toolforte

Test IBAN Generator

generate_test_iban

Read-only

Generate structurally valid test IBANs for NL, DE, BE, FR, or GB that belong to no real bank account. Each one carries the country's own character layout, correct mod-97 check digits, and for Belgium and France the national check digit the bank computes over the account, so it also passes validate_iban in full. For development and test data only.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`count`	No	How many test IBANs to generate, 1 to 100 (default 1)
`country`	No	Country code of the IBAN layout: NL, DE, BE, FR or GB (default NL)	NL

Output Schema

TableJSON Schema

Name	Required	Description
`note`	No
`count`	No	Number of items
`ibans`	No
`result`	No	The result, when it is not an object
`country`	No

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

Changed3 schema fields changedSep 5, 2026

addedInput schema / properties / count / description

Added value: +"How many test IBANs to generate, 1 to 100 (default 1)"

addedInput schema / properties / country / description

Added value: +"Country code of the IBAN layout: NL, DE, BE, FR or GB (default NL)"

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "$schema": "https://json-schema.org/draft/2020-12/schema",
+  "additionalProperties": {},
+  "properties": {
+    "count": {
+      "description": "Number of items",
+      "type": "number"
+    },
+    "country": {
+      "type": "string"
+    },
+    "ibans": {
+      "items": {},
+      "type": "array"
+    },
+    "note": {
+      "type": "string"
+    },
+    "result": {
+      "description": "The result, when it is not an object"
+    }
+  },
+  "type": "object"
+}

First observedSep 1, 2026

TDQS

A4.5/5.0

Behavior4/5

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

Beyond the readOnlyHint=true annotation, the description discloses meaningful behavior: correct mod-97 check digits, country-specific layouts, and the national check digit for BE and FR. It also states that the output passes validate_iban in full, which is useful behavioral context for an agent deciding whether this output is fit for purpose.

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 two sentences with no filler. It front-loads the core action and scope, then adds the validation/check-digit details, and closes with a clear usage restriction. Every sentence earns its place.

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 generator with only two optional, fully documented parameters and an output schema, the description covers what an agent needs: scope, validity guarantees, non-production intent, and the relationship to validate_iban. No critical behavioral gaps remain.

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 coverage is 100%, so the baseline is 3, but the description adds real value beyond the schema by explaining what the country parameter controls: country-specific layout, mod-97 check digits, and BE/FR national check digits. This helps an agent reason about country-dependent behavior rather than just treating country as an enum value.

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 opens with a specific verb and resource: 'Generate structurally valid test IBANs' for a defined set of countries. It clearly states the generated IBANs belong to no real bank account and explicitly connects to validate_iban, making the tool's role and boundary unmistakable.

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 gives clear usage context: 'For development and test data only' and notes the IBANs are not tied to real accounts, which acts as an exclusion of production use. It does not explicitly contrast with sibling generators like generate_test_bsn, but the tool name and content make the intended scenario clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All toolforte tools Inspect

Try in Browser

RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.8/5.0

Disambiguation5/5

Every tool targets a distinct resource or action, and the detailed descriptions clearly separate near neighbors like generate_test_bsn versus generate_brp_test_data, read_page versus url_screenshot versus url_to_pdf, and image_compress/convert/resize. Even with 40 tools, there is no real boundary-blurring overlap.

Naming Consistency3/5

All names are snake_case and readable, but the set mixes conventions: verb_noun (generate_*, validate_*), noun_verb (pdf_merge, image_resize), conversion-style names (csv_to_json, html_to_pdf), and bare nouns (base64, qr_code_png). The groups are recognizable, but there is no single predictable pattern.

Tool Count2/5

Forty tools is an oversized surface for an agent to consider on every call, well above the point where tool selection cost starts to hurt. The broad purpose explains the count, but many one-off utilities could be grouped or exposed selectively.

Completeness3/5

The server covers many domains—encoding, Dutch test data, image/PDF handling, memory, and workflows—but several categories are partial: there are no reverse conversions like json_to_csv or html_to_markdown, no PDF text extraction, and no workflow create/update/delete tools. Agents can work around some gaps, but notable operations are missing.

Resources

Need Help?