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book-recommendations

by surendranb
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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

    B3.2/5.0

    Scored across 5 tools

    Disambiguation5/5

    Each tool serves a clearly distinct purpose: recommend provides targeted recommendations, blind_date offers random serendipity, free_classics surfaces public-domain works, and skills_list/skill_read manage usage guidance. No overlap or ambiguity exists between the tools.

    Naming Consistency2/5

    Tool names follow no consistent pattern: 'recommend' is a bare verb, 'blind_date' and 'free_classics' are noun phrases, while 'skills_list' is a noun-noun compound and 'skill_read' reverses the typical verb-object order. This mixed convention could cause confusion about expected behavior.

    Tool Count5/5

    With just 5 tools, the server is tightly scoped for its domain. Each tool adds distinct value without redundancy, and the count is well within the ideal range for a focused MCP server.

    Completeness4/5

    The core recommendation workflows are covered: tailored recommendations, serendipitous discovery, and access to classics. However, missing operations like fetching book details or saving favorites create minor gaps, though agents can likely work around them for most use cases.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues

    Resources