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Alternatives to dataloupe

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    Related Servers

    • A
      license
      Not graded
      quality
      C
      maintenance
      Zero-dependency MCP server and CLI for token-efficient inspection of local CSV/JSON/JSONL files, providing schema, samples, and paginated filtered queries to AI agents.
      MIT
    • F
      license
      Not graded
      quality
      D
      maintenance
      An MCP server that enables the analysis of CSV and Parquet files by providing tools for statistical summaries, data previews, and structure exploration. It allows users to query local datasets and create sample data using natural language.
      -
    • A
      license
      A
      quality
      A
      maintenance
      A minimal MCP server that provides a persistent DuckDB SQL engine to AI assistants, enabling natural-language querying of CSVs, Parquet, and cloud data with 12 tools and optional read-only mode.
      12
      MIT
    • A
      license
      Not graded
      quality
      A
      maintenance
      A dead-simple, self-hosted MCP server for querying your databases with AI agents.
      105 PyPI
      2
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      MCP server for sandboxed, read-only SQL queries on CSV/Parquet/JSON files via DuckDB, limited to a specified directory.
      1
      MIT

    TDQS

    A3.9/5.0

    Scored across 7 tools

    Disambiguation3/5

    Most tools are clearly distinct: listing, describing, previewing, diffing, and visualizing each have obvious roles. However, query_data and sql_query overlap heavily in functionality and both return Markdown tables, so an agent may struggle to pick between them despite the SQL versus non-SQL distinction.

    Naming Consistency4/5

    The dominant pattern is verb_data or verb_data_files: list_data_files, describe_data, preview_data, query_data, diff_data, visualize_data. sql_query breaks the pattern by being a noun phrase instead of a verb-first tool name, making it the one inconsistent outlier.

    Tool Count5/5

    Seven tools is a well-scoped set for local data exploration and comparison. Each tool covers a distinct phase of working with tabular files, and none feel redundant enough to be cut entirely.

    Completeness4/5

    The surface covers the full exploration workflow: discover files, inspect schema/stats, preview rows, query/filter/aggregate, compare files, and produce a visual artifact. Minor gaps exist, such as no way to export query results to a plain file or combine multiple data files beyond diffing, but core workflows have no dead ends.

    Maintenance

    ActivityActive
    ResponsivenessResponsive