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African Speech Corpora MCP

by papasega
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Python
Remote

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    Deploy Server
    One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

    TDQS

    A3.5/5.0

    Scored across 8 tools

    Disambiguation5/5

    Each tool targets a distinct operation: listing variants, searching segments, getting stats, citing, auditing, planning, filtering, and comparing. Though search_segments and filter_segments both work on segments, their preconditions and purposes are clearly different—search is free-form with overrides, while filter requires a versioned audit manifest. No two tools appear interchangeable.

    Naming Consistency4/5

    Most tools follow a clear verb_noun pattern (list_corpora, search_segments, cite_corpus, audit_corpus, plan_training_set, filter_segments, compare_corpora). The outlier is 'corpus_stats' which uses noun_noun instead of a get/stats verb, breaking the pattern slightly. This is a minor deviation that doesn't hinder readability.

    Tool Count5/5

    With 8 tools, the server is well-scoped for its domain of managing and analyzing African speech corpora. Each tool addresses a distinct aspect of the workflow without redundancy or bloat. The count feels just right—not too thin, not overwhelming.

    Completeness5/5

    The tool surface covers the core lifecycle of corpus exploration and usage: discovering corpora, searching segments, retrieving stats, citations, audit metrics, planning training sets, filtering based on audits, and comparing variants. There are no glaring gaps such as missing download or update operations, as the focus is analysis rather than modification. The server fulfills its stated purpose comprehensively.

    Maintenance

    ActivitySlowing
    ResponsivenessNo issues

    Resources