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polylens-bilibili

by liu-xindi
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Python
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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 16 tools

    Disambiguation5/5

    Each tool targets a clearly distinct resource or action: video info vs. parts vs. frame vs. subtitles vs. danmaku are separated, and get_comments vs. get_comment_replies are explicitly differentiated (top-level vs. sub-replies). The login cluster (start_qr_login, complete_qr_login, get_login_status, logout) has separable roles despite sharing the auth theme. No tool appears to duplicate another.

    Naming Consistency5/5

    Nearly all tools follow a clean verb_noun pattern (get_comments, get_video_info, search_videos, list_up_videos, get_up_info, get_feed, get_login_status, get_danmaku, suggest_keywords). The only deviations, logout and the start/complete_qr_login pair, are standard idioms that remain predictable.

    Tool Count4/5

    16 tools is reasonable for a Bilibili content surface spanning auth, video data, and discovery, and each tool maps to a genuine operation. It sits near the upper end of comfortable scoping but does not feel padded.

    Completeness4/5

    Coverage is broad: auth lifecycle, video metadata, comments/replies, danmaku, subtitles, parts, frames, search, suggestions, feed, and uploader info. Gaps are minor — no write/interaction operations (like, favorite, follow) or related-video lookup — but core read workflows are fully supported.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues

    Resources