---
title: "Build a Voice Agent with LiveKit Agents Python SDK 1.5 (2026)"
description: "LiveKit Agents 1.5 (April 2026) added an audio-based interruption model and native MCP tools. Here's a full self-hosted LiveKit voice agent with adaptive turn detection."
canonical: https://callsphere.ai/blog/vw4h-build-voice-agent-livekit-agents-python-sdk
category: "AI Voice Agents"
tags: ["LiveKit", "Agents SDK", "WebRTC", "MCP", "Tutorial"]
author: "CallSphere Team"
published: 2026-04-19T00:00:00.000Z
updated: 2026-05-07T16:13:46.696Z
---

# Build a Voice Agent with LiveKit Agents Python SDK 1.5 (2026)

> LiveKit Agents 1.5 (April 2026) added an audio-based interruption model and native MCP tools. Here's a full self-hosted LiveKit voice agent with adaptive turn detection.

> **TL;DR** — LiveKit Agents 1.5 ships an ML model that distinguishes real interruptions from "mm-hmm", coughs, and background noise. Combine that with native MCP tool support and the framework is the most polished OSS voice-agent stack in May 2026.

## What you'll build

A self-hosted LiveKit server + an Agents 1.5 Python worker that joins rooms, runs Deepgram STT + OpenAI LLM + ElevenLabs TTS (all swappable), and exposes a calculator MCP tool. Browser test page included.

## Prerequisites

1. Docker (for the LiveKit server) + Python 3.11.
2. `pip install "livekit-agents[deepgram,openai,elevenlabs,silero,turn-detector]" python-dotenv`.
3. API keys for Deepgram, OpenAI, ElevenLabs (or swap to local providers).
4. `livekit-server` Docker image.

## Architecture

```mermaid
flowchart LR
  BR[Browser] -->|WebRTC| LK[LiveKit Server]
  LK |Room| AG[Agents Worker 1.5]
  AG --> STT[Deepgram]
  AG --> LLM[OpenAI gpt-4o-mini]
  AG --> TTS[ElevenLabs]
  AG --> MCP[MCP Server -> tools]
```

## Step 1 — Run LiveKit server

```bash
docker run --rm -p 7880:7880 -p 7881:7881 -p 7882:7882/udp \
  -e LIVEKIT_KEYS="devkey: secret" \
  livekit/livekit-server --dev
```

This is fine for local dev; for production use Helm + a dedicated SFU.

## Step 2 — Define the agent

```python

# agent.py

import os
from dotenv import load_dotenv
from livekit import agents
from livekit.agents import Agent, AgentSession, JobContext, RoomInputOptions, WorkerOptions
from livekit.plugins import openai, deepgram, elevenlabs, silero
from livekit.plugins.turn_detector.multilingual import MultilingualModel
load_dotenv()

class Assistant(Agent):
    def **init**(self):
        super().**init**(instructions=(
            "You are a polite, concise voice assistant. Keep replies under 2 sentences. "
            "If asked to compute, call the calculator tool."))

async def entrypoint(ctx: JobContext):
    session = AgentSession(
        stt=deepgram.STT(model="nova-2", language="en"),
        llm=openai.LLM(model="gpt-4o-mini"),
        tts=elevenlabs.TTS(voice="EXAVITQu4vr4xnSDxMaL"),
        vad=silero.VAD.load(),
        turn_detection=MultilingualModel())  # 1.5 ML interruption model
    await session.start(agent=Assistant(), room=ctx.room,
                        room_input_options=RoomInputOptions())
    await ctx.connect()
    await session.generate_reply(instructions="Greet the user and ask what they need.")

if **name** == "**main**":
    agents.cli.run_app(WorkerOptions(entrypoint_fnc=entrypoint))
```

## Step 3 — `.env`

```bash
LIVEKIT_URL=ws://127.0.0.1:7880
LIVEKIT_API_KEY=devkey
LIVEKIT_API_SECRET=secret
OPENAI_API_KEY=sk-...
DEEPGRAM_API_KEY=...
ELEVEN_API_KEY=...
```

## Step 4 — Run the agent worker

```bash
python agent.py dev
```

The worker registers with LiveKit and waits for rooms.

## Step 5 — Add an MCP tool (1.5 native)

```python
from livekit.agents import function_tool, RunContext

@function_tool
async def calculator(ctx: RunContext, expression: str) -> str:
    """Evaluate a basic arithmetic expression."""
    import ast, operator as op
    OPS = {ast.Add: op.add, ast.Sub: op.sub, ast.Mult: op.mul, ast.Div: op.truediv}
    def ev(n):
        if isinstance(n, ast.Constant): return n.value
        if isinstance(n, ast.BinOp): return OPS[type(n.op)](ev(n.left), ev(n.right))
        raise ValueError("bad")
    return str(ev(ast.parse(expression, mode="eval").body))

class Assistant(Agent):
    def **init**(self):
        super().**init**(instructions="...", tools=[calculator])
```

For production, point `AgentSession(mcp_servers=[...])` at a remote MCP server (Anthropic, GitHub, your own).

## Step 6 — Browser test client

Use the `agent-starter-react` repo or a quick `livekit-client` snippet to join the same room. The agent answers automatically.

## Common pitfalls

- **Worker not registering.** LIVEKIT_URL must match the host the browser uses (`ws://127.0.0.1:7880`, not `localhost` if your client is on a phone).
- **Turn detector model download.** First run downloads ~120 MB of weights; pre-cache in CI.
- **Interruption model on slow CPUs.** It's fine on M-series and modern x86; on Pi-class hardware, disable.

## How CallSphere does this in production

CallSphere runs OneRoof Property's 10 specialists on a Pion-based WebRTC mesh — same architecture pattern as LiveKit, custom-tuned for property workflows. Healthcare uses 14 HIPAA-aware tools on FastAPI :8084 with OpenAI Realtime; Salon, Dental, F&B and Behavioral round out 6 verticals. Total: 37 agents · 90+ tools · 115+ DB tables. Flat pricing $149/$499/$1499 — [14-day trial](/trial) · [22% affiliate](/affiliate) · [/industries/real-estate](/industries/real-estate) · [/demo](/demo).

## FAQ

**Cloud vs self-hosted LiveKit?** Cloud is faster to try; self-hosted is cheaper at scale.

**Sub-agent / multi-agent patterns?** Yes — `session.update_agent(NewAgent())` mid-call.

**Realtime API instead of STT/LLM/TTS?** Yes — `openai.realtime.RealtimeModel()`.

**Mobile?** Native iOS/Android SDKs.

**Phone numbers?** LiveKit Cloud Build plan includes one US DID.

## Sources

- [LiveKit Agents on GitHub](https://github.com/livekit/agents)
- [LiveKit Agents docs](https://docs.livekit.io/agents/)
- [agent-starter-python](https://github.com/livekit-examples/agent-starter-python)
- [LiveKit voice agent quickstart](https://docs.livekit.io/agents/quickstarts/voice-agent/)

---

Source: https://callsphere.ai/blog/vw4h-build-voice-agent-livekit-agents-python-sdk