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ppikkuaho

movie-rec

by ppikkuaho
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Python
Hybrid

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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

    B3.3/5.0

    Scored across 8 tools

    Disambiguation5/5

    Each tool has a clearly distinct purpose: resolving titles, adding evidence, retrieving context, generating candidates, recording recommendations, fetching history, recording reactions, and discovering titles. No two tools appear to overlap in functionality, and the descriptions provide strong differentiation.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern: resolve_title, add_evidence, get_evidence_context, get_candidates, record_recommendations, get_recommendation_history, record_reaction, discover_titles. The pattern is systematic and predictable, making tool selection straightforward.

    Tool Count5/5

    With 8 tools, the server is well-scoped for its purpose of movie recommendation and user feedback. Each tool addresses a distinct part of the workflow without redundancy, and the count is within the typical well-scoped range (3-15).

    Completeness4/5

    The tool set covers the core lifecycle: resolving user inputs, adding evidence, generating candidates, recording recommendations, retrieving history, and capturing reactions. Minor gaps exist (e.g., no explicit delete/update for evidence or reactions), but these are not critical for the main recommendation flow and can be worked around.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues

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