feat: 添加MCP服务器初始实现及相关文件

添加MCP服务器的初始实现，包括： - 主程序文件mcp_server.py - 配置文件config.toml - 依赖文件requirements.txt - 安装指南INSTALL.md - 使用说明README.md 服务器功能包括： - 接收客户端请求 - 调用OpenAI API进行分析 - 提供健康检查接口 - 支持与disk_inspection.py脚本对接
2025-09-10 22:15:10 +08:00
parent 107b20a410
commit 79cdb45e20
5 changed files with 0 additions and 0 deletions
--- a/mcp_server-py/mcp_server.py
+++ b/mcp_server-py/mcp_server.py
@@ -0,0 +1,188 @@
+#!/usr/bin/env python3
+# -*- coding: UTF-8 -*-
+
+import os
+import sys
+import logging
+import json
+import toml
+import traceback
+from flask import Flask, request, jsonify
+import openai
+
+class MCPServer:
+    def __init__(self):
+        # 初始化应用
+        self.app = Flask(__name__)
+        # 加载配置
+        self.config = self.load_config()
+        # 配置日志
+        self.setup_logging()
+        # 配置OpenAI客户端
+        self.setup_openai()
+        # 注册路由
+        self.register_routes()
+
+    def load_config(self):
+        """加载配置文件"""
+        config_path = os.path.join(os.path.dirname(__file__), "config.toml")
+        if not os.path.exists(config_path):
+            print(f"错误：配置文件不存在: {config_path}")
+            sys.exit(1)
+        
+        with open(config_path, "r", encoding="utf-8") as f:
+            return toml.load(f)
+
+    def setup_logging(self):
+        """配置日志系统"""
+        log_config = self.config.get("logging", {})
+        log_level = getattr(logging, log_config.get("level", "info").upper())
+        log_format = log_config.get("format", "text")
+        log_file = log_config.get("file_path", "/var/log/mcp_server.log")
+        
+        # 确保日志目录存在
+        log_dir = os.path.dirname(log_file)
+        if log_dir and not os.path.exists(log_dir):
+            os.makedirs(log_dir, exist_ok=True)
+        
+        # 配置日志格式
+        if log_format == "json":
+            formatter = logging.Formatter(
+                '{"time":"%(asctime)s", "level":"%(levelname)s", "message":"%(message)s"}'
+            )
+        else:
+            formatter = logging.Formatter(
+                '%(asctime)s - %(name)s - %(levelname)s - %(message)s'
+            )
+        
+        # 配置文件日志
+        file_handler = logging.FileHandler(log_file, encoding="utf-8")
+        file_handler.setFormatter(formatter)
+        
+        # 配置控制台日志
+        console_handler = logging.StreamHandler()
+        console_handler.setFormatter(formatter)
+        
+        # 获取根logger并配置
+        logger = logging.getLogger()
+        logger.setLevel(log_level)
+        logger.addHandler(file_handler)
+        logger.addHandler(console_handler)
+        
+        self.logger = logging.getLogger("MCPServer")
+
+    def setup_openai(self):
+        """配置OpenAI客户端"""
+        openai_config = self.config.get("openai", {})
+        openai.api_key = openai_config.get("api_key")
+        
+        # 如果配置了自定义API基础URL
+        if "base_url" in openai_config:
+            openai.api_base = openai_config["base_url"]
+        
+        self.openai_config = openai_config
+
+    def register_routes(self):
+        """注册API路由"""
+        @self.app.route("/mcp/v1/submit", methods=["POST"])
+        def submit_data():
+            """接收并处理MCP提交的数据"""
+            try:
+                # 获取请求数据
+                data = request.get_json()
+                if not data:
+                    self.logger.warning("接收到无效的JSON数据")
+                    return jsonify({"error": "无效的JSON数据"}), 400
+                
+                self.logger.info(f"接收到MCP提交请求，类型: {data.get('type')}")
+                
+                # 处理提交的数据
+                result = self.process_submission(data)
+                
+                return jsonify({"status": "success", "result": result})
+            except Exception as e:
+                self.logger.error(f"处理提交请求时出错: {str(e)}")
+                self.logger.debug(traceback.format_exc())
+                return jsonify({"error": str(e)}), 500
+        
+        @self.app.route("/health", methods=["GET"])
+        def health_check():
+            """健康检查接口"""
+            return jsonify({"status": "healthy"}), 200
+
+    def process_submission(self, data):
+        """处理提交的数据，调用OpenAI API进行分析"""
+        submission_type = data.get("type", "")
+        content = data.get("content", "")
+        timestamp = data.get("timestamp", "")
+        
+        # 根据数据类型生成不同的提示词
+        if submission_type == "disk_inspection_report":
+            prompt = self.generate_disk_report_prompt(content)
+        else:
+            prompt = f"请分析以下数据（类型：{submission_type}）：\n{content}"
+        
+        # 调用OpenAI API
+        response = self.call_openai_api(prompt)
+        
+        return {
+            "analysis": response,
+            "processed_at": self.get_current_timestamp(),
+            "original_type": submission_type
+        }
+
+    def generate_disk_report_prompt(self, report_content):
+        """为硬盘巡检报告生成特定的提示词"""
+        return f"""你是一位专业的系统管理员，请分析以下硬盘巡检报告：
+
+{report_content}
+
+请提供详细的分析结果，包括：
+1. 健康状态总结
+2. 异常项分析（如果有）
+3. 潜在风险评估
+4. 维护建议
+5. 需要特别关注的问题（如果有）"""
+
+    def call_openai_api(self, prompt):
+        """调用OpenAI API"""
+        try:
+            # 调用OpenAI ChatCompletion API
+            response = openai.ChatCompletion.create(
+                model=self.openai_config.get("model", "gpt-3.5-turbo"),
+                messages=[
+                    {"role": "system", "content": "你是一个专业的AI助手，帮助用户分析和处理各种数据。"},
+                    {"role": "user", "content": prompt}
+                ],
+                max_tokens=self.openai_config.get("max_tokens", 2048),
+                temperature=self.openai_config.get("temperature", 0.7)
+            )
+            
+            # 提取回复内容
+            return response["choices"][0]["message"]["content"].strip()
+        except Exception as e:
+            self.logger.error(f"调用OpenAI API时出错: {str(e)}")
+            raise
+
+    def get_current_timestamp(self):
+        """获取当前时间戳"""
+        import datetime
+        return datetime.datetime.now().isoformat()
+
+    def run(self):
+        """启动服务器"""
+        server_config = self.config.get("server", {})
+        host = server_config.get("host", "0.0.0.0")
+        port = server_config.get("port", 8080)
+        debug = server_config.get("debug", False)
+        
+        self.logger.info(f"MCP服务器启动成功，监听地址: {host}:{port}")
+        self.logger.info(f"OpenAI API配置: 模型={self.openai_config.get('model')}")
+        
+        # 启动Flask服务器
+        self.app.run(host=host, port=port, debug=debug)
+
+if __name__ == "__main__":
+    # 创建并运行MCP服务器
+    server = MCPServer()
+    server.run()