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bankstatemently

bankstatemently

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    Related Servers

    • A
      license
      A
      quality
      C
      maintenance
      Converts PDF bank statements into structured data (Markdown, JSON, CSV, JSONL) with verified transactions and balance checks, enabling agents to audit numbers.
      5
      3 npm
      MIT
    • A
      license
      C
      quality
      D
      maintenance
      Provides deterministic data parsing and enrichment for AI agents, including bank statements, trade history, EDI, PDFs to structured markdown, and atomic enrichment for amounts, dates, and addresses, with strict schema enforcement to prevent hallucinations.
      37
      24 npm
      2
      ISC
    • A
      license
      A
      quality
      A
      maintenance
      Converts customer-supplied PDF bank statements into checked Excel, CSV, or JSON with balance validation. Runs locally with your own MainBook API key or against MainBook's hosted endpoint, and it never connects to bank accounts.
      5
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      Deterministic bank-statement parsing for AI agents: messy CSV/OFX exports to clean, categorized ledger rows. In-memory only, no storage, no external calls, no LLM in the loop.
      MIT
    • F
      license
      Not graded
      quality
      D
      maintenance
      Financial data infrastructure for AI agents. Connect to a startup's books to read live P&L and bank balances, review and reclassify transactions, manage the chart of accounts, and connect banking sources.
      -

    TDQS

    A4/5.0

    Scored across 16 tools

    Disambiguation4/5

    Most tools have clearly distinct responsibilities: ingestion (convert_statement, request_upload), retrieval (get_statement, list_statements), analysis (aggregate, group_by, top_n, compare, time_series), and management (rate_statement, dismiss_statement, categorize_statement). The six analytics tools share similar scope/metric language and could occasionally be confused, but their descriptions are explicit enough to disambiguate.

    Naming Consistency3/5

    The statement lifecycle tools follow a consistent verb_noun pattern (convert_statement, get_statement, list_statements, dismiss_statement, rate_statement, categorize_statement). However, the analytics tools break this pattern with bare verbs and phrases like aggregate, compare, group_by, top_n, and time_series, making the overall naming convention mixed but still readable.

    Tool Count4/5

    At 16 tools, the server is slightly above the ideal 3-15 range but each tool earns its place across ingestion, document management, analytics, transfers, credits, and benchmarking. The count feels justified for the domain breadth, though a few analytics tools could theoretically be consolidated.

    Completeness4/5

    The domain is well covered: conversion, upload, retrieval, listing, rating, categorization, dismissal, transaction queries, aggregations, transfer matching, credits, and benchmark evaluation are all present. Minor gaps exist, such as no permanent delete (dismiss only hides) and no dedicated account-list endpoint, but these are workable and not core dead ends.

    Maintenance

    ActivityActive
    ResponsivenessNo issues