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Alternatives to AmexAnalysis-MCP

No user-submitted related servers found.

    Related Servers

    • A
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      Enables users to analyze local Excel and CSV files through natural language queries and a web dashboard while keeping data local. It supports saving specific analyses as reusable tools and building a custom analytics toolkit within Claude Desktop.
      10
      MIT
    • A
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      Not graded
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      B
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      Enables querying your own local bank and credit card statement files (CSV or PDF) in plain language, so you can discover forgotten recurring subscriptions, compare spending across months and quarters, and look up transactions without any bank logins or network calls.
      MIT
    • A
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      A
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      Enables an AI agent to analyze your own bank card invoices from Nubank CSV and Itaú PDF files, with optional read-only fetching from Gmail or Google Drive. It validates parsed totals against statement totals and provides tools for spending summaries, transaction searches, monthly comparisons, and recurring-charge detection.
      7
      MIT
    • A
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      quality
      D
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      Enables users to analyze AWS costs, track spending trends, and detect anomalies directly within Claude Desktop using the AWS Cost Explorer API. It provides tools to identify major cost drivers and compare usage across different time periods through natural language queries.
      MIT
    • A
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      AI-powered personal finance analysis through Claude AI using Plaid integration, enabling natural language queries about transactions, subscriptions, budgets, and spending trends.
      1
      MIT
    • A
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      Enables AI assistants to analyze a local bank statement CSV through seven tools covering spending by category, top merchants, recurring subscriptions, unusual or duplicate charges, end-of-month forecasts, and transaction search, plus a monthly review prompt. CSV files stay on the user's machine, with only aggregated results and matched transactions exposed to the assistant.
      7
      MIT

    TDQS

    B3.3/5.0

    Scored across 6 tools

    Disambiguation5/5

    Each tool targets a distinct analytical aspect: overall spending, subscriptions, specific vendors, anomalies, category breakdown, and export. No meaningful overlap exists between them.

    Naming Consistency4/5

    Five of six tools follow a clear verb_noun convention (analyze_*, find_*, export_*). The outlier, spending_by_category, uses a noun phrase but is still readable and not jarringly inconsistent.

    Tool Count5/5

    Six tools is a well-scoped count for a specialized spending-analysis server. Each tool covers a distinct need without redundancy or bloat.

    Completeness4/5

    The surface covers the core analysis lifecycle: overall analysis, drill-downs (vendor, category), anomaly detection, and export. Minor gaps like time-period comparison or raw transaction listing could be added, but the current set supports typical workflows.

    Maintenance

    ActivityStale
    ResponsivenessNo issues