FREE, no payment required: validate an IBAN (checksum and country structure, all countries) and identify BIC/bank name where the local registry has data. Registry data never proves account ownership or existence.
| Name | Required | Description | Default |
|---|---|---|---|
| iban | Yes |
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 present, the description carries the full disclosure burden. It goes beyond the tool name by revealing that registry data is not always available and explicitly warns that it 'never proves account ownership or existence'. This is valuable, well-communicated behavioral context.
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?
Two dense sentences contain all key information: free access, validation scope, registry-linked BIC/bank lookup, and an important limitation. The content is front-loaded and there is almost no wasted text.
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?
For a one-parameter tool without an output schema, the description does a solid job: it explains what will be validated, what extra data may be returned, and a critical limitation. The main remaining gap is an explicit statement of the output format or return contract, which the agent has to infer from the validation context.
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?
The schema describes only 'iban' as a string with zero description coverage, so the description must compensate. It names the content of the parameter implicitly ('validate an IBAN'), but it does not specify expected formatting (spaces, uppercase, country prefix) or acceptable variants. It adds some but not full meaning beyond the schema.
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 states a specific verb ('validate') and resource ('IBAN'), scopes it to 'checksum and country structure, all countries', and adds a secondary behavior ('identify BIC/bank name where the local registry has data'). This clearly distinguishes it from siblings like validate_vat or validate_einvoice_eu.
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 description makes the usage context clear: this is a free, full-country IBAN validation tool that may also return BIC/bank info. It does not explicitly name when to prefer an alternative, but 'validate an IBAN' plus 'all countries' gives the agent enough context to choose it over VAT/company/entity tools.
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.
Many tools are clearly separate (validate_vat, validate_iban, token_status, tx_status), but several overlap by combining the same core checks: check_counterparty_eu, must_verify_before_pay, tx_preflight, and invoice_to_pay_dossier_eu all screen sanctions and/or do VIES/IBAN checks. The descriptions help, but the boundaries between a KYB check, a payment gate, and a transaction preflight are subtle enough that agents can easily pick the wrong one.
Names are uniformly lowercase snake_case, and patterns like validate_*, prepare_*, and *_eu give some predictability. However, the verb style is inconsistent: some tools are verb-led (read_url, screen_sanctions_eu, lookup_company_eu), others are noun-led (market_data, token_status, agentllm_micro), and paid/prepare pairs do not share a consistent naming scheme.
24 tools is at the upper edge of what is reasonable, and the server mixes several unrelated concerns: EU VAT/invoice compliance, sanctions/KYB, US import readiness, AI disclosure/LLM inference, market data, URL reading, and transaction status. The core comply-to-pay workflow is well represented, but the extra domains make the tool list feel heavier and less like a single coherent service.
The EU invoice/payment compliance flow is fairly complete: e-invoice validation, VAT rules, VIES, IBAN, sanctions, transaction preflight, payment decisions, bookkeeping statements, and receipt verification are all covered. Obvious gaps remain for such a broadly named server: no export/other product compliance, no broader EU regulatory coverage, and the key invoice guard explicitly does not cover duplicate-ledger detection, internal approval, or delivery checks.
