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Data File Analysis MCP Server

by llm-guy
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Python

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    TDQS

    B3.3/5.0

    Scored across 2 tools

    Disambiguation3/5

    The two tools are clearly distinct by file type (Parquet vs CSV), so an agent should be able to tell them apart when the file format is known. However, they share the identical purpose and structure (summarizing file dimensions), and there is no unified or generic tool to handle either format, which could cause confusion if an agent must guess the format.

    Naming Consistency4/5

    Both tools follow the same verb_noun pattern (summarize_parquet_file, summarize_csv_file), sharing the identical 'summarize' verb and 'file' suffix. The only variation is the file format in the middle, which is consistent and predictable, though the format should ideally be a parameter rather than baked into the tool name.

    Tool Count3/5

    With only 2 tools, this sits at the boundary of 'too few.' It's not a single trivial tool, but two near-identical tools covering only file summarization feels thin for a 'Data File Analysis' server, which implies a much broader analysis scope than just counting rows and columns.

    Completeness2/5

    For a server named 'Data File Analysis,' this surface is severely limited: there is no way to read, sample, filter, compute statistics, inspect columns/types, or join files. Even for a narrow summarization-only scope, neither tool supports inspecting column schemas or data previews, leaving significant gaps that will cause agent failures for common analysis tasks.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues

    Resources