paid per call via x402 (USDC on Base)'), the validation behavior (checksum validation, NHTSA error notes), and that recall payloads include component, summary, remedy, and park-it/park-outside flags. It stops short of stating read-only/no-side-effect semantics, latency, or rate limits, and the payment handshake behavior is only in the schema, so not a full 5.

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?

Front-loaded with the verb and the returned fields, then a second sentence for usage context, with no filler. The first sentence is a long enumeration heavy with commas, which slightly hurts scannability, but every clause carries real 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?

There is no output schema, so the description must describe returns — and it does, listing the vehicle attributes, checksum/error behavior, and recall fields in detail. It also surfaces the paid-call requirement, which an agent must know before invoking. The remaining gaps (payment failure behavior, whether recalls defaults to on) are honest omissions rather than misdirection.

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 baseline is 3. The description corroborates the 'recalls' parameter by describing the recall payload and mentions the pay-per-call flow behind 'payment_signature', but it adds no syntax, default, or format detail beyond what the schema already documents (e.g., that omitting payment_signature returns payment requirements).

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?

States a specific verb (decode) and resource (17-character VIN) and then enumerates the exact output domain: make, model, model year, trim, body class, engine, fuel, drive type, transmission, plant, checksum validation, NHTSA error notes, and safety recall campaigns. There are no sibling tools, and an agent still knows exactly what this returns without opening the schema.

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?

Explicitly names the trigger context: 'Use when an agent must identify a vehicle from its VIN ... and check open safety recalls before a purchase, listing, insurance quote or repair.' That is concrete when-to-use guidance with enumerated scenarios. No alternatives are named, but with no siblings there is nothing to route against, so this is only short of a 5 by omission of when-not conditions.

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

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

  1. 1 tool update
    • First observedvin_decode

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