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cammac-creator/ibanforge-mcp

by Various

IBANforge — IBAN validation, BIC/SWIFT lookup, Swiss clearing, and EMI/vIBAN classification API with MCP for AI agents

C

MCP

cammac-creator/ibanforge-mcp

Added 13 July 2026

#ai-agents #api #banking #bic #compliance #fintech #hono #iban

Overview

IBANforge is an MCP server that provides IBAN validation, BIC/SWIFT lookup, Swiss clearing number handling, and EMI/vIBAN classification. It exposes these financial data lookups via the Model Context Protocol so AI agents can integrate them directly.

Best for

Best for
Developers building AI agent workflows that need to validate and classify European banking identifiers

Use cases

  • Validate IBAN numbers in automated payment or onboarding workflows
  • Look up BIC/SWIFT codes to confirm bank routing for cross-border transfers
  • Classify accounts as EMI or virtual IBAN for compliance and screening

Notes

IBANforge is an MCP server that provides IBAN validation, BIC/SWIFT lookup, Swiss clearing number handling, and EMI/vIBAN classification. It exposes these financial data lookups via the Model Context Protocol so AI agents can integrate them directly.

1 stars on GitHub. Last updated 2026-07-13. Licensed MIT.

Use cases

  • Validate IBAN numbers in automated payment or onboarding workflows
  • Look up BIC/SWIFT codes to confirm bank routing for cross-border transfers
  • Classify accounts as EMI or virtual IBAN for compliance and screening

Pros

  • Covers IBAN, BIC, Swiss clearing, and EMI classification in one tool
  • Straightforward MCP integration for AI agent pipelines
  • Written in TypeScript with typed responses for predictable parsing

Cons

  • Very new project with only 1 star and limited community validation
  • Requires running a separate MCP server, adding deployment overhead
  • Documentation and test coverage may be sparse

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Covers IBAN, BIC, Swiss clearing, and EMI classification in one tool
  • Straightforward MCP integration for AI agent pipelines
  • Written in TypeScript with typed responses for predictable parsing

Cons

  • Very new project with only 1 star and limited community validation
  • Requires running a separate MCP server, adding deployment overhead
  • Documentation and test coverage may be sparse
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