VoxFabric
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": false
} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| speakA | 本地朗读文本（可带情绪）。interrupt=True 时打断当前播放，便于实时插话。 |
| listenC | 采集本地麦克风语音并识别为中文文本。本地或云端 ASR 均可（云端需先在 config.yaml 配 asr.aliyun）。返回识别结果 JSON（含 text 字段）。 |
| set_engineA | 切换某类引擎（会话级）。kind ∈ vad/asr/agent/tts，name 用 catalog() 查看。 |
| catalogA | 列出所有已注册的引擎与当前选择。 |
| healthA | 返回声络状态摘要（版本、ffplay 是否可用、当前引擎）。 |
| listen_startA | 启动常驻语音会话：后台持续听写麦克风并实时转写。返回 session_id 与状态。 |
| get_speechB | 轮询拉取实时语音事件（speech_start/final/state…）。宿主可据此感知用户说话。 |
| listen_stopA | 停止常驻语音会话，释放麦克风。 |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 8 tools
Each tool targets a distinct function: speak for TTS, listen for one-shot STT, listen_start/get_speech/listen_stop for streaming sessions, set_engine/catalog for configuration, and health for status. No two tools have overlapping responsibilities.
Most names follow an imperative verb style with snake_case for compound actions (listen_start, get_speech). A few single-word names like catalog and health deviate from a strict verb_noun pattern, but the overall style is consistent and readable.
8 tools is well within the ideal range. Each tool serves a clear purpose in the voice lifecycle (speech, recognition, session control, engine management, health) without redundancy.
The core voice workflows are covered: one-shot and continuous recognition, TTS, engine switching, and status. Minor gaps exist such as no explicit pause/resume or volume control for speech, but these can be worked around using engine settings.