diff --git a/examples/onebot_demo.py b/examples/onebot_demo.py
new file mode 100644
index 00000000..07259308
--- /dev/null
+++ b/examples/onebot_demo.py
@@ -0,0 +1,167 @@
+"""Example of integrating memU with a OneBot v11 (NapCat) QQ bot for long-term memory."""
+
+import sys
+import types
+import asyncio
+import logging
+from openai import AsyncOpenAI
+
+# Mock the core Rust module if not compiled in the environment
+mock_core = types.ModuleType("memu._core")
+mock_core.hello_from_bin = lambda: "Hello from mocked bin!"
+sys.modules["memu._core"] = mock_core
+
+from memu.app import MemoryService
+from memu.app.settings import MemorizeConfig, CategoryConfig
+from memu.integrations.onebot import OneBotAdapter, OneBotConfig
+
+# Configure logging to match memU standards
+logging.basicConfig(
+    level=logging.INFO,
+    format="%(asctime)s - %(name)s - %(levelname)s - %(message)s"
+)
+logger = logging.getLogger("memu.examples.onebot")
+
+# ==============================================================================
+# LLM Configuration
+# ==============================================================================
+LLM_PROFILES = {
+    "default": {
+        "base_url": "",  # Your LLM endpoint
+        "api_key": "",  # Your LLM API key
+        "chat_model": "",  # Your LLM chat model
+        "client_backend": "sdk"
+    },
+    "embedding": {
+        "base_url": "",  # Your LLM endpoint for embeddings
+        "api_key": "",  # Your LLM API key for embeddings
+        "embed_model": "",  # Your LLM embedding model
+        "client_backend": "sdk"
+    }
+}
+
+# Initialize a chat client for generating conversational responses
+chat_client = AsyncOpenAI(
+    base_url=LLM_PROFILES["default"]["base_url"],
+    api_key=LLM_PROFILES["default"]["api_key"]
+)
+
+async def on_qq_message(event: dict, adapter: OneBotAdapter, memory_service: MemoryService):
+    """Callback function triggered when a QQ message is received via OneBot."""
+    user_id = str(event.get("user_id"))
+    group_id = event.get("group_id")
+    text = event.get("clean_text", "")
+    message_type = event.get("message_type")
+    
+    # Ignore empty messages or messages sent by the bot itself
+    if not text or user_id == str(adapter.get_self_id()):
+        return
+        
+    logger.info(f"Received message from User [{user_id}]: {text}")
+    
+    try:
+        current_user = {"user_id": user_id}
+
+        # Retrieve long-term memories related to the current message
+        logger.info("Retrieving related memories from memU...")
+        retrieved_result = await memory_service.retrieve(
+            queries=[{"role": "user", "content": text}],
+            where=current_user
+        )
+        
+        # Handle the result based on memU's return structure
+        items = (
+            retrieved_result.get("items", []) 
+            if isinstance(retrieved_result, dict) 
+            else getattr(retrieved_result, "items", [])
+        )
+        
+        memory_context = ""
+        if items:
+            memory_context = "\n".join([
+                f"- {m.get('summary', '')}" if isinstance(m, dict) else f"- {m.summary}" 
+                for m in items
+            ])
+            logger.info(f"Successfully retrieved {len(items)} related memory item(s).")
+        else:
+            logger.info("No related long-term memory found for the current topic.")
+
+        # Generate a response using the LLM, augmented by retrieved memories
+        logger.info("Generating response using LLM with memory context...")
+        system_prompt = (
+            "You are an AI assistant. There is no short-term chat history between us. "
+            "You MUST rely exclusively on the clues provided in the [Long-Term Memory Database] below to answer. "
+            "If there is no relevant information in the memory, simply state that you don't know or don't remember. "
+            "If the memory contradicts the user's current statement (e.g., they used to like apples but now say oranges), "
+            "point out the change in a friendly conversational tone.\n\n"
+            f"[Long-Term Memory Database]:\n{memory_context if memory_context else 'Empty'}\n"
+        )
+            
+        messages = [
+            {"role": "system", "content": system_prompt},
+            {"role": "user", "content": text}
+        ]
+
+        response = await chat_client.chat.completions.create(
+            model=LLM_PROFILES["default"]["chat_model"],
+            messages=messages,
+            temperature=0.7
+        )
+        reply_text = response.choices[0].message.content
+        
+        # Send the generated response back to the QQ group or private chat
+        if message_type == "group":
+            logger.info(f"Sending reply to group [{group_id}].")
+            await adapter.send_group_msg_ack(int(group_id), f"[CQ:at,qq={user_id}] {reply_text}")
+        else:
+            logger.info(f"Sending private reply to user [{user_id}].")
+            adapter.send_private_msg(int(user_id), reply_text)
+
+        # Persist the current message into the memory database
+        logger.info("Committing current interaction to memU storage...")
+        await memory_service.create_memory_item(
+            memory_type="event",
+            memory_content=text,
+            memory_categories=["QQConversations"],
+            user=current_user
+        )
+
+        logger.info("Interaction cycle completed successfully.")
+        
+    except Exception as e:
+        logger.error(f"Error occurred during interaction cycle: {e}", exc_info=True)
+
+
+async def main():
+    """Main entry point for starting the OneBot memory integration example."""
+    logger.info("Initializing memU MemoryService...")
+    memory_service = MemoryService(
+        llm_profiles=LLM_PROFILES,
+        memorize_config=MemorizeConfig(
+            memory_categories=[
+                CategoryConfig(name="QQConversations", description="Records of chats from QQ")
+            ]
+        ),
+    )
+
+    async def msg_handler(event: dict, adapter: OneBotAdapter):
+        await on_qq_message(event, adapter, memory_service)
+
+    # Initialize the OneBot adapter with standard configuration
+    logger.info("Initializing OneBot v11 Adapter...")
+    config = OneBotConfig(
+        ws_url="ws://127.0.0.1:3001", 
+        access_token="" # Replace with environment variable in production
+    )
+    
+    adapter = OneBotAdapter(config=config, on_message=msg_handler)
+    
+    logger.info("Starting OneBot engine and entering event loop...")
+    await adapter.connect()
+
+
+if __name__ == "__main__":
+    try:
+        asyncio.run(main())
+    except KeyboardInterrupt:
+        logger.info("Application shutdown requested by user.")
\ No newline at end of file
diff --git a/src/memu/integrations/onebot.py b/src/memu/integrations/onebot.py
new file mode 100644
index 00000000..e10e054f
--- /dev/null
+++ b/src/memu/integrations/onebot.py
@@ -0,0 +1,223 @@
+import json
+import asyncio
+import logging
+import re
+import time
+import uuid
+from typing import Callable, Awaitable, Any, Dict, List, Optional
+
+logger = logging.getLogger(__name__)
+
+class OneBotConfig:
+    """Configuration for the OneBot (NapCat) adapter."""
+    
+    def __init__(
+        self,
+        ws_url: str,
+        access_token: Optional[str] = None,
+    ):
+        self.ws_url = ws_url
+        self.access_token = access_token
+
+
+class OneBotAdapter:
+    """Adapter for connecting to a OneBot v11 implementation (e.g., NapCat) via WebSocket."""
+    
+    def __init__(
+        self,
+        config: OneBotConfig,
+        on_message: Optional[Callable[[Dict[str, Any], "OneBotAdapter"], Awaitable[None]]] = None
+    ):
+        self.config = config
+        self.on_message = on_message
+        
+        self._ws = None
+        self._self_id: Optional[int] = None
+        self._is_alive = False
+        
+        self._reconnect_attempts = 0
+        self._max_reconnect_delay = 60.0
+        self._last_message_at = 0.0
+        self._pending_messages: List[Dict[str, Any]] = []
+        self._pending_requests: Dict[str, asyncio.Future] = {}
+
+    def get_self_id(self) -> Optional[int]:
+        """Get the connected bot's user ID."""
+        return self._self_id
+
+    def is_connected(self) -> bool:
+        """Check if the WebSocket connection is currently active."""
+        return self._is_alive and self._ws is not None
+
+    async def connect(self):
+        """Main loop for managing WebSocket connection and auto-reconnection."""
+        import websockets
+        kwargs = {}
+        if self.config.access_token:
+            kwargs["additional_headers"] = {"Authorization": f"Bearer {self.config.access_token}"}
+
+        while True:
+            try:
+                logger.info(f"Connecting to OneBot server at {self.config.ws_url}...")
+                
+                # Disable underlying ping to fully simulate Node.js ws library behavior.
+                async with websockets.connect(self.config.ws_url, ping_interval=None, **kwargs) as ws:
+                    self._ws = ws
+                    self._is_alive = True
+                    self._reconnect_attempts = 0
+                    self._last_message_at = time.time()
+                    logger.info("Connected to OneBot server successfully.")
+
+                    if self._pending_messages:
+                        to_flush = self._pending_messages[:]
+                        self._pending_messages.clear()
+                        sent = 0
+                        for item in to_flush:
+                            try:
+                                await self._ws.send(json.dumps(item))
+                                sent += 1
+                            except Exception:
+                                pass
+                        if sent > 0:
+                            logger.info(f"Flushed {sent}/{len(to_flush)} queued outbound message(s).")
+
+                    # Wrap get_login_info in try-except and delay to prevent initialization shock.
+                    async def fetch_bot_info():
+                        try:
+                            await asyncio.sleep(1.0)
+                            info = await self.get_login_info()
+                            logger.info(f"Bot logged in successfully. Basic info: {info}")
+                        except Exception as e:
+                            logger.warning(f"Failed to fetch Bot account info: {e}")
+                    
+                    asyncio.create_task(fetch_bot_info())
+
+                    # Start application layer heartbeat detection task.
+                    heartbeat_task = asyncio.create_task(self._heartbeat_loop())
+
+                    try:
+                        async for message in ws:
+                            self._is_alive = True
+                            self._last_message_at = time.time()
+                            self._handle_raw_message(message)
+                            
+                        # Log specific disconnection status codes for easier troubleshooting.
+                        logger.warning(f"WebSocket loop exited cleanly. Close code: {ws.close_code}, reason: {ws.close_reason}")
+                        
+                    except websockets.exceptions.ConnectionClosed as cc:
+                        logger.warning(f"WebSocket connection closed by server: Code={cc.code}, Reason={cc.reason}")
+                    finally:
+                        heartbeat_task.cancel()
+
+            except Exception as e:
+                logger.error(f"WebSocket Error: {e}")
+
+            # Execute cleanup and backoff reconnection logic.
+            self._cleanup()
+            delay = min(1.0 * (2 ** self._reconnect_attempts), self._max_reconnect_delay)
+            logger.info(f"Reconnecting in {delay}s (Attempt {self._reconnect_attempts + 1})...")
+            await asyncio.sleep(delay)
+            self._reconnect_attempts += 1
+
+    def _cleanup(self):
+        """Clean up connection state and discard all pending Futures."""
+        self._is_alive = False
+        self._ws = None
+        for future in self._pending_requests.values():
+            if not future.done():
+                future.set_exception(Exception("Connection closed"))
+        self._pending_requests.clear()
+
+    async def _heartbeat_loop(self):
+        """Heartbeat checker: forcefully disconnect to trigger a reconnect if the connection goes idle."""
+        while True:
+            await asyncio.sleep(45)
+            stale_ms = (time.time() - self._last_message_at) * 1000
+            if stale_ms > 180000:  # No inbound traffic for over 3 minutes.
+                logger.warning(f"No inbound traffic for {int(stale_ms/1000)}s, forcing reconnect...")
+                if self._ws:
+                    await self._ws.close()
+                break
+
+    def _handle_raw_message(self, message: str):
+        """Parse and route inbound messages."""
+        try:
+            event = json.loads(message)
+        except json.JSONDecodeError:
+            return
+
+        # Process API responses (Echo callback mechanism)
+        if "echo" in event and event["echo"] in self._pending_requests:
+            future = self._pending_requests.pop(event["echo"])
+            if not future.done():
+                if event.get("status") == "ok":
+                    future.set_result(event.get("data"))
+                else:
+                    future.set_exception(Exception(event.get("msg", "API request failed")))
+            return
+
+        # Process heartbeat meta events
+        if event.get("post_type") == "meta_event" and event.get("meta_event_type") == "heartbeat":
+            return
+
+        # Record the bot's own User ID upon receiving login info
+        if event.get("status") == "ok" and "data" in event and "user_id" in event["data"]:
+            self._self_id = event["data"]["user_id"]
+
+        # Trigger business message hook
+        if event.get("post_type") == "message":
+            # Clean CQ codes to extract pure text for LLM embedding and processing
+            clean_text = re.sub(r'\[CQ:.*?\]', '', event.get("raw_message", "")).strip()
+            event['clean_text'] = clean_text
+            if self.on_message:
+                asyncio.create_task(self.on_message(event, self))
+
+    # ================= API Implementations =================
+    
+    async def _send_with_response(self, action: str, params: Dict[str, Any], timeout_ms: int = 5000) -> Any:
+        """Send an API request with an Echo identifier and await its Promise (Future) response."""
+        if not self.is_connected():
+            raise Exception("WebSocket not open")
+
+        echo = str(uuid.uuid4())
+        req = {"action": action, "params": params, "echo": echo}
+        
+        future = asyncio.get_event_loop().create_future()
+        self._pending_requests[echo] = future
+
+        await self._ws.send(json.dumps(req))
+
+        try:
+            return await asyncio.wait_for(future, timeout=timeout_ms / 1000.0)
+        except asyncio.TimeoutError:
+            self._pending_requests.pop(echo, None)
+            raise Exception(f"Request timeout for action: {action}")
+
+    def _send_safe(self, action: str, params: Dict[str, Any]):
+        """Safely send a request without awaiting its response. Queues the request if disconnected."""
+        req = {"action": action, "params": params}
+        if self.is_connected():
+            asyncio.create_task(self._ws.send(json.dumps(req)))
+        else:
+            if len(self._pending_messages) < 200:
+                self._pending_messages.append(req)
+
+    async def get_login_info(self) -> Any:
+        """Fetch the login information of the current bot."""
+        return await self._send_with_response("get_login_info", {})
+
+    def send_private_msg(self, user_id: int, message: str):
+        """Send a private message silently (no ack)."""
+        self._send_safe("send_private_msg", {"user_id": user_id, "message": message})
+
+    async def send_private_msg_ack(self, user_id: int, message: str) -> Any:
+        """Send a private message and wait for the acknowledgment."""
+        return await self._send_with_response("send_private_msg", {"user_id": user_id, "message": message}, 15000)
+
+    def send_group_msg(self, group_id: int, message: str):
+        """Send a group message silently (no ack)."""
+        self._send_safe("send_group_msg", {"group_id": group_id, "message": message})
+
+    async def send_group_msg_ack(self, group_id: int, message: str) -> Any:
+        """Send a group message and wait for the acknowledgment."""
+        return await self._send_with_response("send_group_msg", {"group_id": group_id, "message": message}, 15000)
\ No newline at end of file