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Related Servers

Alternatives to voice-summary

No user-submitted related servers found.

    Related Servers

    • A
      license
      A
      quality
      A
      maintenance
      Enables AI coding agents to synthesize and play concise spoken summaries of their work through multiple TTS providers, including Azure, OpenRouter, OpenAI, Gemini, ElevenLabs, and local OpenAI-compatible endpoints. It also lets agents stop playback on demand and check which provider, voice, and audio bridge are currently active.
      4
      146 PyPI
      1
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables AI coding assistants to verbally announce task progress and events through local text-to-speech, with cloud synthesis via Volcano Engine or Edge TTS, scene-based voice settings, and a Windows SAPI fallback so announcements continue even when the cloud fails.
      MIT
    • A
      license
      Not graded
      quality
      D
      maintenance
      Provides voice summaries after each AI request in Cursor, Cline, or any MCP-supported editor, allowing users to hear what was done and stay informed without staring at the screen.
      9
      MIT
    • F
      license
      Not graded
      quality
      A
      maintenance
      Enables coding agents to speak aloud using text-to-speech functionality. Works with agents running inside devcontainers and provides configurable voice settings for creating chatty AI companions.
      6
      -
    • A
      license
      Not graded
      quality
      A
      maintenance
      Enables AI agents to give spoken output by synthesizing text into speech with an on-device neural model and playing it through the user's speakers, entirely offline. Agents can queue spoken summaries and stop playback on demand.
      1 npm
      MIT

    TDQS

    A4/5.0

    Scored across 3 tools

    Disambiguation5/5

    Each tool has a distinct purpose: set_language configures voice settings, speak_summary performs the core action, and list_voices provides introspection. There is no overlap; an agent can easily select the right tool.

    Naming Consistency5/5

    All tool names use snake_case with a clear verb_noun pattern: set_language, speak_summary, list_voices. This is consistent and predictable.

    Tool Count5/5

    With only 3 tools, the server is tightly scoped to its purpose: configure voice, speak summary, and inspect options. Each tool is necessary and there is no bloat.

    Completeness4/5

    The core lifecycle is covered: configure language/gender, speak a summary, and list voices. However, list_voices defers to an external command for the full catalog and there is no explicit stop/cancel operation, leaving minor gaps.

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues