MineNasAI/PoC验证.md

MineNASAI - PoC 验证计划

创建日期: 2025-02-04 目标: 验证3个关键技术的可行性 预计时间: 2-3天

---

验证目标

为什么需要 PoC？

在投入大量时间开发之前，我们需要验证以下关键技术的可行性：

1. Claude Code CLI 集成 (最高优先级)

   • 风险：子进程管理、输出解析复杂
   • 影响：这是核心功能，如果不可行需要重新设计

2. 智能路由算法

   • 风险：路由准确度不足
   • 影响：影响用户体验和资源利用率

3. MCP Server 加载

   • 风险：MCP协议不熟悉、进程通信复杂
   • 影响：工具扩展能力的基础

---

PoC 1: Claude Code CLI 集成

目标

验证可以通过 Python 子进程调用 Claude Code CLI，并正确解析其输出。

验证内容

• 子进程启动和管理
• 实时输出流捕获
• ANSI 转义序列处理
• 交互式输入处理
• 超时和资源限制
• 错误处理和恢复

实施步骤

步骤1: 环境准备

# 1. 确保已安装 Claude Code CLI
# 如果没有,访问: https://docs.anthropic.com/claude/docs/claude-code

# 2. 验证 CLI 可用
claude --version

# 3. 测试基本调用
claude "print hello world in python"

# 4. 创建 PoC 工作目录
mkdir -p poc/claude_cli_test
cd poc/claude_cli_test

步骤2: 基础子进程调用 (poc_1_basic.py)

"""PoC 1.1: Basic Claude CLI subprocess call."""
import subprocess
import sys

def test_basic_call():
    """测试基本的 CLI 调用."""
    print("=== PoC 1.1: Basic CLI Call ===\n")
    
    # 简单命令
    cmd = ["claude", "print hello world in python"]
    
    print(f"执行命令: {' '.join(cmd)}")
    print("-" * 60)
    
    try:
        # 使用 subprocess.run
        result = subprocess.run(
            cmd,
            capture_output=True,
            text=True,
            timeout=30,
        )
        
        print("STDOUT:")
        print(result.stdout)
        print("\nSTDERR:")
        print(result.stderr)
        print(f"\n退出码: {result.returncode}")
        
        if result.returncode == 0:
            print("\n✅ 基础调用成功!")
            return True
        else:
            print("\n❌ 命令执行失败")
            return False
            
    except subprocess.TimeoutExpired:
        print("\n❌ 命令超时")
        return False
    except Exception as e:
        print(f"\n❌ 异常: {e}")
        return False


if __name__ == "__main__":
    success = test_basic_call()
    sys.exit(0 if success else 1)

验收标准:

• 脚本可以成功调用 Claude CLI
• 可以捕获完整输出
• 超时机制生效

运行测试:

python poc_1_basic.py

---

步骤3: 实时输出流捕获 (poc_1_streaming.py)

"""PoC 1.2: Real-time output streaming."""
import subprocess
import sys
import select
import os


def test_streaming_output():
    """测试实时输出流捕获."""
    print("=== PoC 1.2: Streaming Output ===\n")
    
    cmd = ["claude", "count to 10 with 1 second delays in python"]
    
    print(f"执行命令: {' '.join(cmd)}")
    print("-" * 60)
    
    try:
        # 使用 Popen 进行流式输出
        process = subprocess.Popen(
            cmd,
            stdout=subprocess.PIPE,
            stderr=subprocess.PIPE,
            text=True,
            bufsize=1,  # 行缓冲
        )
        
        print("实时输出:")
        
        # 实时读取输出
        while True:
            # 检查进程是否结束
            if process.poll() is not None:
                break
            
            # 读取一行输出
            line = process.stdout.readline()
            if line:
                print(f"[OUT] {line.rstrip()}")
            
            # 读取错误输出
            # 注意: stderr 需要非阻塞读取或使用 select
            
        # 获取剩余输出
        remaining_out, remaining_err = process.communicate()
        if remaining_out:
            print(remaining_out)
        
        print(f"\n退出码: {process.returncode}")
        
        if process.returncode == 0:
            print("\n✅ 流式输出捕获成功!")
            return True
        else:
            print("\n❌ 进程执行失败")
            return False
            
    except Exception as e:
        print(f"\n❌ 异常: {e}")
        return False


if __name__ == "__main__":
    success = test_streaming_output()
    sys.exit(0 if success else 1)

验收标准:

• 可以实时捕获输出（不是等待结束）
• 输出不会丢失
• 可以正确检测进程结束

运行测试:

python poc_1_streaming.py

---

步骤4: PTY 伪终端处理 (poc_1_pty.py)

"""PoC 1.3: PTY pseudo-terminal for interactive handling."""
import pty
import os
import sys
import select
import subprocess


def test_pty_terminal():
    """测试 PTY 伪终端处理."""
    print("=== PoC 1.3: PTY Terminal ===\n")
    
    cmd = ["claude", "create a simple python calculator"]
    
    print(f"执行命令: {' '.join(cmd)}")
    print("-" * 60)
    
    try:
        # 创建 PTY
        master, slave = pty.openpty()
        
        # 启动进程
        process = subprocess.Popen(
            cmd,
            stdin=slave,
            stdout=slave,
            stderr=slave,
            close_fds=True,
        )
        
        os.close(slave)  # 子进程已继承，关闭父进程的副本
        
        print("实时输出 (PTY):")
        output_buffer = []
        
        # 读取输出
        while True:
            # 检查进程是否结束
            if process.poll() is not None:
                break
            
            # 使用 select 进行非阻塞读取
            r, w, e = select.select([master], [], [], 0.1)
            
            if master in r:
                try:
                    data = os.read(master, 1024)
                    if data:
                        text = data.decode('utf-8', errors='replace')
                        print(text, end='')
                        output_buffer.append(text)
                except OSError:
                    break
        
        os.close(master)
        
        print(f"\n\n退出码: {process.returncode}")
        print(f"总输出长度: {len(''.join(output_buffer))} 字符")
        
        if process.returncode == 0:
            print("\n✅ PTY 终端处理成功!")
            return True
        else:
            print("\n❌ 进程执行失败")
            return False
            
    except Exception as e:
        print(f"\n❌ 异常: {e}")
        import traceback
        traceback.print_exc()
        return False


if __name__ == "__main__":
    success = test_pty_terminal()
    sys.exit(0 if success else 1)

验收标准:

• PTY 可以正确创建
• 可以处理交互式输出
• ANSI 转义序列正确显示

运行测试:

python poc_1_pty.py

---

步骤5: 完整集成示例 (poc_1_full.py)

"""PoC 1.4: Full Claude CLI integration."""
import asyncio
import pty
import os
import select
import subprocess
from dataclasses import dataclass
from typing import Optional


@dataclass
class CLIResult:
    """CLI execution result."""
    exit_code: int
    output: str
    error: Optional[str] = None
    duration_ms: int = 0


class ClaudeCLI:
    """Claude CLI wrapper."""
    
    def __init__(self, timeout: int = 300):
        """Initialize CLI wrapper."""
        self.timeout = timeout
    
    async def execute(self, prompt: str, workspace: str = ".") -> CLIResult:
        """
        Execute Claude CLI command.
        
        Args:
            prompt: 任务提示
            workspace: 工作目录
            
        Returns:
            CLIResult with output
        """
        import time
        start_time = time.time()
        
        cmd = ["claude", prompt]
        
        try:
            # 创建 PTY
            master, slave = pty.openpty()
            
            # 启动进程
            process = subprocess.Popen(
                cmd,
                stdin=slave,
                stdout=slave,
                stderr=slave,
                cwd=workspace,
                close_fds=True,
            )
            
            os.close(slave)
            
            # 收集输出
            output_buffer = []
            
            # 读取输出 (带超时)
            timeout_time = start_time + self.timeout
            
            while True:
                # 检查超时
                if time.time() > timeout_time:
                    process.kill()
                    raise TimeoutError(f"Command timeout after {self.timeout}s")
                
                # 检查进程是否结束
                if process.poll() is not None:
                    break
                
                # 非阻塞读取
                r, w, e = select.select([master], [], [], 0.1)
                
                if master in r:
                    try:
                        data = os.read(master, 4096)
                        if data:
                            text = data.decode('utf-8', errors='replace')
                            output_buffer.append(text)
                    except OSError:
                        break
            
            os.close(master)
            
            duration_ms = int((time.time() - start_time) * 1000)
            output = ''.join(output_buffer)
            
            return CLIResult(
                exit_code=process.returncode,
                output=output,
                duration_ms=duration_ms,
            )
            
        except TimeoutError as e:
            return CLIResult(
                exit_code=-1,
                output=''.join(output_buffer),
                error=str(e),
                duration_ms=int((time.time() - start_time) * 1000),
            )
        except Exception as e:
            return CLIResult(
                exit_code=-1,
                output='',
                error=str(e),
                duration_ms=int((time.time() - start_time) * 1000),
            )


async def test_full_integration():
    """测试完整集成."""
    print("=== PoC 1.4: Full Integration ===\n")
    
    cli = ClaudeCLI(timeout=60)
    
    # 测试用例1: 简单任务
    print("测试1: 简单Python脚本")
    print("-" * 60)
    
    result = await cli.execute("create a hello world python script")
    
    print(f"输出:\n{result.output}")
    print(f"\n退出码: {result.exit_code}")
    print(f"耗时: {result.duration_ms}ms")
    
    if result.exit_code == 0:
        print("✅ 测试1通过")
    else:
        print(f"❌ 测试1失败: {result.error}")
        return False
    
    # 测试用例2: 需要多步骤的任务
    print("\n\n测试2: 多步骤任务")
    print("-" * 60)
    
    result = await cli.execute(
        "create a simple REST API with FastAPI that has a hello endpoint"
    )
    
    print(f"输出:\n{result.output[:500]}...")  # 只显示前500字符
    print(f"\n退出码: {result.exit_code}")
    print(f"耗时: {result.duration_ms}ms")
    
    if result.exit_code == 0:
        print("✅ 测试2通过")
    else:
        print(f"❌ 测试2失败: {result.error}")
        return False
    
    print("\n" + "=" * 60)
    print("✅ 完整集成验证通过!")
    print("=" * 60)
    
    return True


if __name__ == "__main__":
    success = asyncio.run(test_full_integration())
    import sys
    sys.exit(0 if success else 1)

验收标准:

• 封装类可以正常工作
• 支持异步调用
• 超时控制有效
• 错误处理完善
• 可以处理简单和复杂任务

运行测试:

python poc_1_full.py

---

PoC 1 总结

完成上述5个步骤后，填写以下清单：

验证结果:

• 基础调用可行
• 流式输出捕获可行
• PTY终端处理可行
• 完整集成验证通过
• 性能可接受 (大多数任务 < 1分钟)

发现的问题: 1. 2. 3.

需要的改进: 1. 2. 3.

结论:

• ✅ 可行，建议使用 PTY + asyncio 方案
• ⚠️ 部分可行，需要调整设计
• ❌ 不可行，需要备选方案

---

PoC 2: 智能路由算法

目标

验证路由算法可以合理地将任务分类为 fast/medium/deep 三种模式。

验证内容

• 启发式规则准确度
• LLM-based 路由可行性
• 用户指令覆盖
• 路由性能 (响应时间)

实施步骤

步骤1: 启发式规则测试 (poc_2_heuristic.py)

"""PoC 2.1: Heuristic routing rules."""
from dataclasses import dataclass
from typing import Literal


@dataclass
class RoutingDecision:
    """Routing decision."""
    mode: Literal["fast", "medium", "deep"]
    reason: str
    confidence: float  # 0.0 - 1.0


class HeuristicRouter:
    """Heuristic-based router."""
    
    def __init__(self):
        """Initialize rules."""
        self.rules = {
            "fast_keywords": ["状态", "查询", "搜索", "是什么", "?", "？"],
            "deep_keywords": ["实现", "开发", "编写", "重构", "优化", "设计", "创建"],
            "medium_keywords": ["修改", "更新", "添加", "删除"],
        }
    
    def evaluate(self, message: str) -> RoutingDecision:
        """Evaluate routing decision."""
        message_lower = message.lower()
        length = len(message)
        
        # 规则1: 短消息 + 查询关键词 -> fast
        if length < 50 and any(kw in message_lower for kw in self.rules["fast_keywords"]):
            return RoutingDecision(
                mode="fast",
                reason="短消息且包含查询关键词",
                confidence=0.9,
            )
        
        # 规则2: 包含开发关键词 -> deep
        deep_count = sum(1 for kw in self.rules["deep_keywords"] if kw in message_lower)
        if deep_count >= 1:
            return RoutingDecision(
                mode="deep",
                reason=f"包含 {deep_count} 个开发关键词",
                confidence=0.7 + min(deep_count * 0.1, 0.2),
            )
        
        # 规则3: 中等长度 + 修改关键词 -> medium
        if 50 <= length <= 200 and any(kw in message_lower for kw in self.rules["medium_keywords"]):
            return RoutingDecision(
                mode="medium",
                reason="中等长度且包含修改关键词",
                confidence=0.6,
            )
        
        # 规则4: 长消息 -> medium/deep
        if length > 200:
            return RoutingDecision(
                mode="medium",
                reason="消息较长，可能需要多步处理",
                confidence=0.5,
            )
        
        # 默认: medium
        return RoutingDecision(
            mode="medium",
            reason="默认中等复杂度",
            confidence=0.4,
        )


def test_heuristic_router():
    """测试启发式路由."""
    print("=== PoC 2.1: Heuristic Router ===\n")
    
    router = HeuristicRouter()
    
    # 测试用例
    test_cases = [
        ("NAS状态?", "fast"),
        ("搜索最新的Python教程", "fast"),
        ("实现一个Web服务", "deep"),
        ("重构这个模块", "deep"),
        ("修改配置文件中的端口", "medium"),
        ("添加一个新的API端点", "medium"),
        ("这是一段很长的描述，我需要你帮我分析一下这个系统的架构，然后给出优化建议，包括性能、安全性和可维护性等多个方面", "medium"),
    ]
    
    correct = 0
    total = len(test_cases)
    
    print(f"测试用例数: {total}\n")
    
    for i, (message, expected) in enumerate(test_cases, 1):
        decision = router.evaluate(message)
        is_correct = decision.mode == expected
        correct += is_correct
        
        status = "✅" if is_correct else "❌"
        print(f"{status} 用例 {i}:")
        print(f"   消息: {message}")
        print(f"   预期: {expected}")
        print(f"   实际: {decision.mode} (置信度: {decision.confidence:.2f})")
        print(f"   理由: {decision.reason}")
        print()
    
    accuracy = correct / total
    print("=" * 60)
    print(f"准确率: {accuracy:.1%} ({correct}/{total})")
    print("=" * 60)
    
    if accuracy >= 0.7:
        print("\n✅ 启发式规则准确度可接受 (>= 70%)")
        return True
    else:
        print(f"\n⚠️ 准确度较低 ({accuracy:.1%}), 建议优化规则或使用LLM")
        return False


if __name__ == "__main__":
    import sys
    success = test_heuristic_router()
    sys.exit(0 if success else 1)

验收标准:

• 准确率 >= 70%
• 置信度评分合理
• 响应时间 < 10ms

运行测试:

python poc_2_heuristic.py

---

步骤2: LLM 路由测试 (poc_2_llm.py)

"""PoC 2.2: LLM-based routing."""
import asyncio
import os
from anthropic import AsyncAnthropic


class LLMRouter:
    """LLM-based router using Claude Haiku."""
    
    def __init__(self, api_key: str):
        """Initialize with API key."""
        self.client = AsyncAnthropic(api_key=api_key)
        self.model = "claude-3-5-haiku-20241022"
    
    async def evaluate(self, message: str) -> dict:
        """Evaluate using Claude Haiku."""
        system_prompt = """
你是一个智能路由助手。分析用户消息，判断任务复杂度:

- **fast**: 简单查询，不需要复杂工具 (<1000 tokens)
  例如: "NAS状态?", "搜索xxx", "是什么"
  
- **medium**: 中等任务，需要少量工具调用 (<5000 tokens)
  例如: "修改配置", "添加功能", "更新文档"
  
- **deep**: 复杂任务，需要编程或多步骤处理 (>5000 tokens)
  例如: "实现xxx", "重构xxx", "设计xxx"

返回 JSON 格式:
{
    "mode": "fast|medium|deep",
    "reason": "判断理由",
    "confidence": 0.0-1.0
}
"""
        
        try:
            response = await self.client.messages.create(
                model=self.model,
                max_tokens=200,
                system=system_prompt,
                messages=[
                    {"role": "user", "content": f"分析这个任务: {message}"}
                ]
            )
            
            # 解析响应
            import json
            text = response.content[0].text
            
            # 尝试提取JSON
            if "{" in text and "}" in text:
                json_str = text[text.find("{"):text.rfind("}")+1]
                result = json.loads(json_str)
                return result
            else:
                # 降级到启发式
                return {"mode": "medium", "reason": "LLM解析失败", "confidence": 0.5}
                
        except Exception as e:
            print(f"LLM路由失败: {e}")
            return {"mode": "medium", "reason": f"错误: {e}", "confidence": 0.0}


async def test_llm_router():
    """测试LLM路由."""
    print("=== PoC 2.2: LLM Router ===\n")
    
    # 检查API密钥
    api_key = os.getenv("ANTHROPIC_API_KEY")
    if not api_key:
        print("⚠️ 未设置 ANTHROPIC_API_KEY，跳过LLM测试")
        return True
    
    router = LLMRouter(api_key)
    
    # 测试用例
    test_cases = [
        ("NAS状态?", "fast"),
        ("实现一个Web服务", "deep"),
        ("修改配置文件中的端口", "medium"),
    ]
    
    print(f"测试用例数: {len(test_cases)}\n")
    
    for i, (message, expected) in enumerate(test_cases, 1):
        print(f"用例 {i}: {message}")
        result = await router.evaluate(message)
        
        is_correct = result["mode"] == expected
        status = "✅" if is_correct else "❌"
        
        print(f"   {status} 预期: {expected}, 实际: {result['mode']}")
        print(f"   理由: {result.get('reason', 'N/A')}")
        print(f"   置信度: {result.get('confidence', 0):.2f}")
        print()
    
    print("✅ LLM路由可行（需要API费用）")
    return True


if __name__ == "__main__":
    success = asyncio.run(test_llm_router())
    import sys
    sys.exit(0 if success else 1)

验收标准:

• LLM可以正确分类
• 响应时间可接受 (< 2秒)
• API费用在预算内

运行测试:

export ANTHROPIC_API_KEY="your-api-key"
python poc_2_llm.py

---

PoC 2 总结

验证结果:

• 启发式规则准确度: ____%
• LLM路由准确度: ____%
• LLM平均响应时间: ___ ms
• 单次LLM路由成本: $_____

结论:

• ✅ 启发式规则足够，先用规则
• ✅ 启发式 + LLM混合（低置信度时调用LLM）
• ⚠️ 仅使用LLM（成本和延迟较高）

---

PoC 3: MCP Server 加载

目标

验证可以动态加载和调用 MCP Server。

验证内容

• MCP Server 发现和启动
• MCP 协议通信 (stdio/sse)
• 工具调用和结果解析
• 进程生命周期管理

实施步骤

步骤1: 基础MCP连接 (poc_3_basic.py)

"""PoC 3.1: Basic MCP server connection."""
import asyncio
import subprocess
import json


async def test_mcp_connection():
    """测试 MCP Server 连接."""
    print("=== PoC 3.1: MCP Connection ===\n")
    
    # 使用官方 filesystem MCP server
    cmd = ["npx", "-y", "@modelcontextprotocol/server-filesystem", "/tmp"]
    
    print(f"启动 MCP Server: {' '.join(cmd)}")
    print("-" * 60)
    
    try:
        # 启动进程
        process = subprocess.Popen(
            cmd,
            stdin=subprocess.PIPE,
            stdout=subprocess.PIPE,
            stderr=subprocess.PIPE,
            text=True,
        )
        
        # 发送 initialize 请求
        initialize_request = {
            "jsonrpc": "2.0",
            "id": 1,
            "method": "initialize",
            "params": {
                "protocolVersion": "0.1.0",
                "capabilities": {},
                "clientInfo": {
                    "name": "poc-test",
                    "version": "0.1.0"
                }
            }
        }
        
        print("发送 initialize 请求...")
        process.stdin.write(json.dumps(initialize_request) + "\n")
        process.stdin.flush()
        
        # 读取响应
        response_line = process.stdout.readline()
        response = json.loads(response_line)
        
        print(f"收到响应: {json.dumps(response, indent=2)}")
        
        if "result" in response:
            print("\n✅ MCP 连接成功!")
            print(f"Server capabilities: {response['result'].get('capabilities', {})}")
            
            # 清理
            process.terminate()
            process.wait(timeout=5)
            return True
        else:
            print(f"\n❌ 初始化失败: {response.get('error')}")
            process.terminate()
            return False
            
    except Exception as e:
        print(f"\n❌ 异常: {e}")
        import traceback
        traceback.print_exc()
        return False


if __name__ == "__main__":
    success = asyncio.run(test_mcp_connection())
    import sys
    sys.exit(0 if success else 1)

验收标准:

• MCP Server可以启动
• initialize握手成功
• 可以正确解析响应

运行测试:

python poc_3_basic.py

---

步骤2: 工具调用测试 (poc_3_tools.py)

"""PoC 3.2: MCP tool calling."""
import asyncio
import subprocess
import json


async def test_mcp_tools():
    """测试 MCP 工具调用."""
    print("=== PoC 3.2: MCP Tools ===\n")
    
    cmd = ["npx", "-y", "@modelcontextprotocol/server-filesystem", "/tmp"]
    
    try:
        process = subprocess.Popen(
            cmd,
            stdin=subprocess.PIPE,
            stdout=subprocess.PIPE,
            stderr=subprocess.PIPE,
            text=True,
        )
        
        # Initialize
        initialize_request = {
            "jsonrpc": "2.0",
            "id": 1,
            "method": "initialize",
            "params": {
                "protocolVersion": "0.1.0",
                "capabilities": {},
                "clientInfo": {"name": "poc-test", "version": "0.1.0"}
            }
        }
        
        process.stdin.write(json.dumps(initialize_request) + "\n")
        process.stdin.flush()
        response = json.loads(process.stdout.readline())
        print(f"✓ Initialized")
        
        # List tools
        list_tools_request = {
            "jsonrpc": "2.0",
            "id": 2,
            "method": "tools/list",
            "params": {}
        }
        
        print("\n列出可用工具...")
        process.stdin.write(json.dumps(list_tools_request) + "\n")
        process.stdin.flush()
        response = json.loads(process.stdout.readline())
        
        if "result" in response:
            tools = response["result"].get("tools", [])
            print(f"✓ 找到 {len(tools)} 个工具:")
            for tool in tools:
                print(f"  - {tool['name']}: {tool.get('description', 'N/A')}")
            
            # 测试调用一个工具 (read_file)
            if tools:
                print("\n测试调用工具...")
                
                # 创建测试文件
                test_file = "/tmp/mcp_test.txt"
                with open(test_file, "w") as f:
                    f.write("Hello MCP!")
                
                call_tool_request = {
                    "jsonrpc": "2.0",
                    "id": 3,
                    "method": "tools/call",
                    "params": {
                        "name": "read_file",
                        "arguments": {"path": test_file}
                    }
                }
                
                process.stdin.write(json.dumps(call_tool_request) + "\n")
                process.stdin.flush()
                response = json.loads(process.stdout.readline())
                
                if "result" in response:
                    print(f"✓ 工具调用成功: {response['result']}")
                    print("\n✅ MCP 工具调用验证通过!")
                    
                    process.terminate()
                    return True
                else:
                    print(f"❌ 工具调用失败: {response.get('error')}")
            
        process.terminate()
        return False
        
    except Exception as e:
        print(f"\n❌ 异常: {e}")
        import traceback
        traceback.print_exc()
        return False


if __name__ == "__main__":
    success = asyncio.run(test_mcp_tools())
    import sys
    sys.exit(0 if success else 1)

验收标准:

• 可以列出工具
• 可以调用工具
• 结果解析正确

运行测试:

python poc_3_tools.py

---

PoC 3 总结

验证结果:

• MCP Server 可以启动
• 协议通信正常
• 工具调用成功
• 进程管理可控

发现的问题: 1. 2.

结论:

• ✅ MCP 集成可行
• ⚠️ 需要解决的问题:
• ❌ 不可行，需要替代方案

---

总体结论

完成所有 PoC 后，填写总体评估：

PoC 验证总结

PoC	状态	结论	备注
Claude CLI 集成	⏸️	-	-
智能路由算法	⏸️	-	-
MCP Server 加载	⏸️	-	-

风险评估更新

原有风险的验证结果:

1. Claude CLI集成复杂 (原风险等级: 高)

   • PoC 结果: ____
   • 新风险等级: ____
   • 建议: ____

2. 智能路由效果不佳 (原风险等级: 中)

   • PoC 结果: ____
   • 新风险等级: ____
   • 建议: ____

3. MCP Server不稳定 (原风险等级: 中)

   • PoC 结果: ____
   • 新风险等级: ____
   • 建议: ____

下一步建议

基于 PoC 结果:

• ✅ 所有验证通过，可以开始 Phase 0 正式开发
• ⚠️ 部分通过，需要调整设计后开发
• ❌ 关键技术不可行，需要重新规划

具体行动: 1. 2. 3.

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文档结束