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Alternatives to yt-analysis-mcp

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    TDQS

    A3.8/5.0

    Scored across 5 tools

    Disambiguation5/5

    Each tool has a clearly distinct purpose with no ambiguity: ask_about_video answers questions about content, extract_frames extracts frames at user-provided timestamps, extract_screenshots uses AI to find and extract key frames, get_video_timestamps previews AI-identified timestamps, and summarize_video provides text summaries. The descriptions explicitly differentiate their use cases, such as distinguishing between extract_frames (manual timestamps) and extract_screenshots (AI-selected timestamps).

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern with underscores, using clear action verbs like ask_about, extract, get, and summarize paired with descriptive nouns like video, frames, screenshots, and timestamps. There are no deviations in style or convention, making the set predictable and easy to understand at a glance.

    Tool Count5/5

    With 5 tools, the count is well-scoped for the YouTube analysis domain, covering core workflows like content querying, frame extraction (both manual and AI-driven), timestamp previewing, and summarization. Each tool earns its place without redundancy, and the number is manageable for agents to navigate effectively.

    Completeness4/5

    The tool set provides strong coverage for video analysis, including content understanding, visual extraction, and summarization, with no dead ends. A minor gap exists in lacking direct video metadata retrieval (e.g., title, duration, uploader), but agents can work around this by using existing tools like ask_about_video or summarize_video for such information.

    Maintenance

    ActivityStale
    ResponsivenessNo issues