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Alternatives to jp-zengin-name

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    Related Servers

    • A
      license
      A
      quality
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      Enables AI agents to validate a Japanese qualified invoice against the six required items, reduced-rate markings, per-rate totals, and once-per-invoice-per-rate tax rounding, while flagging the common line-by-line rounding mistake, and to normalize and verify T + 13-digit registration numbers. Read-only tools also compute expected consumption tax for a given amount, rate, price basis, and rounding method.
      3
      MIT
    • A
      license
      A
      quality
      C
      maintenance
      Japan-specific utilities for AI agents — era ↔ Western year conversion, kanji-to-romaji, postal code lookup, national holidays, kana conversion, and Japanese name splitting. 9 tools, MIT licensed, install via uvx.
      9
      MIT
    • A
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      quality
      D
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      Enables AI assistants to perform Japanese business calendar calculations including holiday detection, business day arithmetic, payment date settlement, and deadline management using local data.
      6
      MIT
    • A
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      quality
      A
      maintenance
      Enables AI agents to build and parse VietQR payments, convert old 63-province addresses to the 34-province structure, validate tax IDs and e-invoices, turn money amounts into Vietnamese words, and convert between solar and lunar calendar dates. All tools run offline with bundled data, returning structured ok/error results.
      MIT
    • A
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      Enables AI agents to verify that every number, money amount, percentage, count, date and time in an AI-written Japanese summary or meeting minutes actually appears in the source text, normalizing kanji numerals, 万/億, full-width digits, Japanese era years, 午前/午後 times and 割/分 rates before comparison. Exposes a read-only check tool that reports each fact as supported, approximate, mismatched or unsupported, plus an extraction tool that lists the quantities in a text.
      2
      1
      MIT
    • A
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      Enables AI assistants to access and compare Japanese public data from e-Stat, corporate registration, real estate, and invoice APIs, automatically converting codes into human-readable formats with sources and timestamps.
      14
      36 PyPI
      12
      MIT

    TDQS

    A4/5.0

    Scored across 3 tools

    Disambiguation5/5

    Each tool targets a distinct action on Zengin names: matching two names, formatting a name into Zengin form, and validating an existing Zengin name. The boundaries between format (produce) and check (validate) are clear from the descriptions, so an agent can select the right tool without ambiguity.

    Naming Consistency5/5

    All three tools follow the same predictable pattern: a shared `zengin_name_` prefix plus a distinct action verb (`match`, `format`, `check`). There is no mixing of conventions or vague verbs.

    Tool Count5/5

    Three tools are well-scoped for a narrow domain focused on Japanese Zengin name handling. Each tool covers a distinct operation and none feels redundant or missing for the stated purpose.

    Completeness5/5

    The surface covers the core lifecycle: match payer/customer names, format names to Zengin standards, and validate Zengin names from files. Together these operations form a complete workflow for the domain without obvious gaps.

    Maintenance

    ActivityMaintained
    ResponsivenessSyncing