Generate structurally valid test IBANs (correct mod-97 check digits) for NL, DE, BE, FR, or GB that belong to no real bank account. For development and test data only.
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | ||
| country | No | NL |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description correctly carries the behavioral burden. It discloses that the output is structurally valid, has correct check digits, is restricted to five countries, and is intentionally unlinked to real bank accounts. For a pure generation tool this covers the main risks.
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?
The description is two short sentences with no filler. The core behavior is front-loaded, followed by the supported countries and the test-only caveat. Each clause contributes distinct and useful information.
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?
The description covers what is generated, the supported countries, the technical guarantee about check digits, and the intended test-data use. The main gap is the return format, since no output schema exists and the description does not say whether the tool returns a single IBAN string or an array when count is used.
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 needs to compensate for parameter meaning. It restates the country enum in prose and implies the count parameter via the plural 'IBANs', but it does not explicitly explain that count controls the number of returned IBANs. The schema's min, max, default, and enum still provide useful structure.
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: 'Generate structurally valid test IBANs'. It enumerates the supported countries, emphasizes correct mod-97 check digits, and explicitly states the output belongs to no real bank account. This makes the tool easy to distinguish from validation and other generation siblings.
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 gives clear when-to-use and when-not-to-use guidance: 'For development and test data only' and 'belong to no real bank account'. It does not name an alternative sibling explicitly, but the closest siblings differ in verb or data type, so the omission is minor.
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 some pairs could be confused: html_to_pdf vs url_to_pdf both produce PDFs, read_page vs url_screenshot both fetch a URL, and generate_test_bsn vs generate_brp_test_data both generate Dutch test data. Detailed descriptions mitigate most ambiguity, so agents can usually select correctly.
All tool names follow a consistent snake_case convention with predictable verb_noun patterns (e.g., generate_*, validate_*, memory_*, url_*). The naming is uniform and makes each tool's function easily inferable from its name.
35 tools is a heavy surface for any MCP server, even a general-purpose toolbox. The large number of niche Dutch-specific tools (BRP, UPA, BSN, holidays) may overwhelm agents and increase selection complexity. The server could benefit from splitting into smaller, focused servers.
The server covers a wide range of utilities, but there are notable gaps: no hash generation, no json_to_csv counterpart, and the workflow sub-domain only offers list/run without create/delete. Core utilities are present, but some obvious counterparts and lifecycle operations are missing.