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Gemini-Video-MCP

by SolenmeChiara
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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

    A4.9/5.0

    Scored across 5 tools

    Disambiguation5/5

    Each tool serves a clearly distinct purpose: cost estimation, local video description, URL-based description, frame viewing, and upload retrieval. The two description tools are cleanly separated by input source (local path vs URL) with explicit parameter names, eliminating ambiguity.

    Naming Consistency5/5

    All tools follow a consistent verb_noun snake_case pattern (e.g., estimate_cost, describe_video, view_media, get_upload_url). The describe_video_url variant appropriately uses a suffix to indicate its remote input mode, preserving overall consistency.

    Tool Count5/5

    With five tools, the server is well-scoped for video understanding workflows. Each tool covers a distinct step in the process—cost planning, local/remote description, visual extraction, and file upload—without redundant or missing functionality.

    Completeness5/5

    The tool surface fully covers the expected video analysis lifecycle: estimating token usage, uploading or referencing videos, describing content from local/URL sources, and examining frames. No essential operation is missing, and unsupported platform limitations are explicitly documented as out of scope.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues

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