toolforte

IBAN Validator

validate_iban

Read-onlyIdempotent

Check whether an IBAN is well formed: the mod-97 checksum, the country code, the length that country's IBAN must have, and whether every position holds the kind of character that country allows there (mod-97 turns letters into numbers, so on its own it cannot see a capital O typed in place of a zero). Returns validity, country, and where known the bank identifier printed inside the IBAN. This is a format check, not a bank check: a passing IBAN can still name a bank code that never existed or has since merged away, and says nothing about whether the account exists or can receive a payment. For twelve countries it also verifies the national check digit that the bank computes over the bank code and account number (BE, FR, MC, ES, IT, SM, PT, SI, PL, TN, EE, HU); nationalCheck 'failed' there means the number is very probably invented, since that digit cannot be back-computed the way the mod-97 pair can. Absent nationalCheck means not checked, never approved. For Dutch IBANs it also names the institution behind the four-letter bank code, including codes that no longer issue accounts; an unrecognised code does not make the IBAN invalid. A territory that borrows another country's IBAN (Reunion, Guernsey, Aland and the like) is reported with the prefix it actually uses, since no IBAN starts with RE or GG. Never guess whether an IBAN is well formed: use this tool. Do not present a pass as confirmation that money can be sent.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`iban`	Yes	The IBAN to validate

Output Schema

TableJSON Schema

Name	Required	Description
`iban`	No
`valid`	No	Whether the input passed every check
`result`	No	The result, when it is not an object
`country`	No
`bankCode`	No
`checkDigits`	No
`countryName`	No
`institution`	No
`accountNumber`	No

Schema Changelog

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

Changed1 schema field changedSep 5, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "$schema": "https://json-schema.org/draft/2020-12/schema",
+  "additionalProperties": {},
+  "properties": {
+    "accountNumber": {
+      "type": "string"
+    },
+    "bankCode": {
+      "type": "string"
+    },
+    "checkDigits": {
+      "type": "string"
+    },
+    "country": {
+      "type": "string"
+    },
+    "countryName": {
+      "type": "string"
+    },
+    "iban": {
+      "type": "string"
+    },
+    "institution": {
+      "additionalProperties": {},
+      "properties": {
+        "kind": {
+          "type": "string"
+        },
+        "name": {
+          "type": "string"
+        }
+      },
+      "type": "object"
+    },
+    "result": {
+      "description": "The result, when it is not an object"
+    },
+    "valid": {
+      "description": "Whether the input passed every check",
+      "type": "boolean"
+    }
+  },
+  "type": "object"
+}

First observedSep 1, 2026

TDQS

A3.9/5.0

Behavior5/5

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

Annotations already mark this as read-only and idempotent, so the description's job is to add behavioral nuance. It does this richly: mod-97 cannot catch a capital O substituted for zero, nationalCheck only applies to twelve listed countries, and a passing IBAN can still reference a non-existent bank. This is far beyond what annotations alone provide.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The first half is dense and valuable, but the description becomes bloated near the end. The sentence about 'A territory borrows another country's IBAN prefix' is confusing and ungrammatical, and the final two admonitions largely repeat the earlier 'format check, not a bank check' caveat. The definition would be stronger if trimmed after 'Absent nationalCheck means not implemented.'

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?

The description covers return values (validity, country, bank identifier, nationalCheck), explains the main false-positive risk, and even mentions an edge case about territory IBAN prefixes. Combined with the single parameter and existing output schema, an agent has enough context to invoke the tool correctly, though the confusing tail adds noise.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and the only parameter is documented as 'The IBAN to validate,' so the baseline is 3. The description adds useful semantic context about what well-formed means, but it does not specify input formatting details such as uppercase requirements or whether spaces are accepted.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

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: 'check whether an IBAN is well formed,' and enumerates the exact validation dimensions (mod-97, country code, length, character rules). It clearly separates itself from a bank or account check, though it does not explicitly distinguish sibling tools.

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 when-to-use guidance ('Never guess whether an IBAN is well formed: use this tool') and when-not-to-interpret guidance ('This is a format check, not a bank check'). It does not name alternative sibling tools, but none are direct IBAN-validation equivalents.

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

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

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