ibanchecker-mcp
Server Details
IBAN validation, extraction, format specs and BIC/SWIFT lookup tools for AI assistants.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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Tool Definition Quality
Average 4.7/5 across 5 of 5 tools scored.
Tools are generally distinct: extraction, format lookup, BIC lookup, single validation, and bulk validation. However, validate_iban and validate_bulk_ibans overlap in purpose (both validate IBANs), which could cause misselection, though the bulk version is clearly for batches.
Most tools follow a verb_noun pattern (e.g., get_iban_format, lookup_bic), but extract_ibans_from_text is a longer phrase with a preposition, creating slight inconsistency. Overall, the naming is mostly predictable.
With 5 tools, the server covers the core IBAN-checking workflow (extraction, format info, BIC lookup, single and bulk validation) without superfluous tools. The count is well-scoped for the domain.
The tool set covers all essential operations for IBAN checking: extracting from text, validating individually or in bulk, retrieving format specs, and looking up BICs. There are no obvious gaps for the stated purpose.
Available Tools
5 toolsextract_ibans_from_textExtract IBANs From TextARead-onlyIdempotentInspect
Scan a free-form block of text and pull out every candidate IBAN, then validate each one.
Useful for unstructured sources such as emails, invoices, PDFs pasted as text, or chat messages where IBANs appear inline and may be split by spaces or surrounded by other words. Returns a JSON array of the IBANs found, each with its validation result (valid, countryCode, bank details when known); text containing no IBAN returns an empty list rather than an error.
Use this as the first step when the account number is buried in prose; pass the extracted IBANs to validate_bulk_ibans only if you need to re-check them separately. Input text is processed in memory and not stored.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Arbitrary text to scan for IBANs, e.g. the body of an email or invoice. IBANs may be split across spaces or embedded in sentences. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, idempotent, and non-destructive behavior. The description adds that input is processed in memory and not stored, empty text returns an empty list instead of error, and the return structure includes validation results (valid, countryCode, bank details). No contradiction with annotations.
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 compact (3 sentences plus a usage note), front-loaded with the primary action, and each sentence adds distinct value: action, use case, and behavioral details. No unnecessary words.
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 single-parameter tool with no output schema, the description adequately covers input format, edge cases (no IBANs), return structure, and processing behavior (in-memory). Sibling tools are listed, providing full context for an agent to decide when to use this tool.
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 single parameter 'text' is fully described in the input schema with the same level of detail as the tool description. With 100% schema coverage, the description adds no new parameter-specific information beyond what's already in the schema, so a baseline score of 3 is appropriate.
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 clearly states the tool's function: scan free-form text, extract candidate IBANs, and validate each. It distinguishes itself from sibling tools like validate_iban (single IBAN) and validate_bulk_ibans (re-checking) by specifying use cases.
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?
Explicitly advises when to use this tool as a first step for IBANs in prose, and when to defer to validate_bulk_ibans for re-checking. This provides clear decision guidance against siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_iban_formatGet Country IBAN FormatARead-onlyIdempotentInspect
Return the IBAN format specification for a country, covering 90 supported IBAN-using countries.
Returns JSON describing the country's total IBAN length, the BBAN layout (bank code, branch code, and account number positions and lengths), an example IBAN, and the SEPA-membership flag. Use this to understand or display how a country's IBAN is structured, to build input masks, or to explain a validation failure, not to validate a specific number (use validate_iban for that). An unsupported or unknown country code returns an error result describing the problem.
| Name | Required | Description | Default |
|---|---|---|---|
| country_code | Yes | Two-letter ISO 3166-1 alpha-2 country code, case-insensitive (e.g. 'DE' for Germany, 'GB' for the United Kingdom, 'FR' for France). |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover readOnlyHint, idempotentHint, destructiveHint. Description adds useful context: returns JSON with specific fields (length, BBAN layout, example, SEPA flag) and error handling for unsupported countries. No contradictions.
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?
Concise 4 sentences: purpose, return content, usage scenarios, error handling. No redundant 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?
With comprehensive annotations and a clear description explaining return content and error behavior, the description is complete. No output schema needed.
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 coverage is 100% with a detailed description for country_code. Description does not add extra parameter semantics beyond what the schema provides, so baseline 3 is appropriate.
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?
Description clearly states 'Return the IBAN format specification for a country', specifies 90 supported countries, and explicitly distinguishes from sibling tools like validate_iban (for validation) and extract_ibans_from_text (for extraction).
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?
Explicitly states when to use (understand IBAN structure, build input masks, explain validation failures) and when not to (validate a specific number), with a direct alternative: 'use validate_iban for that'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
lookup_bicLook Up Bank by BIC/SWIFTARead-onlyIdempotentInspect
Look up a financial institution by its BIC (Business Identifier Code, also called SWIFT code) and return the matching bank's details.
Accepts an 8-character (head office) or 11-character (branch) BIC. Returns JSON with the bank name, city, ISO country code, SEPA membership, and (when available) the official website and Wikidata entity. Use this to resolve a BIC to a human-readable bank, to confirm a SWIFT code is real, or to enrich a validated IBAN with institution details. An unknown or malformed BIC returns an error result rather than a guess; codes are never fabricated.
| Name | Required | Description | Default |
|---|---|---|---|
| bic | Yes | An 8- or 11-character ISO 9362 BIC/SWIFT code, case-insensitive (e.g. 'DEUTDEFF' or 'DEUTDEFF500'). |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate read-only, idempotent, and non-destructive behavior. The description adds details about accepted lengths, case-insensitivity, error handling for unknown codes, and that codes are never fabricated, going beyond annotations.
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 concise (two paragraphs) and front-loaded. Every sentence adds value: purpose, input format, use cases, and error behavior. No unnecessary words.
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?
Given a single parameter, no output schema, and helpful annotations, the description fully covers the tool's functionality. It lists the return fields (bank name, city, country, SEPA, website, Wikidata) and explains error handling, making it complete for selection and invocation.
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 input schema's description covers 100% of the parameter with pattern, length, and example. The tool description adds case-insensitivity and head office vs. branch context, marginally enhancing semantics.
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 title and description clearly state the tool looks up a financial institution by BIC code. It provides specific use cases (resolving BIC, confirming SWIFT, enriching IBAN) and is distinct from IBAN-related sibling tools.
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 explicitly states when to use (resolve BIC, confirm SWIFT, enrich IBAN) and what happens with invalid input (error, no fabrication). It implicitly differentiates from siblings but lacks explicit 'do not use' language.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
validate_bulk_ibansValidate Multiple IBANsARead-onlyIdempotentInspect
Validate a batch of up to 100 IBANs in one call, applying the same ISO 13616 checks as validate_iban (country, length, BBAN structure, MOD-97).
Returns a JSON array of per-IBAN results in the same order as the input, each with valid, countryCode, an optional reason for failures, and bank details when the code is recognized, plus a summary count of valid vs. invalid entries.
Use this instead of calling validate_iban in a loop when checking a list (e.g. a payment file or a column of supplier accounts). Split inputs larger than 100 into multiple calls. Account numbers are validated in memory and never stored.
| Name | Required | Description | Default |
|---|---|---|---|
| ibans | Yes | Array of 1 to 100 IBAN strings to validate. Case-insensitive; spaces are tolerated. Order is preserved in the response. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide readOnly, idempotent, non-destructive hints. Description adds that it applies ISO 13616 checks, preserves order, returns per-IBAN results with details, and states data is validated in memory and never stored.
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 front-loaded with core purpose, then provides necessary details. No unnecessary sentences.
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?
Given sibling tools and no output schema, description sufficiently explains tool's role and return structure.
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 coverage is 100%. Description adds value beyond schema by noting case-insensitivity and spaces tolerated, and order preserved.
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 clearly states it validates a batch of up to 100 IBANs using the same checks as validate_iban. It distinguishes from sibling tool validate_iban by handling bulk 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?
Explicitly says to use this instead of calling validate_iban in a loop when checking a list, and to split inputs larger than 100 into multiple calls.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
validate_ibanValidate IBANARead-onlyIdempotentInspect
Validate a single International Bank Account Number (IBAN) against the official ISO 13616 structure for its country.
What it checks: the country code, total length for that country, the national BBAN structure, and the MOD-97 check digits. When the bank/branch code maps to a known institution, the response also includes the bank name, BIC/SWIFT code, and country.
Returns JSON with fields such as valid (boolean), countryCode, checkDigitsValid, the formatted IBAN, and an optional bank object. On a malformed input the call still succeeds with valid: false and a reason (e.g. INVALID_FORMAT, INVALID_CHECKSUM); it does not throw for invalid IBANs.
Use this when you have one account number to verify. For many IBANs prefer validate_bulk_ibans; to pull IBANs out of prose use extract_ibans_from_text first. No account data is stored; validation runs in memory and is discarded.
| Name | Required | Description | Default |
|---|---|---|---|
| iban | Yes | A single IBAN to validate. Case-insensitive; spaces are tolerated and ignored (e.g. 'DE89 3704 0044 0532 0130 00' or 'GB29NWBK60161331926819'). |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Descriptive beyond annotations: details what checks are performed, output fields (valid, countryCode, checkDigitsValid, formatted, bank object), and error handling (malformed returns valid:false with reason). Annotations already indicate safety and idempotency, but description adds substantive operational detail.
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?
Description is thorough but slightly verbose; could be trimmed without losing key information. However, it is well-structured with clear paragraphs.
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?
Despite missing output schema, description explains return fields, validation steps, error behavior, and data handling (in-memory, discarded). Covers all necessary context for using the 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 covers iban with minLength 5 and description; tool description adds that it's case-insensitive and spaces are tolerated, with explicit examples. This adds clarity beyond the schema definition.
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?
Description clearly states it validates a single IBAN against ISO 13616 structure, listing specific checks (country code, length, BBAN, MOD-97). It distinguishes from siblings by mentioning validate_bulk_ibans and extract_ibans_from_text.
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?
Explicitly states when to use (single IBAN) and when not (prefer bulk for many, extract from text first). Also notes no data is stored, setting clear expectations.
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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