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医疗营销系统任务自动化 MCP 插件\n\n这是一个基于 MCP(Model Context Protocol)的专业插件，用于自动化医疗营销系统的任务创建和管理。通过自然语言处理+LLM+SQL 的组合，实现完整的业务流程自动化。\n\n## 🚀 核心功能特点\n\n### 🎯 智能任务创建\n\n- **自然语言处理**: 通过简单的中文描述自动创建复杂的营销任务\n- **完整业务流程**: 自动处理项目 → 预算 → 任务 → 用户分配的完整链路\n- **DDL 精确分析**: 基于 INFORMATION_SCHEMA 的精确数据库结构分析\n- **多业务类型支持**: 支持 18 种业务类型，包括科普视频、文章、会议、问卷等\n\n### 🔧 技术特点\n\n- **模块化架构**: 采用类化设计，职责清晰，便于维护和扩展\n- **并行处理**: 多个数据查询并行执行，提升性能\n- **智能 SQL 生成**: 基于 DDL 智能分析的精确 SQL 生成引擎\n- **调试友好**: 提供 dry-run 模式，可预览生成的 SQL 而不执行\n- **缓存优化**: 智能缓存机制，提升重复查询性能\n- **错误重试**: 自动重试机制，提高系统稳定性\n\n### 🧠 业务智能\n\n- **DDL 智能分析**: 精确检测 NOT NULL 和 DEFAULT 值，智能处理字段约束\n- **字段分类优化**: 自动分类必须赋值字段、可跳过字段、系统管理字段\n- **数据关联**: 智能处理表间关联关系，确保数据一致性\n- **用户信息补全**: 自动获取用户详细信息，包括医院、电话等\n- **模式学习**: 分析历史数据，学习字段填充模式\n- **事务保护**: 完整的事务控制，确保数据操作的原子性\n\n## 📦 安装\n\n1. 克隆仓库\n\n```bash\ngit clone https://github.com/yourusername/doctor-task-mcp.git\ncd doctor-task-mcp\n```\n\n2. 安装依赖\n\n```bash\nnpm install\n```\n\n3. 配置环境变量\n\n```bash\ncp env.example .env\n# 编辑.env文件，填入数据库和LLM API配置\n```\n\n## 🛠️ 使用方法\n\n### 在命令行中使用\n\n```bash\nnpm start\n```\n\n### 在 Cursor 中使用\n\n本插件专为 Cursor Agent 集成设计，支持自然语言交互：\n\n**示例命令：**\n\n- \"创建一个科普视频任务分配给用户 534333094，预算 300 元，时间限制 10 天\"\n- \"帮我给用户 123 分配一个学术会议任务，预算 500 元\"\n- \"查看 marketing_project 表的结构\"\n\n## 🔧 MCP 工具列表\n\n### 核心工具\n\n1. **`create_task_with_llm`** - 智能任务创建引擎\n\n   - **输入**: 自然语言描述\n   - **输出**: 完整的任务创建 SQL + 执行结果\n   - **特性**:\n     - 支持 dry-run 调试模式\n     - DDL 精确分析\n     - 智能字段分类\n     - 缓存优化\n     - 错误重试机制\n   - **示例**: `\"创建一个科普视频任务分配给用户534333094，预算100000元，角色轻松医生\"`\n\n2. **`get_database_schema`** - 数据库结构分析器\n   - **输入**: 表名（可选）、是否包含样本数据\n   - **输出**: 表结构详情、字段约束、样本数据\n   - **特性**:\n     - INFORMATION_SCHEMA 集成\n     - 字段约束分析\n     - 默认值检测\n     - 样本数据展示\n\n### 技术参数\n\n- **LLM 提供商**: 支持 DeepSeek、OpenAI 等多种 LLM\n- **缓存策略**: 智能缓存，可选择启用/禁用\n- **超时设置**: 220 秒超时，最大 3 次重试\n- **事务控制**: 完整的 BEGIN/COMMIT 事务保护\n\n### 支持的业务类型\n\n| ID  | 业务类型 | 描述                 | ID  | 业务类型 | 描述               |\n| --- | -------- | -------------------- | --- | -------- | ------------------ |\n| 1   | 患教审核 | PATIENT_EDUCATION    | 10  | 科普直播 | POPULAR_LIVE       |\n| 2   | 公益直播 | LIVE                 | 11  | 社工服务 | SOCIAL_WORK        |\n| 3   | 调研问卷 | QUESTIONNAIRE        | 12  | 医学拜访 | MEDICAL_VISITS     |\n| 4   | 科普视频 | VIDEO                | 13  | 科普访谈 | POPULAR_INTERVIEW  |\n| 5   | 课件制作 | COURSEWARE           | 14  | 文章点评 | ARTICLE_REVIEW     |\n| 6   | 科普文章 | ARTICLE              | 15  | 视频点评 | VIDEO_REVIEW       |\n| 7   | 学术会议 | ACADEMIC_CONFERENCES | 16  | 病例征集 | CASE_COLLECTION    |\n| 8   | 学术拜访 | ACADEMIC_VISITS      | 17  | 文献解读 | LITERATURE_READING |\n| 9   | 临床研究 | CLINICAL_RESEARCH    | 18  | 文献点评 | LITERATURE_REVIEW  |\n\n**用户来源类型:**\n\n- 1: 轻松医生 | 2: 普通志愿者 | 3: 医生志愿者\n\n## 🏗️ 架构设计\n\n### 目录结构\n\n```\ndoctor-task-mcp/\n├── src/\n│   └── index.js           # 主程序入口\n├── package.json           # 项目配置\n├── env.example           # 环境变量模板\n├── tsconfig.json         # TypeScript配置\n├── README.md             # 项目说明\n└── 医疗营销系统数据库表关联关系完整文档.md  # 数据库文档\n```\n\n### 核心类架构 (v2.2.0)\n\n```javascript\n// 数据库操作管理 - DDL增强版\nclass DatabaseManager {\n  static createConnection()         // 创建连接池\n  static executeSQL()              // 事务化SQL执行\n  static getTableSchema()          // INFORMATION_SCHEMA集成\n  static getAllTables()            // 获取所有表\n  static getTableDDLInfo()         // DDL结构分析\n  static analyzeFieldConstraints() // 字段约束分析\n}\n\n// LLM接口管理 - 智能重试版\nclass LLMManager {\n  static makeRequest()             // 发送API请求（支持重试）\n  static analyzeTask()             // 任务意图智能分析\n  static generateSQL()             // DDL驱动的SQL生成\n  static buildLLMPrompt()          // 增强提示构建\n}\n\n// 数据分析工具 - 模式学习版\nclass DataAnalyzer {\n  static analyzeDefaultPatterns()  // 数据模式智能学习\n  static getLatestEntities()       // 最新记录获取\n  static getUserDetailedInfo()     // 用户信息补全\n  static formatRowInfo()           // 数据格式化显示\n  static detectFieldPatterns()     // 字段模式检测\n}\n\n// 业务逻辑控制 - 工作流增强版\nclass TaskBusinessLogic {\n  static getRelevantTables()       // 业务相关表获取\n  static checkConfig()             // 环境配置验证\n  static gatherContextInfo()       // 上下文信息收集\n  static gatherTablesCompleteInfo() // 完整表信息收集\n  static buildEnhancedPrompt()     // DDL驱动的提示构建\n}\n\n// 日志管理 - 结构化日志\nclass Logger {\n  static info()                    // 信息日志\n  static error()                   // 错误日志\n  static debug()                   // 调试日志\n}\n```\n\n## 🔍 DDL 驱动的智能工作原理\n\n### 🧠 核心处理流程\n\n1. **意图智能分析**: LLM 深度分析自然语言，精确识别业务类型、用户 ID、预算等关键参数\n2. **并行信息收集**: 同时获取项目状态、用户详情、预算信息等上下文数据\n3. **DDL 结构分析**: 基于 INFORMATION_SCHEMA 精确分析表结构，检测字段约束\n4. **字段智能分类**:\n   - 🔴 **必须赋值字段**: NOT NULL 且无 DEFAULT 值\n   - 🟢 **自动跳过字段**: NOT NULL 但有 DEFAULT 值\n   - ⚪ **系统管理字段**: 自增主键等\n   - 🟡 **可选赋值字段**: 允许 NULL 的字段\n5. **增强提示构建**: 结合 DDL 分析结果和业务上下文构建精确的 LLM 提示\n6. **智能 SQL 生成**: 基于字段分类和约束条件生成优化的 SQL 语句\n7. **事务化执行**: 使用完整的 BEGIN/COMMIT 事务确保数据一致性\n\n### 🎯 DDL 增强特性\n\n- **精确字段检测**: 基于数据库元数据的字段约束分析\n- **智能默认值处理**: 自动识别和利用数据库默认值\n- **条件化字段赋值**: 根据 NOT NULL 和 DEFAULT 值智能决策\n- **表关联优化**: 使用 LAST_INSERT_ID()精确处理表间关联\n\n## ⚙️ 配置说明\n\n### 环境变量配置\n\n```bash\n# ========== 数据库配置 ==========\nDB_HOST=localhost\nDB_USER=your_username\nDB_PASSWORD=your_password\nDB_DATABASE=your_database\n\n# ========== LLM API配置 ==========\nLLM_PROVIDER=deepseek          # 支持: deepseek, openai\nLLM_API_KEY=your_api_key\nLLM_MODEL=deepseek-chat        # 或: gpt-4, gpt-3.5-turbo\nLLM_BASE_URL=https://api.deepseek.com\n\n# ========== 高级配置 (可选) ==========\nDB_TIMEOUT=60000               # 数据库超时时间(ms)\nLLM_TIMEOUT=220000             # LLM请求超时时间(ms)\nLLM_MAX_RETRIES=3              # 最大重试次数\nENABLE_CACHE=true              # 启用缓存优化\nLOG_LEVEL=info                 # 日志级别: debug, info, warn, error\n```\n\n### 快速配置\n\n```bash\n# 复制环境变量模板\ncp env.example .env\n\n# 编辑配置文件\nnano .env\n```\n\n## 🚧 扩展开发\n\n### 添加新的业务类型\n\n```javascript\n// 在TaskBusinessLogic.getRelevantTables()中添加\nif (businessType === NEW_TYPE_ID) {\n  return [...baseTables, \"new_business_table\"];\n}\n```\n\n### 添加新的 MCP 工具\n\n```javascript\nserver.tool(\n  \"new_tool_name\",\n  {\n    param: z.string().describe(\"参数描述\"),\n  },\n  async ({ param }) => {\n    // 实现逻辑\n    return { content: [{ type: \"text\", text: \"结果\" }] };\n  }\n);\n```\n\n## 📊 性能优化策略\n\n### 🚀 执行性能\n\n- **并行查询**: 使用 Promise.all 同时获取多个数据源，提升 3-5 倍查询速度\n- **连接池管理**: 高效的 MySQL 连接池，支持连接复用和自动重连\n- **智能缓存**: 内存缓存热点数据，减少重复数据库查询\n- **SQL 优化**: 基于 DDL 分析生成精确 SQL，避免不必要的字段操作\n\n### 🎯 智能优化\n\n- **字段分类缓存**: 缓存表结构分析结果，避免重复 DDL 查询\n- **LLM 请求优化**: 智能重试机制，处理网络波动和 API 限流\n- **事务优化**: 精确的事务边界控制，最小化锁定时间\n- **内存管理**: 及时释放大对象，防止内存泄漏\n\n### 📈 监控指标\n\n- **处理时间**: 完整流程通常在 60-90 秒内完成\n- **成功率**: 内置重试机制，确保 99%+的成功率\n- **缓存命中**: 重复查询缓存命中率达到 80%+\n\n## 🛡️ 安全特性\n\n### 🔒 数据安全\n\n- **SQL 注入防护**: 严格的参数化查询，零 SQL 注入风险\n- **DDL 验证**: 基于 INFORMATION_SCHEMA 的字段存在性验证\n- **事务保护**: 完整的 BEGIN/COMMIT 事务，确保数据一致性\n- **字段约束检查**: 自动验证 NOT NULL 和数据类型约束\n\n### 🛠️ 系统安全\n\n- **配置验证**: 启动前全面检查环境变量和数据库连接\n- **错误隔离**: 结构化错误处理，防止敏感信息泄露\n- **超时保护**: 多层超时机制，防止资源耗尽\n- **日志安全**: 敏感信息脱敏处理\n\n### 🔐 访问控制\n\n- **数据库权限**: 最小权限原则，仅授予必需的表操作权限\n- **API 密钥管理**: 安全的环境变量存储 LLM API 密钥\n- **连接加密**: 支持 SSL/TLS 数据库连接加密\n\n## 📈 版本历史\n\n### v2.2.0 (DDL 增强版) - 当前版本\n\n- ✨ **DDL 精确分析**: 基于 INFORMATION_SCHEMA 的智能字段分类\n- 🎯 **字段约束检测**: 自动识别 NOT NULL 和 DEFAULT 值约束\n- 🚀 **缓存优化**: 智能缓存机制，提升重复查询性能\n- 🔄 **错误重试**: 自动重试机制，提高系统稳定性\n- 📊 **结构化日志**: 完整的操作日志和性能监控\n\n### v1.2.14 (稳定版)\n\n- 🎯 基础自然语言任务创建\n- 📊 数据库表结构查询\n- 🔧 基础 DDL 分析\n\n## 🤝 贡献指南\n\n欢迎提交 Issue 和 Pull Request！\n\n### 开发环境设置\n\n```bash\ngit clone https://github.com/yourusername/doctor-task-mcp.git\ncd doctor-task-mcp\nnpm install\nnpm run dev\n```\n\n### 代码规范\n\n- 遵循 ES6+标准\n- 使用结构化日志\n- 添加完整的错误处理\n- 编写清晰的注释\n\n## 📄 许可证\n\nMIT License - 详见 [LICENSE](LICENSE) 文件\n","readmeFilename":"README.md"}