Yudao Pilot MCP

中文 | English

中文

Yudao Pilot MCP 是面向 yudao / ruoyi-vue-pro 生态的工作区感知型 MCP 服务。它帮助 AI 编码工具识别本地后端、前端、数据库和代码生成目标，让 AI 生成的代码准确落到正确项目结构里。

严肃声明

yudao、ruoyi-vue-pro 生态与 ruoyi / RuoYi / 若依原生生态不是同一个项目。当前 MCP 只支持 yudao、ruoyi-vue-pro、ruoyi-vue-pro-jdk17、yudao-cloud 相关项目，不支持若依原生生态项目。

核心价值

• 让 AI 不再猜 yudao 项目目录和生成位置

• 用 .yudao-pilot/config.yaml 固化后端、前端和数据库配置

• 基于项目指纹校验路径，避免代码写错仓库或模块

• 生成菜单、字典、H2 测试 SQL 和前后端骨架代码

• 当工作目录不明确时停止初始化，并要求 AI 先询问真实项目目录

快速使用

1. 安装命令行入口。

git clone https://github.com/woodynew/yudao-pilot-mcp.git
cd yudao-pilot-mcp
uv tool install .

2. 在 MCP 客户端中注册服务。

{
  "mcpServers": {
    "yudao-pilot": {
      "command": "yudao-pilot",
      "args": []
    }
  }
}

3. 在你的 yudao 工作区中让 AI 先调用 load_workspace_config。首次使用会生成 .yudao-pilot/config.yaml，并要求确认识别到的后端和前端路径。

4. 确认配置后，典型流程是：

load_workspace_config
validate_workspace_projects
inspect_codegen_context
generate_codegen_scaffold(write_files=true)

如果用户明确要求“先预览”，则调用：

generate_codegen_scaffold(write_files=false)

此时预览产物会写入 .yudao-pilot/previews/ 下的临时目录，不会影响项目现有代码。

文档

• 项目概览

• 配置指南

• MCP 工具与工作流

• SQL、菜单与字典生成

• 开发与测试

• 前端产物矩阵

• 产品说明

• 路线图

Related MCP server: Builder-Proj-MCP Server

English

Yudao Pilot MCP is a workspace-aware MCP server for the yudao / ruoyi-vue-pro ecosystem. It helps AI coding tools understand local backend projects, frontend targets, database configuration, and code-generation routes so generated code lands in the right place.

Important Notice

The yudao / ruoyi-vue-pro ecosystem is not the same project as the original ruoyi / RuoYi ecosystem. This MCP currently supports yudao, ruoyi-vue-pro, ruoyi-vue-pro-jdk17, and yudao-cloud projects only. It does not support original RuoYi projects.

Core Value

• Stop AI tools from guessing yudao project paths

• Use .yudao-pilot/config.yaml as the routing source of truth

• Validate backend and frontend paths with project fingerprints

• Generate menu SQL, dictionary SQL, H2 test SQL, and backend/frontend scaffolds

• Refuse unsafe initialization when the project workspace is unknown

Quick Start

1. Install the command.

git clone https://github.com/woodynew/yudao-pilot-mcp.git
cd yudao-pilot-mcp
uv tool install .

2. Register the MCP server in your client.

{
  "mcpServers": {
    "yudao-pilot": {
      "command": "yudao-pilot",
      "args": []
    }
  }
}

3. Ask the AI client to call load_workspace_config from your yudao workspace. On first use, Yudao Pilot creates .yudao-pilot/config.yaml and asks the AI to confirm detected backend and frontend paths.

4. After configuration is confirmed, the common flow is:

load_workspace_config
validate_workspace_projects
inspect_codegen_context
generate_codegen_scaffold(write_files=true)

If the user explicitly asks to preview first, call:

generate_codegen_scaffold(write_files=false)

Preview artifacts are written under .yudao-pilot/previews/ and do not touch the existing project code.

Documentation

• Overview

• Configuration

• MCP Tools and Workflow

• SQL, Menu, and Dictionary Generation

• Development and Testing

• Frontend Output Matrix

• Product Notes

• Roadmap