voice-summary
Related Servers
Alternatives to voice-summary
No user-submitted related servers found.
Related Servers
- AlicenseAqualityAmaintenanceEnables 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.4146 PyPI1MIT
- AlicenseNot gradedqualityDmaintenanceEnables AI assistants to speak aloud by generating and playing audio through the system output. Supports multiple TTS providers, playback queue management, and configurable voice profiles.2 npm1MIT
- AlicenseNot gradedqualityBmaintenanceEnables 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
- AlicenseNot gradedqualityDmaintenanceProvides 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.9MIT
- FlicenseNot gradedqualityAmaintenanceEnables 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-
- AlicenseNot gradedqualityAmaintenanceEnables 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 npmMIT
TDQS
Scored across 3 tools
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.
All tool names use snake_case with a clear verb_noun pattern: set_language, speak_summary, list_voices. This is consistent and predictable.
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.
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.