# Speech AI - Pronunciation, STT & TTS (remote · apim-ai-apis.azure-api.net)

Pronunciation scoring, speech-to-text, and text-to-speech for language learning

- Trust score: 73/100 (medium)
- Change this week: +6
- Registry status: active
- Liveness: live
- Owner verified: no
- Last scored: 2026-08-04

## Components

- remote · `apim-ai-apis.azure-api.net`: 73/100 (this document), [markdown](https://verifymcp.io/servers/fasuizu-br-speech-ai/mcp-pronunciation-mcp.md), [page](https://verifymcp.io/servers/fasuizu-br-speech-ai/mcp-pronunciation-mcp)

## Channel facts

- Endpoint: `https://apim-ai-apis.azure-api.net/mcp/pronunciation/mcp`
- Transports: `streamable-http`
- Auth: `none`
- Version: `2.3.0`

## Trust breakdown

How this component scores in each security and reliability category. Every signal is checked automatically against the live server, and we only credit what we can confirm. Scores are 0–100 per category. Scoring method: https://verifymcp.io/docs/scoring (what has changed: https://verifymcp.io/docs/scoring/changelog)

Scored 2026-08-04.

- **Endpoint Security**: 77/100
  - The endpoint's TLS certificate is valid, in date, and uses a strong key.
  - Authorisation is enforced on tool calls, but the challenge carries no valid RFC 9728 metadata, so a client cannot discover where to get a token.
  - HTTPS not yet verified: we couldn't determine whether a plaintext access path exists.
  - The HSTS (Strict-Transport-Security) header is present.
  - DNSSEC check failed: this domain isn't protected by DNSSEC.
- **Transport & Reachability**: 100/100
  - Verified streamable-http transport via a live MCP handshake.
- **Schema Quality & AI Usability**: 64/100
  - AI-judged instruction clarity (excellent).
  - Context-footprint check failed: tool/resource definitions use about 2017 tokens (~201/item across 10 items; 10 tools + 0 resources), over budget; trim descriptions and params.
  - Usage-examples check failed: none of the tools include examples.
- **Stability & Change Management**: 30/100
  - Stability observed for 9 of 30 days with no destabilising changes; credit accrues until the full window elapses.
- **Tool Coverage**: 100/100
  - 100% of tools have a non-trivial description (not blank, and not just the tool's name).
  - 100% of tool parameters carry a description.
- **Capabilities**: 100/100
  - Implements a supported MCP spec version (2025-11-25); the latest is 2026-07-28.

## Install

### Claude

```bash
claude mcp add --transport http fasuizu-br-speech-ai https://apim-ai-apis.azure-api.net/mcp/pronunciation/mcp
```

### Codex

```toml
[mcp_servers.fasuizu-br-speech-ai]
url = "https://apim-ai-apis.azure-api.net/mcp/pronunciation/mcp"
```

### opencode

```json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "fasuizu-br-speech-ai": {
      "type": "remote",
      "url": "https://apim-ai-apis.azure-api.net/mcp/pronunciation/mcp",
      "enabled": true
    }
  }
}
```

### OpenClaw

```bash
openclaw mcp add fasuizu-br-speech-ai --url https://apim-ai-apis.azure-api.net/mcp/pronunciation/mcp --transport streamable-http
```

### Hermes

```yaml
mcp_servers:
  fasuizu-br-speech-ai:
    url: "https://apim-ai-apis.azure-api.net/mcp/pronunciation/mcp"
```

### Other

```json
{
  "mcpServers": {
    "fasuizu-br-speech-ai": {
      "type": "http",
      "url": "https://apim-ai-apis.azure-api.net/mcp/pronunciation/mcp"
    }
  }
}
```

The mcpServers block is a cross-client convention. Remote transports vary, so check your client's docs.

## Changelog

Every change recorded for this component, newest first. Days that predate change tracking, or that we cannot explain, say so: "we were watching and nothing happened" and "we were not watching" are different claims.

### 2026-08-03 (score 73, +1)

No change was recorded against any check on this day. Stability & Change Management went from 23 to 27. That category is still filling its 30-day observation window: 7 days of observed history at the previous scan, 8 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-08-01 (score 72, +1)

No change was recorded against any check on this day. Stability & Change Management went from 17 to 20. That category is still filling its 30-day observation window: 5 days of observed history at the previous scan, 6 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-07-31 (score 71, +3)

- [functional] We updated how we score, so this day's move reflects our rubric, not a change to the server

### 2026-07-30 (score 68, +1)

- [functional] We updated how we score, so this day's move reflects our rubric, not a change to the server

### 2026-07-28 (score 67, +1)

No change was recorded against any check on this day. Stability & Change Management went from 3 to 7. That category is still filling its 30-day observation window: 1 days of observed history at the previous scan, 2 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-07-27 (score 66, +1)

- [functional] We updated how we score, so this day's move reflects our rubric, not a change to the server

### 2026-07-26 (score 65)

First indexed and scored.

## MCP tools (10)

### `assess_pronunciation` (~379 tokens)

Assess Pronunciation

Assess English pronunciation quality from audio.

Scores pronunciation at four levels: overall, sentence, word, and phoneme.
Each score is 0-100. Phonemes are returned in both IPA and ARPAbet notation.
Sub-300ms inference latency.

Args:
    audio_base64: Base64-encoded audio data. Supports WAV, MP3, OGG, and WebM formats.
    text: The reference English text that the speaker was expected to read aloud.
    audio_format: Audio format hint — one of 'wav', 'mp3', 'ogg', 'webm'. Defaults to 'wav'.

Returns:
    dict with keys:
        - overallScore (int 0-100): Overall pronunciation quality
        - sentenceScore (int 0-100): Sentence-level fluency and accuracy
        - words (list): Per-word scores, each containing:
            - word (str): The word
            - score (int 0-100): Word pronunciation score
            - phonemes (list): Per-phoneme scores with IPA/ARPAbet notation
        - decodedTranscript (str): What the model heard (ASR transcript)
        - transcript (str): Reference text
        - confidence (float 0-1): Scoring confidence
        - warnings (list[str]): Quality warnings if any
        - audioQuality (dict): Audio metrics (SNR, peak/RMS dB, etc.)

Input parameters:

- `audio_base64` (string, required): Base64-encoded audio data. Supports WAV, MP3, OGG, and WebM formats.
- `audio_format` (string): Audio format hint — one of 'wav', 'mp3', 'ogg', 'webm'.
- `text` (string, required): The reference English text that the speaker was expected to read aloud.

### `check_pronunciation_service` (~65 tokens)

Check Pronunciation Service

Check if the pronunciation assessment service is healthy and ready.

Returns:
    dict with keys:
        - status (str): 'healthy' or error state
        - modelLoaded (bool): Whether the scoring model is loaded
        - version (str): API version

### `get_phoneme_inventory` (~138 tokens)

Get Phoneme Inventory

Get the full phoneme inventory supported by the pronunciation scorer.

Returns a list of all English phonemes the engine can assess, including
ARPAbet symbol, IPA equivalent, example word, and phoneme category
(vowel, consonant, diphthong).

Returns:
    list of dicts, each with keys:
        - arpabet (str): ARPAbet symbol (e.g. 'AA', 'TH')
        - ipa (str): IPA notation
        - example (str): Example word containing the phoneme
        - category (str): vowel, consonant, or diphthong

### `transcribe_audio` (~313 tokens)

Transcribe Audio

Transcribe audio to text with word-level timestamps.

Converts spoken English audio into text with optional word-level timestamps
and per-word confidence scores.

Args:
    audio_base64: Base64-encoded audio data (WAV, MP3, OGG, FLAC, WebM).
    audio_format: Audio format hint. Auto-detected from magic bytes if omitted.
    include_timestamps: Whether to include word-level timing (default: true).

Returns:
    dict with keys:
        - text (str): Full decoded transcript
        - words (list): Per-word results with timestamps, each containing:
            - word (str): The transcribed word
            - start (float): Start time in seconds
            - end (float): End time in seconds
            - confidence (float 0-1): Word-level confidence
        - audioDurationMs (int): Audio duration in milliseconds
        - metadata (dict): Processing time, audio length, model version
        - audioQuality (dict): Audio metrics (SNR, peak/RMS dB, etc.)

Input parameters:

- `audio_base64` (string, required): Base64-encoded audio data. Supports WAV, MP3, OGG, FLAC, and WebM formats.
- `audio_format`: Audio format hint — 'wav', 'mp3', 'ogg', 'flac', 'webm'. Auto-detected if omitted.
- `include_timestamps` (boolean): If true, include word-level start/end times and confidence.

### `check_stt_service` (~66 tokens)

Check STT Service

Check if the speech-to-text service is healthy and ready.

Returns:
    dict with keys:
        - status (str): 'healthy' or error state
        - modelLoaded (bool): Whether the STT model is loaded
        - version (str): API version

### `synthesize_speech` (~323 tokens)

Synthesize Speech

Generate natural speech audio from English text.

Produces high-quality speech with 12 English voices.
Returns base64-encoded WAV audio (16-bit PCM, 24kHz mono) along with metadata.

Available voices:
\- af_heart (default), af_bella, af_nicole, af_sarah, af_sky (American female)
\- am_adam, am_michael (American male)
\- bf_emma, bf_isabella (British female)
\- bm_george, bm_lewis, bm_daniel (British male)

Args:
    text: English text to synthesize (1-5000 characters).
    voice: Voice ID. See list above. Defaults to 'af_heart'.
    speed: Speed multiplier from 0.5 to 2.0 (default: 1.0).

Returns:
    dict with keys:
        - audio_base64 (str): Base64-encoded WAV audio (16-bit PCM, 24kHz)
        - duration_ms (str): Audio duration in milliseconds
        - voice (str): Voice ID used
        - text_length (str): Input text character count
        - processing_ms (str): Synthesis time in milliseconds

Input parameters:

- `speed` (number): Speech speed multiplier (0.5 = half speed, 2.0 = double).
- `text` (string, required): English text to convert to speech. Max 5000 characters.
- `voice`: Voice ID (e.g. 'af_heart', 'am_adam'). Uses default if omitted.

### `list_tts_voices` (~61 tokens)

List TTS Voices

List all available text-to-speech voices with metadata.

Returns:
    dict with keys:
        - voices (list): Available voices, each with id, name, gender, accent, grade
        - defaultVoice (str): Default voice ID

### `check_tts_service` (~67 tokens)

Check TTS Service

Check if the text-to-speech service is healthy and ready.

Returns:
    dict with keys:
        - status (str): 'healthy' or error state
        - modelLoaded (bool): Whether the TTS model is loaded
        - version (str): API version

### `transcribe_audio_pro` (~353 tokens)

Transcribe Audio Pro (Whisper)

Transcribe audio with Whisper Large V3 Turbo — multilingual STT.

Supports 99 languages with automatic language detection, word-level
timestamps, per-word confidence scores, and optional speaker diarization
(identifies who spoke each word). Best-in-class WER (~2%).

Args:
    audio_base64: Base64-encoded audio (WAV, MP3, OGG, FLAC, WebM).
    language: Language code. Auto-detected if omitted. Supports 99 languages.
    diarize: Enable speaker diarization (default: false). When true, each word
        includes a speaker label (e.g. SPEAKER_00, SPEAKER_01).

Returns:
    dict with keys:
        - text (str): Full decoded transcript
        - words (list): Per-word results with timestamps, each containing:
            - word (str), start (float), end (float), confidence (float 0-1)
            - speaker (str|null): Speaker label when diarize=true
        - speakers (dict|null): Speaker info with count and labels
        - audioDurationMs (int): Audio duration in milliseconds
        - metadata (dict): Processing time, language, languageProbability
        - audioQuality (dict): Audio metrics (SNR, peak/RMS dB, etc.)

Input parameters:

- `audio_base64` (string, required): Base64-encoded audio data. Supports WAV, MP3, OGG, FLAC, and WebM formats.
- `diarize` (boolean): Enable speaker diarization to identify who spoke each word.
- `language`: Language code (e.g. 'en', 'es', 'zh'). Auto-detected when omitted.

### `check_whisper_service` (~103 tokens)

Check Whisper Service

Check if the Whisper STT Pro service is healthy and ready.

Returns:
    dict with keys:
        - status (str): 'healthy' or error state
        - modelLoaded (bool): Whether the Whisper model is loaded
        - diarizeLoaded (bool): Whether the diarization pipeline is loaded
        - version (str): API version
        - modelName (str): Whisper model name (e.g. 'large-v3-turbo')

## Diagnostics

Captured diagnostic sections: TLS, DNSSEC, Authorisation, Transports. The full working is on the page: https://verifymcp.io/servers/fasuizu-br-speech-ai/mcp-pronunciation-mcp#diagnostics

## Score history

- 2026-08-04: 73
- 2026-08-03: 73
- 2026-08-02: 72
- 2026-08-01: 72
- 2026-07-31: 71
- 2026-07-30: 68
- 2026-07-29: 67
- 2026-07-28: 67
- 2026-07-27: 66
- 2026-07-26: 65

## Links

- Remote endpoint: https://apim-ai-apis.azure-api.net/mcp/pronunciation/mcp
- Repository: https://github.com/fasuizu-br/speech-ai-examples
- Website: https://brainiall.com/
- Changelog RSS feed: https://verifymcp.io/servers/fasuizu-br-speech-ai/mcp-pronunciation-mcp/changelog.xml
- Changelog JSON feed: https://verifymcp.io/servers/fasuizu-br-speech-ai/mcp-pronunciation-mcp/changelog.json
- HTML version of this page: https://verifymcp.io/servers/fasuizu-br-speech-ai/mcp-pronunciation-mcp