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Gandr-AI

Gandr TTS

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by Gandr-AI
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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

    A4.3/5.0

    Scored across 4 tools

    Disambiguation5/5

    Each tool has a clearly distinct purpose: synthesize for TTS, list_voices for voice metadata, list_languages for language metadata, and get_usage for account status. No two tools overlap in function.

    Naming Consistency4/5

    Tool names are lowercase with underscores and mostly follow a verb_noun pattern (list_voices, list_languages, get_usage), but synthesize is a bare verb, which is a minor deviation from the pattern.

    Tool Count5/5

    With four tools, the server is well-scoped: one core operation, two metadata lookups, and one usage check. This is an ideal size for a TTS-focused server.

    Completeness5/5

    The tool surface covers the essential lifecycle for text-to-speech: the synthesis action, necessary resource discovery (voices/languages), and account monitoring. There are no obvious gaps or dead ends.

    Maintenance

    ActivitySlowing
    ResponsivenessNo issues

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