diff --git a/apps/docs/integrations/livekit.mdx b/apps/docs/integrations/livekit.mdx
index 8a85a4d3..5b090084 100644
--- a/apps/docs/integrations/livekit.mdx
+++ b/apps/docs/integrations/livekit.mdx
@@ -93,6 +93,8 @@ if __name__ == "__main__":
 
 `preload` puts the caller's profile into the first turn, so the greeting can use it. `attach` stores the conversation after each agent reply, and stores anything left when the session closes, including a caller who hangs up mid-turn. `SupermemoryAgent` recalls inside `llm_node` before each reply and adds the memory tools. That covers voice turns, text turns from `generate_reply` or `session.run`, and LiveKit's preemptive generation. Each user message is recalled once, and tool follow-ups reuse it.
 
+A runnable version, with a greeting that uses the caller's memory, is in the [example agent](https://github.com/supermemoryai/supermemory/tree/main/packages/livekit-sdk-python/examples).
+
 `agent_name` turns on explicit dispatch, which is how job metadata reaches the agent. Remove it to join every new room automatically, for example when testing in the [Agents Playground](https://agents-playground.livekit.io).
 
 ## Your own agent
diff --git a/packages/livekit-sdk-python/README.md b/packages/livekit-sdk-python/README.md
index b88bd531..c6d918e1 100644
--- a/packages/livekit-sdk-python/README.md
+++ b/packages/livekit-sdk-python/README.md
@@ -71,6 +71,8 @@ if __name__ == "__main__":
     agents.cli.run_app(server)
 ```
 
+A runnable version with a greeting that uses memory is in [examples/](examples/).
+
 If you already have an `Agent` subclass, pass `tools=memory.tools()` and recall from `llm_node`:
 
 ```python
diff --git a/packages/livekit-sdk-python/examples/.env.example b/packages/livekit-sdk-python/examples/.env.example
new file mode 100644
index 00000000..3bda6f73
--- /dev/null
+++ b/packages/livekit-sdk-python/examples/.env.example
@@ -0,0 +1,14 @@
+# LiveKit Cloud project: Settings > API keys. The same keys cover STT, LLM, and TTS
+# through LiveKit Inference.
+LIVEKIT_URL=wss://your-project.livekit.cloud
+LIVEKIT_API_KEY=
+LIVEKIT_API_SECRET=
+
+# https://console.supermemory.ai
+SUPERMEMORY_API_KEY=
+
+# Optional: pin every call to one caller while testing.
+# SUPERMEMORY_CONTAINER_TAG=demo_caller
+
+# Optional: require explicit dispatch, so your backend can pass {"container_tag": ...}.
+# LIVEKIT_AGENT_NAME=memory-agent
diff --git a/packages/livekit-sdk-python/examples/README.md b/packages/livekit-sdk-python/examples/README.md
new file mode 100644
index 00000000..85cfea14
--- /dev/null
+++ b/packages/livekit-sdk-python/examples/README.md
@@ -0,0 +1,38 @@
+# Voice agent example
+
+A LiveKit voice agent that remembers each caller. Tell it something on one call, hang up, and it knows it on the next.
+
+## Setup
+
+```bash
+pip install supermemory-livekit python-dotenv
+cp .env.example .env
+```
+
+Fill in `.env` with your LiveKit Cloud project keys and a [Supermemory API key](https://console.supermemory.ai). LiveKit Inference provides speech-to-text, the LLM, and text-to-speech, so no other keys are needed.
+
+From a checkout of this repo, install the local package instead: `pip install -e .. python-dotenv`.
+
+## Talk to it
+
+In your terminal, through your mic:
+
+```bash
+python voice_agent.py console
+```
+
+In the browser: run `python voice_agent.py dev`, open the [Agents Playground](https://agents-playground.livekit.io), and connect to your project.
+
+## Try memory
+
+1. Say "My name is Priya, and please remember I'm vegetarian."
+2. Hang up and start a new call.
+3. The agent greets you by name. Ask "What should I order for dinner?"
+
+Memory is scoped per caller:
+
+- Console mode uses the container tag `console_user`.
+- In rooms, the agent uses the participant attribute `supermemory_container_tag`, or else the participant identity. The Playground gives each session a new identity, so set `SUPERMEMORY_CONTAINER_TAG` in `.env` to keep one caller across Playground calls.
+- In production, dispatch the agent from your backend with `{"container_tag": "<your user id>"}` as job metadata, and set `LIVEKIT_AGENT_NAME`.
+
+Each call is stored as one document, and facts the caller asks it to remember are saved right away. See the [integration docs](https://supermemory.ai/docs/integrations/livekit) for configuration.
diff --git a/packages/livekit-sdk-python/examples/voice_agent.py b/packages/livekit-sdk-python/examples/voice_agent.py
new file mode 100644
index 00000000..f6d4a7cf
--- /dev/null
+++ b/packages/livekit-sdk-python/examples/voice_agent.py
@@ -0,0 +1,71 @@
+"""Voice agent that remembers each caller across calls.
+
+Run from this folder after filling in .env (see README.md):
+
+    python voice_agent.py console   # talk through your mic in the terminal
+    python voice_agent.py dev       # join LiveKit rooms, e.g. from the Agents Playground
+"""
+
+import json
+import logging
+import os
+
+from dotenv import load_dotenv
+from livekit import agents
+from livekit.agents import AgentServer, AgentSession, ChatContext, JobContext
+from supermemory_livekit import SupermemoryAgent, SupermemoryLiveKit
+
+load_dotenv()
+logger = logging.getLogger("voice-agent")
+
+INSTRUCTIONS = (
+    "You are a friendly voice assistant. You remember this caller across calls. "
+    "Use what you know naturally, and do not mention the memory system. "
+    "When the caller asks you to remember something, call remember. Keep replies short."
+)
+
+server = AgentServer()
+
+
+# An agent_name turns on explicit dispatch, which is how job metadata reaches the agent.
+# Leave it empty to join every new room, which the Agents Playground needs.
+@server.rtc_session(agent_name=os.getenv("LIVEKIT_AGENT_NAME", ""))
+async def entrypoint(ctx: JobContext):
+    memory = SupermemoryLiveKit(api_key=os.environ["SUPERMEMORY_API_KEY"])
+
+    # Your backend can pass the caller id in dispatch metadata. SUPERMEMORY_CONTAINER_TAG
+    # pins every call to one caller while testing. Console mode has no remote participant.
+    metadata = json.loads(ctx.job.metadata or "{}")
+    container_tag = metadata.get("container_tag") or os.getenv("SUPERMEMORY_CONTAINER_TAG")
+    if not container_tag and ctx.is_fake_job():
+        container_tag = "console_user"
+
+    await ctx.connect()
+    if container_tag:
+        memory.bind(container_tag=container_tag, session_id=ctx.room.name)
+    else:
+        participant = await ctx.wait_for_participant()
+        memory.bind(participant=participant, session_id=ctx.room.name)
+    logger.info("memory scoped to container tag %s", memory.container_tag)
+
+    # The caller's profile goes into the first turn, so the greeting can use it.
+    chat_ctx = ChatContext()
+    await memory.preload(chat_ctx)
+
+    session = AgentSession(
+        stt="deepgram/nova-3:en",
+        llm="openai/gpt-4.1-mini",
+        tts="cartesia/sonic-3",
+    )
+    memory.attach(session)
+    await session.start(
+        room=ctx.room,
+        agent=SupermemoryAgent(memory, chat_ctx=chat_ctx, instructions=INSTRUCTIONS),
+    )
+    await session.generate_reply(
+        instructions="Greet the caller. If you already know them, welcome them back by name."
+    )
+
+
+if __name__ == "__main__":
+    agents.cli.run_app(server)