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madhusudan-kulkarni

biotools-mcp

by madhusudan-kulkarni
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Python
Hybrid

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    TDQS

    A4/5.0

    Scored across 11 tools

    Disambiguation5/5

    Each tool has a distinct purpose within its domain. The seq_* tools cover motif scanning, GC content, reverse complement, translation, ORF finding, and sequence stats with no overlap. The stats_* tools cover descriptive statistics, t-test, chi-square, Mann-Whitney, and correlation, also without ambiguity. The two domains are clearly separated by prefix and description.

    Naming Consistency4/5

    Tool names follow a consistent domain-prefix pattern: seq_ for sequence operations and stats_ for statistical tests. However, within each prefix, the naming style is mixed (e.g., seq_translate is a verb, seq_orf_finder is a noun; stats_describe is a verb, stats_t_test is a noun). This minor inconsistency lowers the score from 5 to 4, but the prefix convention makes names predictable.

    Tool Count5/5

    With 11 tools, the server is well-scoped for a bioinformatics toolkit. It covers a reasonable set of sequence analysis functions and common statistical tests without being bloated. The count falls well within the ideal range for a focused utility server.

    Completeness4/5

    The tool surface covers core sequence operations (translation, reverse complement, GC content, motif scanning, ORF finding, and stats) and common statistical tests (descriptive, t-test, chi-square, Mann-Whitney, correlation). Minor gaps exist, such as sequence alignment or advanced statistical tests like ANOVA, but agents can perform most basic workflows without dead ends.

    Maintenance

    ActivityMaintained
    ResponsivenessSyncing

    Resources