validate_vatValidate a European VAT number against the EU VIES register (keyless deterministic lookup of the European Commission checkVatService). Price: 0.005 USDC per call (x402, Base). Resource: https://api.exo-trust.com/execute/validate_vat. Returns the payment challenge unless already settled.
| Name | Required | Description | Default |
|---|---|---|---|
| vat_number | Yes | ||
| country_code | No |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the behavioral burden. It adds useful operational details: keyless deterministic lookup, price, resource URL, and payment challenge behavior. However, it does not explain what happens after settlement, error cases, or authorization requirements.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three concise sentences, with the purpose front-loaded and each subsequent sentence carrying an operational detail: price, resource, and return behavior. No filler or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema exists, and the payment workflow is underspecified. 'Returns the payment challenge unless already settled' leaves the settled case and actual validation result unclear, which an agent needs to invoke this paid tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It identifies vat_number as a European VAT number, but never mentions country_code, its optionality, or its default behavior. The compensation is incomplete.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb and resource: 'Validate a European VAT number against the EU VIES register.' This clearly distinguishes the tool from all siblings, none of which target VAT validation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The context for use is explicit: validate European VAT numbers via VIES. However, there is no mention of when not to use it or any alternatives, though none of the sibling tools appear to be close substitutes.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools have clearly distinct purposes, but edgar_financials and edgar_report overlap heavily, with the report apparently building on the same financial data. The three registry lookups (sanctions, VAT, LEI) are distinct, and the text-processing tools are separable.
Naming is inconsistent: some tools use bare verbs (classify, extract, proofread, rewrite, summarize, translate), some use verb_noun (check_sanctions, lookup_lei, validate_vat, code_explain), and others use domain-based names (clinical_dd, edgar_financials, edgar_report, synergy_discovery). No single consistent convention is applied.
14 tools is within the reasonable range and each covers a distinct specialist area, but the set feels slightly broad and includes a few near-duplicates (edgar_financials vs edgar_report). It is not excessive, though tightening could improve focus.
The catalog covers a wide range of domains: sanctions, VAT, LEI, SEC filings, clinical trials, code analysis, text transformation, and discovery. It includes a discovery tool to enumerate specialists, which helps. Minor gaps like missing update/delete-style operations are not expected for a read-only specialist API, so coverage is strong.