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Check a French VAT number in VIES

check_vat
Read-only

Checks live in VIES, the European Commission's VAT register, whether a French VAT number (or the VAT number of a SIREN or SIRET) is valid, with the name and address declared for VAT, crossed with the French registry: company active, insolvency proceeding, and a name_matches consistency signal between the VIES name and the registered name (not a proof of ownership). To confirm the number belongs to a given company, compare the returned names with that company's name. Pass requester_vat (the user's own EU VAT number) to get a VIES consultation number, proof of the check. vies.status 'unavailable' means VIES could not answer: try again later, it does not mean invalid.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
numberYesFR VAT number, SIREN or SIRET; spaces allowed
requester_vatNoThe user's own EU VAT number, e.g. DE811569869, for a consultation number

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.3/5.0
Behavior5/5

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

Beyond the readOnlyHint/openWorldHint annotations, it discloses that the check is live, that name_matches is a consistency signal and explicitly not proof of ownership, and that vies.status 'unavailable' is an indeterminate result rather than an invalid one. These are exactly the behavioral caveats an agent needs to avoid misreporting results.

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?

The verb and scope are front-loaded and every sentence carries information, with no filler or restatement of the title. Sentences are long and parenthetically dense, which slightly hurts scannability.

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?

With no output schema, the description carries the return-value burden and does so: it enumerates returned fields (name, address, company active, insolvency proceeding, name_matches, vies.status). An agent has enough to call the tool and interpret its result without further documentation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3, but the description adds real meaning: requester_vat is explained as producing a consultation number that serves as proof of the check, not merely a lookup input. The accepted input forms (FR VAT, SIREN, SIRET) are already in the schema.

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: a live validity check of a French VAT number (or SIREN/SIRET VAT number) against VIES, crossed with the French registry. This is functionally distinct from siblings like get_company or validate_identifier, but no sibling is named, so it falls short of explicit differentiation.

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 gives clear operative guidance: pass requester_vat to obtain a VIES consultation number as proof, compare returned names to confirm ownership, and retry later when vies.status is 'unavailable'. It does not name or exclude any sibling tool, but the conditions for correct use are well covered.

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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