feat: 原生MCP工具 + xiaozhi CLI客户端测试工具

src/psycho_screener/mcp_tool_native.py

@@ -0,0 +1,174 @@
+"""
+儿童心理陪伴 MCP 工具（原生 mcp 协议版）
+使用官方 mcp Python SDK，不依赖 fastmcp
+
+适用于直接集成到 xiaozhi-esp32-server 的 Docker 容器环境中。
+"""
+
+from __future__ import annotations
+
+import os
+import json
+import logging
+from mcp.server import Server
+from mcp.server.stdio import stdio_server
+from mcp.types import Tool, TextContent
+
+# Configure logging
+logging.basicConfig(
+    level=logging.INFO,
+    format="%(asctime)s - %(name)s - %(levelname)s - %(message)s"
+)
+logger = logging.getLogger("PsychoScreenerMCP")
+
+# ============================================================================
+# 导入筛查器
+# ============================================================================
+
+import sys
+sys.path.insert(0, os.path.join(os.path.dirname(__file__), ".."))
+
+from psycho_screener.screener import PsychoScreener, ScreeningResult
+
+
+# ============================================================================
+# MCP Server
+# ============================================================================
+
+APP_NAME = "psycho-screener"
+APP_VERSION = "1.0.0"
+
+server = Server(APP_NAME)
+
+
+@server.list_tools()
+async def list_tools() -> list[Tool]:
+    """列出所有可用工具"""
+    return [
+        Tool(
+            name="psycho_screen",
+            description="对儿童对话进行心理问题筛查。当儿童与玩偶对话中可能存在霸凌、抑郁、焦虑、家庭矛盾等心理问题时，调用此工具进行分析。",
+            inputSchema={
+                "type": "object",
+                "properties": {
+                    "messages": {
+                        "type": "array",
+                        "description": "儿童与玩偶的完整对话上下文，格式为消息数组。每条消息包含 role（system/user/assistant）和 content（内容）。",
+                        "items": {
+                            "type": "object",
+                            "properties": {
+                                "role": {"type": "string"},
+                                "content": {"type": "string"}
+                            },
+                            "required": ["role", "content"]
+                        }
+                    },
+                    "include_prefix": {
+                        "type": "boolean",
+                        "default": True,
+                        "description": "检测到问题时是否返回注入前缀"
+                    }
+                },
+                "required": ["messages"]
+            }
+        )
+    ]
+
+
+@server.call_tool()
+async def call_tool(name: str, arguments: dict) -> list[TextContent]:
+    """执行工具调用"""
+    if name != "psycho_screen":
+        return [TextContent(type="text", text=json.dumps({"error": f"Unknown tool: {name}"}))]
+
+    messages = arguments.get("messages", [])
+    include_prefix = arguments.get("include_prefix", True)
+
+    api_key = os.environ.get("MINIMAX_API_KEY", "")
+    if not api_key:
+        result = {
+            "detected": False,
+            "category": "none",
+            "severity": "none",
+            "summary": "API key 未配置",
+            "suggestion": "",
+            "prefix": "",
+            "error": "MINIMAX_API_KEY not set"
+        }
+        return [TextContent(type="text", text=json.dumps(result, ensure_ascii=False))]
+
+    try:
+        # 提取孩子消息
+        child_messages = [
+            msg["content"]
+            for msg in messages
+            if msg.get("role") == "user" and msg.get("content")
+        ]
+        context = "\n".join(child_messages)
+
+        if not context.strip():
+            result = {
+                "detected": False,
+                "category": "none",
+                "severity": "none",
+                "summary": "无儿童对话内容可分析",
+                "suggestion": "",
+                "prefix": ""
+            }
+            return [TextContent(type="text", text=json.dumps(result, ensure_ascii=False))]
+
+        # 调用筛查器
+        screener = PsychoScreener(api_key=api_key)
+        screening_result = screener.screen(context)
+
+        # 构建结果
+        result: dict = {
+            "detected": screening_result.detected,
+            "category": screening_result.category,
+            "severity": "none" if not screening_result.detected else screening_result.severity,
+            "summary": screening_result.summary,
+            "suggestion": screening_result.suggestion if screening_result.detected else "",
+        }
+
+        if include_prefix and screening_result.detected:
+            result["prefix"] = screener.build_response_prefix(screening_result)
+
+        logger.info(
+            f"psycho_screen: detected={screening_result.detected}, "
+            f"category={screening_result.category}, severity={screening_result.severity}"
+        )
+
+        return [TextContent(type="text", text=json.dumps(result, ensure_ascii=False))]
+
+    except Exception as e:
+        logger.exception(f"psycho_screen error: {e}")
+        result = {
+            "detected": False,
+            "category": "none",
+            "severity": "none",
+            "summary": f"筛查过程出错: {str(e)}",
+            "suggestion": "",
+            "prefix": "",
+            "error": str(e)
+        }
+        return [TextContent(type="text", text=json.dumps(result, ensure_ascii=False))]
+
+
+# ============================================================================
+# 主入口
+# ============================================================================
+
+async def main():
+    """启动 MCP stdio 服务器"""
+    logger.info(f"启动 PsychoScreener MCP 服务器 v{APP_VERSION}")
+    async with stdio_server() as (read_stream, write_stream):
+        await server.run(
+            read_stream,
+            write_stream,
+            server.create_initialization_options()
+        )
+
+
+if __name__ == "__main__":
+    import asyncio
+    asyncio.run(main())

test_xiaozhi_client.py

@@ -0,0 +1,65 @@
+#!/usr/bin/env python3
+"""
+小智设备连接测试客户端
+连接到 xiaozhi-server，模拟设备握手，触发 MCP 工具初始化
+"""
+
+import asyncio
+import json
+import uuid
+import websockets
+import sys
+
+XIAOZHI_WS = "ws://localhost:8000/xiaozhi/v1/"
+DEVICE_ID = str(uuid.uuid4())
+TOPIC = str(uuid.uuid4())
+
+
+async def main():
+    print(f"连接 xiaozhi-server: {XIAOZHI_WS}")
+    print(f"Device ID: {DEVICE_ID}")
+
+    async with websockets.connect(XIAOZHI_WS, ping_interval=None) as ws:
+        # 发送设备 hello
+        hello = {
+            "type": "hello",
+            "deviceId": DEVICE_ID,
+            "deviceName": "测试设备",
+            "clientType": "py-websocket-test",
+            "protocolVersion": "1.0.0",
+            "featureSet": {"mcp": True},
+        }
+        await ws.send(json.dumps(hello))
+        print(f"发送 hello: {hello}")
+
+        # 接收消息（最多等 30 秒）
+        for i in range(20):
+            try:
+                msg = await asyncio.wait_for(ws.recv(), timeout=5.0)
+                data = json.loads(msg)
+                msg_type = data.get("type", "unknown")
+                print(f"收到 [{msg_type}]: {json.dumps(data, ensure_ascii=False)[:200]}")
+                
+                if msg_type == "welcome":
+                    print("\n✅ 连接成功！")
+                    if "tools" in data:
+                        print(f"MCP 工具列表: {[t.get('name') for t in data.get('tools', [])]}")
+                    if "mcpTools" in data:
+                        print(f"MCP 工具: {data.get('mcpTools')}")
+                    break
+            except asyncio.TimeoutError:
+                print(f"  ... 等待中 ({i+1}/20)")
+                continue
+
+        print("\n测试完成，5秒后关闭...")
+        await asyncio.sleep(5)
+
+
+if __name__ == "__main__":
+    try:
+        asyncio.run(main())
+    except KeyboardInterrupt:
+        print("\n已退出")
+    except Exception as e:
+        print(f"错误: {e}")
+        sys.exit(1)

xiaozhi_cli_client.py

@@ -0,0 +1,238 @@
+#!/usr/bin/env python3
+"""
+小智 AI CLI 客户端 - 简化版（含 MCP 工具处理）
+
+功能：
+    - 连接 xiaozhi-server
+    - 声明 MCP 能力
+    - 发送文本对话
+    - 服务器可调用 MCP 工具（psycho_screen）
+    - 客户端将 MCP 调用转发给 psycho-screener stdio 工具
+    - 返回结果给服务器
+
+用法：
+    python xiaozhi_cli_client.py "今天小朋友打我，我好害怕"
+"""
+
+import asyncio
+import json
+import uuid
+import sys
+import argparse
+import websockets
+import subprocess
+import os
+
+DEVICE_ID = str(uuid.uuid4())
+WS_URL = "ws://localhost:8000/xiaozhi/v1/"
+MINIMAX_API_KEY = os.environ.get(
+    "MINIMAX_API_KEY",
+    "sk-cp-Sd2G0paJUZWdQhKrISIICVqQnuiE4qvT-yMszahI7s0Sau02Pa1XZCXNsj2Z91n-xNV8hIG-xL8lENaEgFNQBZr7S6Y8_R7OASOScenpJIxxWOb6vc7sF38"
+)
+
+
+# ============================================================================
+# MCP 工具调用处理
+# ============================================================================
+
+def _mcp_call_sync(messages: list, include_prefix: bool) -> dict:
+    """同步调用 MCP 工具（在独立线程中运行）"""
+    import select, threading
+
+    script_path = os.path.join(os.path.dirname(__file__), "src", "psycho_screener", "mcp_tool_native.py")
+    env = {**os.environ, "MINIMAX_API_KEY": MINIMAX_API_KEY}
+    proc = subprocess.Popen(
+        [sys.executable, script_path],
+        stdin=subprocess.PIPE, stdout=subprocess.PIPE, stderr=subprocess.PIPE,
+        text=True, env=env,
+    )
+
+    _id = [0]
+    def send(msg):
+        _id[0] += 1
+        msg["id"] = _id[0]
+        proc.stdin.write(json.dumps(msg) + "\n")
+        proc.stdin.flush()
+        if select.select([proc.stdout], [], [], 20)[0]:
+            return json.loads(proc.stdout.readline())
+        return None
+
+    try:
+        send({"jsonrpc": "2.0", "method": "initialize", "params": {
+            "protocolVersion": "2024-11-05", "capabilities": {},
+            "clientInfo": {"name": "xiaozhi-cli", "version": "1.0"}
+        }})
+        proc.stdin.write(json.dumps({"jsonrpc": "2.0", "method": "notifications/initialized"}) + "\n")
+        proc.stdin.flush()
+
+        r = send({"jsonrpc": "2.0", "method": "tools/call", "params": {
+            "name": "psycho_screen",
+            "arguments": {"messages": messages, "include_prefix": include_prefix}
+        }})
+        if r and "result" in r:
+            return json.loads(r["result"][0]["text"])
+        return {"error": "no result"}
+    finally:
+        proc.terminate()
+        proc.wait(timeout=3)
+
+
+async def call_psycho_screener(messages: list, include_prefix: bool = True) -> dict:
+    """异步调用（在独立线程池中运行同步 subprocess）"""
+    loop = asyncio.get_event_loop()
+    return await loop.run_in_executor(None, _mcp_call_sync, messages, include_prefix)
+
+
+def build_mcp_response(req_id: int | str, result: dict) -> dict:
+    """构建 MCP JSON-RPC 成功响应"""
+    return {
+        "type": "mcp",
+        "payload": {
+            "jsonrpc": "2.0",
+            "id": req_id,
+            "result": {
+                "content": [{"type": "text", "text": json.dumps(result, ensure_ascii=False)}],
+                "isError": False,
+            }
+        }
+    }
+
+
+# ============================================================================
+# WebSocket 客户端
+# ============================================================================
+
+async def run_single(text: str):
+    print(f"\n{'='*60}")
+    print(f"设备ID: {DEVICE_ID}")
+    print(f"发送: {text}")
+    print(f"{'='*60}\n")
+
+    url = f"{WS_URL}?device-id={DEVICE_ID}&authorization=cli"
+    async with websockets.connect(url, ping_interval=None, max_size=10 * 1024 * 1024) as ws:
+        # 1. 发 hello，等 welcome（含工具列表）
+        await ws.send(json.dumps({
+            "type": "hello", "version": 1,
+            "features": {"mcp": True},
+            "transport": "websocket",
+            "audio_params": {"format": "opus", "sample_rate": 16000, "channels": 1, "frame_duration": 60},
+        }))
+        raw = await asyncio.wait_for(ws.recv(), timeout=10.0)
+        welcome = json.loads(raw)
+        print(f"[服务器] type={welcome.get('type')}, session={welcome.get('session_id','')[:16]}")
+        tools = [t.get("name") for t in welcome.get("tools", [])]
+        print(f"[工具列表] {tools}")
+
+        # 2. 发文本（用 listen 消息类型）
+        await ws.send(json.dumps({"type": "listen", "state": "detect", "text": text}))
+        print("[已发送文本]\n")
+
+        # 3. 循环收消息，处理 MCP 调用
+        replies = []
+        mcp_init_id = None
+
+        for i in range(30):
+            try:
+                raw = await asyncio.wait_for(ws.recv(), timeout=30.0)
+                try:
+                    data = json.loads(raw)
+                except (json.JSONDecodeError, UnicodeDecodeError):
+                    # 二进制音频数据，跳过
+                    print(f"[二进制数据] (跳过 {len(raw)} bytes)")
+                    continue
+                t = data.get("type")
+
+                if t == "mcp":
+                    payload = data.get("payload", {})
+                    method = payload.get("method")
+                    req_id = payload.get("id")
+                    params = payload.get("params", {})
+
+                    if method == "initialize":
+                        print(f"[MCP] initialize 请求")
+                        resp = {
+                            "type": "mcp",
+                            "payload": {
+                                "jsonrpc": "2.0", "id": req_id,
+                                "result": {
+                                    "protocolVersion": "2024-11-05",
+                                    "capabilities": {"tools": {}},
+                                    "serverInfo": {"name": "xiaozhi-cli", "version": "1.0"}
+                                }
+                            }
+                        }
+                        await ws.send(json.dumps(resp))
+                        print("[MCP] 已回复 initialize")
+
+                    elif method == "tools/call":
+                        tool_name = params.get("name")
+                        args = params.get("arguments", {})
+                        print(f"[MCP] 调用工具: {tool_name}")
+
+                        if tool_name == "psycho_screen":
+                            # 调用我们的筛查器
+                            result = await call_psycho_screener(
+                                messages=args.get("messages", []),
+                                include_prefix=args.get("include_prefix", True),
+                            )
+                            resp = build_mcp_response(req_id, result)
+                            await ws.send(json.dumps(resp))
+                            print(f"[MCP] 筛查结果: detected={result.get('detected')}, category={result.get('category')}")
+                            if result.get("prefix"):
+                                print(f"[MCP] 前缀: {result['prefix'][:80]}")
+                        else:
+                            print(f"[MCP] 未知工具: {tool_name}")
+
+                elif t == "text":
+                    content = data.get("content", "")
+                    replies.append(content)
+                    print(f"[玩偶] {content[:200]}")
+
+                elif t == "llm":
+                    print(f"[LLM] {str(data)[:150]}")
+
+                elif t == "tts":
+                    print("[TTS] (音频跳过)")
+
+                elif t == "error":
+                    print(f"[ERROR] {data}")
+
+                else:
+                    print(f"[{t}] {str(data)[:100]}")
+
+                # 收到第二条文本后退出
+                if t == "text" and len(replies) >= 2:
+                    break
+
+            except asyncio.TimeoutError:
+                print(f"[超时 {i+1}/30]")
+                if i > 3:
+                    break
+
+        print(f"\n{'='*60}")
+        print(f"完成！收到 {len(replies)} 条玩偶回复")
+        for j, r in enumerate(replies):
+            print(f"  回复{j+1}: {r[:300]}")
+        print(f"{'='*60}\n")
+        return True
+
+
+async def main():
+    parser = argparse.ArgumentParser(description="小智 AI CLI 客户端（含 MCP）")
+    parser.add_argument("text", nargs="?", help="对话内容")
+    parser.add_argument("--interactive", "-i", action="store_true", help="交互模式")
+    args = parser.parse_args()
+    if args.interactive or not args.text:
+        print("交互模式暂不支持 MCP 工具处理")
+    else:
+        await run_single(args.text)
+
+
+if __name__ == "__main__":
+    try:
+        asyncio.run(main())
+    except KeyboardInterrupt:
+        print("\n已退出")
+    except Exception as e:
+        print(f"[错误] {e}")
+        sys.exit(1)