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KYB check: sanctions (OFAC, EU, UK) + LEI identity + EU VAT validation in one call

kyb_check

Use when an agent must vet a company or counterparty before paying, onboarding or invoicing. Input: name, optional country (ISO2), lei, vat (EU, with prefix). Output: JSON summary (sanctions hits, LEI found/status, VAT valid), sanctions matches across OFAC SDN, EU and UK lists, GLEIF entity record with parents, VIES VAT result; a down VIES/GLEIF marks only that part. Not a legal determination. Example: ?name=Siemens+AG&lei=W38RGI023J3WT1HWRP32&vat=DE129273398 Price: $0.02 USDC (Base or Solana) via x402.

Input Schema

NameRequiredDescriptionDefault
leiNoLegal Entity Identifier, if known (exact LEI lookup instead of name search)
vatNoEU VAT number with country prefix (Greece = EL), validated in VIES
nameYesCompany or person name in Latin script
countryNoISO 3166-1 alpha-2 country of the legal address (narrows the LEI search)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations, the description carries the burden well: it discloses the return summary, the specific sanctions lists, GLEIF parent data, VIES results, partial-failure behavior ('a down VIES/GLEIF marks only that part'), the legal disclaimer, and the x402 payment cost/rails. It stops short of rate limits, caching, or idempotency details.

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 use case and structured into input/output/example/price. Dense but largely purposeful; the long output enumeration could be tightened slightly.

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 four-parameter tool with no output schema, the description explains what comes back (sanctions hits, LEI status, VAT validity, GLEIF parents), partial failure behavior, and payment requirements. An agent has enough to invoke and interpret it correctly.

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 schema already documents name, country, lei, and vat with useful descriptions. The description restates inputs and adds a worked example, but does not add semantics beyond the schema (e.g., matching behavior for names or format nuances for lei/vat).

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 specific verbs and resources: vet a company/counterparty with sanctions (OFAC/EU/UK), LEI, and EU VAT checks. The combined scope clearly distinguishes it from single-purpose siblings like sanctions_address or sanctions_screen.

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 says when to use it: before paying, onboarding, or invoicing. It does not name alternative tools or when-not-to-use cases, but the context is clear.

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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