Documentation

curl https://agentphone.primary.net/api/numbers/YOUR_NUMBER_ID/send/sms \
  -H "Authorization: Bearer agp_your_api_key_here" \
  -H "Content-Type: application/json" \
  -d '{"to": "+15559876543", "body": "Hello!"}'

{
  "event": "message.inbound",
  "channel": "sms",
  "from": "+15551234567",
  "to": "+15559876543",
  "body": "Hello agent",
  "media": [],
  "timestamp": "2026-02-24T15:30:00.000Z",
  "message_id": "msg_a1b2c3d4-e5f6-7890-abcd-ef1234567890",
  "signature": "hmac-sha256-hex-string..."
}

{
  "reply": "Hello! How can I help you today?",
  "action": "respond"
}

{
  "action": "ignore"
}

import crypto from "crypto";

function verifyWebhook(rawBody, signature, secret) {
  const expected = crypto
    .createHmac("sha256", secret)
    .update(rawBody)
    .digest("hex");
  return crypto.timingSafeEqual(
    Buffer.from(signature, "hex"),
    Buffer.from(expected, "hex")
  );
}

app.post("/webhook", (req, res) => {
  const sig = req.headers["x-agentphone-signature"];
  if (!verifyWebhook(JSON.stringify(req.body), sig, WEBHOOK_SECRET)) {
    return res.status(401).json({ error: "Invalid signature" });
  }
  res.json({ reply: "Got it!", action: "respond" });
});

import hmac, hashlib

def verify_webhook(raw_body: bytes, signature: str, secret: str) -> bool:
    expected = hmac.new(secret.encode(), raw_body, hashlib.sha256).hexdigest()
    return hmac.compare_digest(signature, expected)

@app.post("/webhook")
async def handle(request: Request):
    raw = await request.body()
    sig = request.headers.get("X-AgentPhone-Signature", "")
    if not verify_webhook(raw, sig, WEBHOOK_SECRET):
        raise HTTPException(401, "Invalid signature")
    return {"reply": "Got it!", "action": "respond"}

from openai import OpenAI

client = OpenAI(
    api_key="agp_your_api_key_here",
    base_url="https://agentphone.primary.net/api/v1"
)

# Chat completion
response = client.chat.completions.create(
    model="Qwen3-Next-80B",
    messages=[{"role": "user", "content": "Hello!"}]
)

# Speech-to-text
with open("audio.wav", "rb") as f:
    transcript = client.audio.transcriptions.create(
        model="whisper-large-v3",
        file=f
    )

# Text-to-speech
audio = client.audio.speech.create(
    input="Hello world",
    voice="tara"
)

import OpenAI from "openai";

const client = new OpenAI({
  apiKey: "agp_your_api_key_here",
  baseURL: "https://agentphone.primary.net/api/v1",
});

const completion = await client.chat.completions.create({
  model: "Qwen3-Next-80B",
  messages: [{ role: "user", content: "Hello!" }],
});