Temsor API — Turkey & EU business data

EU VAT Number Validation

eu_vat_validate

Validates an EU VAT number against the official VIES register, with per-country format checks and honest handling of upstream outages.

VIES is free but unreliable: member-state services drop out individually and a failed lookup can easily be mistaken for a rejection. Treating an outage as "invalid" means charging VAT to a customer who should have been exempt — an error with a price tag. So this endpoint never returns invalid when the service could not answer; it returns unknown and names the reason, and reports whether that country's service is currently up. Format is checked locally first, so an obvious typo never becomes an upstream call. Results are cached for 24 hours. Note that most member states do not publish the company name; when they do, it is returned.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`vatNumber`	Yes	VAT number with or without the country prefix, e.g. "DE811907980".
`countryCode`	No	Country code, when the number is given without a prefix.

TDQS

A4.6/5.0

Behavior5/5

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

With no annotations, the description fully discloses key behaviors: local format check first, never returning 'invalid' on outage, returning 'unknown' with reason, reporting country service status, 24-hour caching, and company name when available.

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, well-structured, and front-loaded with the main purpose, followed by essential behavioral details without unnecessary repetition.

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?

For a tool with no output schema, the description covers return values (unknown, reason, service status, company name) adequately, though it does not list all fields explicitly.

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 description coverage is 100%, and the description adds clarifying examples and the relationship between vatNumber and countryCode, enhancing understanding 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 clearly states the tool validates an EU VAT number against the VIES register, with per-country format checks. It is distinct from sibling tools like email_verify or iban_validate.

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?

The description provides clear context on when to use (for EU VAT validation) and explains behavior during outages, but lacks explicit exclusions or direct comparisons to other tools.

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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TDQS

A4/5.0

Disambiguation4/5

Most tools have clearly distinct purposes (e.g., bic_validate vs vin_validate), but there is notable overlap: tr_validate bundles Turkish validations that are also covered individually by iban_validate and tin_validate. Also, lei_validate and lei_lookup are closely related but distinct enough. Overall, agents can usually pick the right tool, but a few pairs could confuse.

Naming Consistency4/5

Tool names are consistently snake_case with predominately verb_noun patterns (e.g., validate, lookup, screen, parse, build). Some nouns like mcp_index, model_archive, and series_history break the verb pattern but are still predictable. Minor deviations from the noun_verb form (tr_invoice_build, shipping_identify) don't cause confusion. Very readable and consistent overall.

Tool Count3/5

With 27 tools, the set is heavy, exceeding the typical 3–15 well-scoped range. However, the server covers a broad domain: international standards validation, Turkey-specific business data (fuel, labor, invoices, addresses), and even MCP/LLM model archives. The count is justifiable given the scope, but it stretches coherence and may overwhelm agents.

Completeness4/5

The tool surface is remarkably comprehensive for the stated Turkey & EU business data purpose: validators for most ID types, VAT, IBAN, phone, VIN, sanctions; plus Turkey-specific operations like invoice build/parse, labor calculations, fuel prices, business days, and address parsing. Minor gaps exist (e.g., no general exchange-rate conversion, no credit-note-specific builder), but agents can accomplish core workflows without dead ends.

Resources

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