Pronunciation scoring, speech-to-text, and text-to-speech for language learning
Config is the same across clients — only the file and path differ.
{
"mcpServers": {
"brainiall-nlp": {
"url": "https://apim-ai-apis.azure-api.net/mcp/nlp/mcp",
"headers": {
"Ocp-Apim-Subscription-Key": "YOUR_KEY"
}
},
"brainiall-image": {
"url": "https://apim-ai-apis.azure-api.net/mcp/image/mcp",
"headers": {
"Ocp-Apim-Subscription-Key": "YOUR_KEY"
}
},
"brainiall-speech": {
"url": "https://apim-ai-apis.azure-api.net/mcp/pronunciation/mcp",
"headers": {
"Ocp-Apim-Subscription-Key": "YOUR_KEY"
}
}
}
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Production AI APIs for speech, text, image, and LLM inference. Available as REST endpoints and MCP servers for AI agents.
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Production AI APIs for speech, text, image, and LLM inference. Available as REST endpoints and MCP servers for AI agents.
Base URL: https://apim-ai-apis.azure-api.net
Full API reference for LLMs: llms-full.txt | llms.txt
| Product | Endpoints | Latency | Notes |
|---|---|---|---|
| Pronunciation Assessment | /v1/pronunciation/assess/base64 | <500ms | 17MB ONNX, per-phoneme scoring (39 ARPAbet) |
| Text-to-Speech | /v1/tts/synthesize | <1s | 12 voices (American + British), 24kHz WAV |
| Speech-to-Text | /v1/stt/transcribe/base64 | <500ms | Compact 17MB model, English, word timestamps |
| Whisper Pro | /v1/whisper/transcribe/base64 | <3s | 99 languages, speaker diarization |
| NLP Suite | /v1/nlp/{toxicity,sentiment,entities,pii,language} | <50ms | CPU-only, ONNX, 5 endpoints |
| Image Processing | /v1/image/{remove-background,upscale,restore-face}/base64 | <3s | GPU (A10), BiRefNet + ESRGAN + GFPGAN |
| LLM Gateway | /v1/chat/completions | varies | 113+ models, OpenAI-compatible, streaming |
Include ONE of these headers in every request:
Ocp-Apim-Subscription-Key: YOUR_KEY
Authorization: Bearer YOUR_KEY
api-key: YOUR_KEY
Get API keys at the portal (GitHub sign-in, purchase credits, create key).
from openai import OpenAI
client = OpenAI(
base_url="https://apim-ai-apis.azure-api.net/v1",
api_key="YOUR_KEY"
)
response = client.chat.completions.create(
model="claude-sonnet",
messages=[{"role": "user", "content": "Hello!"}]
)
print(response.choices[0].message.content)
import requests, base64
audio_b64 = base64.b64encode(open("audio.wav", "rb").read()).decode()
r = requests.post(
"https://apim-ai-apis.azure-api.net/v1/pronunciation/assess/base64",
headers={"Ocp-Apim-Subscription-Key": "YOUR_KEY"},
json={"audio": audio_b64, "text": "Hello world", "format": "wav"}
)
print(r.json()["overallScore"]) # 0-100
import requests
headers = {"Ocp-Apim-Subscription-Key": "YOUR_KEY"}
base = "https://apim-ai-apis.azure-api.net/v1/nlp"
# Sentiment
r = requests.post(f"{base}/sentiment", headers=headers, json={"text": "I love this!"})
print(r.json()) # {"label": "positive", "score": 0.9987}
# PII detection with redaction
r = requests.post(f"{base}/pii", headers=headers, json={"text": "Email john@acme.com", "redact": True})
print(r.json()["redacted_text"]) # "Email [EMAIL]"
import OpenAI from "openai";
const client = new OpenAI({
baseURL: "https://apim-ai-apis.azure-api.net/v1",
apiKey: "YOUR_KEY"
});
const res = await client.chat.completions.create({
model: "claude-sonnet",
messages: [{ role: "user", content: "Hello!" }]
});
console.log(res.choices[0].message.content);
curl -X POST https://apim-ai-apis.azure-api.net/v1/image/remove-background/base64 \
-H "Ocp-Apim-Subscription-Key: YOUR_KEY" \
-H "Content-Type: application/json" \
-d "{\"image\": \"$(base64 -i photo.jpg)\"}"
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|---|---|---|
| Claude |