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goodreads-mcp-ai

by Danathar
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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

    A4.5/5.0

    Scored across 12 tools

    Disambiguation5/5

    Each tool targets a distinct Goodreads resource or relation (search, book details, editions, lists, popular chart, shelves, reviews, similar/author/series books, compare). The 'related books' tools could superficially overlap, but descriptions clearly specify different data sources and use cases.

    Naming Consistency4/5

    All names use snake_case, but the set mixes verb_noun (get_book, search_books, compare_books, list_shelves) with noun_books (book_lists, popular_books, similar_books, author_books, series_books). The pattern is readable and largely predictable, with only minor stylistic drift.

    Tool Count5/5

    Twelve tools is a well-scoped set for a Goodreads MCP: enough to cover search, details, reviews, shelves, lists, editions, and related books without bloat. Each tool clearly earns its place.

    Completeness4/5

    Core read-only workflows are covered: book search/details, editions, reviews, similar/author/series discovery, shelves, Listopia, popular charts, and comparison. Minor gaps exist, such as direct author search by name or retrieving all books in a Listopia list, but agents can work around them via existing tools.

    Maintenance

    ActivityActive
    ResponsivenessResponsive

    Resources