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Integration Development Introduction

On the Lovrabet platform, you can use AI to quickly generate complete business systems. But we know well that AI is not omnipotent.

💡 AI + Human: A Collaborative Model of Complementary Strengths

AI's Capabilities and Boundaries

What Lovrabet's AI can do for you:

✅ Launch complete business systems in days - CRM, ERP, order management systems that traditionally take 2-3 months can be generated by AI in 3-5 days
✅ Significantly reduce development costs - Save 60-80% of development time and labor costs, allowing technical teams to focus on core innovation
✅ Rapidly respond to business needs - Fast market changes? Frequent business adjustments? AI increases system iteration speed by 10x
✅ Usable with zero coding background - Business personnel describe requirements in natural language, AI automatically generates usable systems
✅ Enterprise-grade standard architecture - Auto-generated code follows best practices, secure, stable, and easy to maintain

However, AI currently cannot fully replace human value in the following aspects:

🧠 Deep industry experience - Risk control models, diagnostic processes, supply chain optimization algorithms accumulated over 10 years; AI struggles to understand this business wisdom
🎯 Unique enterprise competitiveness - Your enterprise's unique business rules, organizational culture, decision mechanisms are differentiating advantages
🔧 Ultimate user experience - Carefully crafted interaction design and innovative functional experiences require human creativity and insight
🌐 Ecosystem integration - Deep integration with existing systems like WeChat Work, DingTalk, SAP, Yonyou requires understanding the enterprise IT landscape
🚀 Innovation breakthroughs - Disruptive business models, cutting-edge technology applications, industry-first features are uniquely human values

Integration Development: Best Practice for Human-Machine Collaboration

Our design philosophy: Lovrabet is not meant to replace human developers, but to become your capable assistant.

Core Value:

🚀 Speed up - AI handles 80% of standard features, you focus on the 20% core value
🔗 Seamless integration - Extended features integrate perfectly with AI-generated systems
🎯 Professional advantage - Your domain expertise and innovative capabilities are fully utilized
🛠️ Complete toolchain - SDK, CLI, MCP make integration development simple and efficient

🎯 Typical Integration Development Scenarios

Scenario 1: Industry-Specific Algorithms and Models

Background: I'm a risk control expert at a fintech company, needing to integrate our proprietary credit scoring model. This model is based on 10 years of data accumulation and industry experience, containing 200+ risk features and complex scoring logic.

AI's Limitation: AI cannot understand finance industry-specific risk models, regulatory requirements, and business rules.

Integration Development Solution:

Use Lovrabet AI to generate standard features like customer management and loan applications
Integrate proprietary credit scoring engine through integration development
Use SDK to get customer data, call scoring API, write results back to system
Sync to main system with one click, risk control personnel can use directly

Scenario 2: Complex Multi-System Integration

Background: The enterprise has multiple internal systems including ERP (Yonyou), CRM (Salesforce), WeChat Work, etc., needing to connect data and processes.

AI's Limitation: Each enterprise's system integration solution is different, requiring deep understanding of enterprise IT architecture and business processes.

Integration Development Solution:

Lovrabet AI generates unified data dashboards and operation interfaces
Implement API integration with each system through integration development
Integrate multi-source data in extended pages, providing unified views
Implement cross-system business process automation

Scenario 3: Innovative Interactive Experiences

Background: I want to create a drag-and-drop project board (like Trello) or a visualized supply chain network graph, requiring special UI components and interaction logic.

AI's Limitation: AI excels at generating standard tables and forms, but for highly customized interactive experiences, human design thinking and creativity are needed.

Integration Development Solution:

Lovrabet AI handles underlying data storage and permission control
Introduce professional UI libraries like react-dnd, G6 through integration development
Freely design interaction logic and visual effects
Seamlessly integrate with Lovrabet data using SDK

Scenario 4: Special Business Rules and Processes

Background: Our company's order approval process is very complex: automatically assign approvers based on order amount, customer level, product type; trigger inventory deduction, financial accounting, shipping notifications, etc. after approval.

AI's Limitation: Each enterprise's business rules are unique, AI struggles to understand these business logics formed over years.

Integration Development Solution:

Lovrabet AI generates basic order management features
Implement complex approval engine and automation processes through integration development
Use SDK to operate multiple data tables, coordinating various steps
Keep business logic code independent for easy maintenance and iteration

Scenario 5: Cutting-Edge Technology Applications

Background: I want to integrate AI customer service bots, voice recognition, image recognition, blockchain evidence storage, and other cutting-edge technologies into the system.

AI's Limitation: Lovrabet AI focuses on generating standard business systems; cutting-edge technologies require deep development by professional teams.

Integration Development Solution:

Lovrabet AI generates basic business management features
Integrate OpenAI, Alibaba Cloud, Tencent Cloud services through integration development
Implement innovative features in extended pages
Form differentiated competitive advantages

🛠️ Complete Integration Development Toolchain

To make integration development simpler and more efficient, we've built a complete toolchain based on years of experience:

1️⃣ Lovrabet SDK - Data Access Layer

Problems it solves:

❌ Without SDK: Need to study API documentation yourself, write request code manually, handle authentication, errors, etc.
❌ No type hints: Easy to pass wrong parameters, only discover errors at runtime
❌ Complex authentication: Need to handle Token generation, expiration refresh, etc. yourself

With SDK:

// ✅ Concise and elegant, type-safe
const customers = await client.models.customers.filter({
  currentPage: 1,
  pageSize: 20,
});

// ✅ Create data, IDE auto-suggests fields
const newCustomer = await client.models.customers.create({
  name: "Zhang San",
  phone: "13800138000",
  company: "ABC Tech",
});

Core Features:

🔐 Multiple authentication modes - Auto-adapts to server (AccessKey) and browser (Token/Cookie) environments
📦 Complete type definitions - TypeScript native support, auto-suggests fields and types during development
⚡ Environment adaptive - Same code runs in both Node.js and browser
🎯 Concise API - Intuitive CRUD operations, low learning curve

📖 Detailed Documentation: Lovrabet SDK Usage Guide

2️⃣ Lovrabet CLI - Scaffolding and Sync Tool

Problems it solves:

❌ Without CLI: Build project from scratch, configure routing, build tools, time-consuming and laborious
❌ Manual menu configuration: After developing pages, need to manually add menus in platform backend, easy to miss
❌ Integration difficulties: Unclear how to integrate locally developed pages into main system

With CLI:

# ✅ One-click project creation, auto-generates standard structure
lovrabet create my-app

# ✅ Auto-generate API configuration, no manual writing
lovrabet api pull --appcode your-app-code

# ✅ One-click menu sync, instantly complete main-sub app merge
lovrabet menu sync

Core Features:

🚀 Project scaffolding - Best practice-based project template, ready to use
🔄 API auto-generation - Scan app datasets, auto-generate SDK config files
📋 Smart menu sync - Scan local pages, auto-sync to platform menu (supports Chinese naming)
⚡ Development server - Built-in hot reload, boosts development efficiency
🏗️ Smart build - Optimized micro-frontend build configuration, one-click deployment

Key Highlight - One-Click Menu Sync:

lovrabet menu sync

Auto-scans all pages in src/pages directory
Intelligently extracts menu names (supports Title comments, displayName, component names)
Compares local and platform menus, finds missing items
Batch creates menus, instantly completes main-sub app merge
No manual configuration, zero omissions

📖 Detailed Documentation: Lovrabet CLI Usage Guide

3️⃣ Lovrabet Dataset MCP - AI Assists Human Development 🌟

What is MCP?

MCP (Model Context Protocol) is a standard protocol launched by Anthropic, enabling AI tools (Claude, Cursor, etc.) to understand your business context.

Lovrabet Dataset MCP Server is a service we developed based on the MCP protocol, making AI your intelligent assistant for integration development.

🎯 Core Value: Let AI Understand Your Business

Development process without MCP:

Developer: I want to write code to query customer list
    ↓
AI: OK, let me help you write it (but AI doesn't know your data table structure)
    ↓
AI generates code:
    const data = await fetch('/api/users')  // ❌ Wrong API endpoint
    const { name, email } = data[0]        // ❌ Wrong field names
    ↓
Developer: No, our table is called customers, fields are customer_name and phone
    ↓
Communicate again, modify... (repeat multiple times)

Development process with MCP:

Developer: I want to write code to query customer list
    ↓
AI (understands your business via MCP):
   - I see you have a customers table
   - Contains fields: customer_name, phone, company, create_time
   - Primary key is id
    ↓
AI auto-generates correct code:
    const customers = await client.models.customers.filter({
      currentPage: 1,
      pageSize: 20
    });
    // ✅ Completely correct, works on first try!

🚀 MCP's Powerful Capabilities

MCP can help you:

✅ Quickly generate CRUD code - Understands data structure, auto-generates relational queries
✅ Complex data queries and aggregation - AI understands business logic, generates statistical analysis code
✅ Data association and join queries - Auto-infers table relationships, generates efficient queries
✅ Batch data operations - Understands business rules, generates safe batch code
✅ Generate complete page components - Complete components including state management, pagination, search

🔧 How to Configure MCP Server

Method 1: Using npx (Recommended)

{
  "mcpServers": {
    "lovrabet-dataset": {
      "command": "npx",
      "args": ["-y", "@lovrabet/dataset-mcp-server"],
      "env": {
        "DEFAULT_APP_CODE": "your-app-code"
      }
    }
  }
}

Method 2: Global Installation

npm install -g @lovrabet/dataset-mcp-server

Configuration file:

{
  "mcpServers": {
    "lovrabet-dataset": {
      "command": "lovrabet-dataset-mcp",
      "env": {
        "DEFAULT_APP_CODE": "your-app-code"
      }
    }
  }
}

🌟 MCP's Core Advantages

Capability	Without MCP	With MCP
Understand data structure	❌ AI doesn't know your tables and fields	✅ AI fully understands your business data
Code generation accuracy	❌ Requires repeated corrections	✅ Generated once, types correct
Development efficiency	❌ Frequently check docs, write code manually	✅ Dialogue generates complete code
Complex queries	❌ Need to design data associations yourself	✅ AI auto-infers associations
Learning curve	❌ Need to familiarize with SDK API	✅ Natural language describes requirements

📖 MCP Detailed Documentation and Use Cases: @lovrabet/dataset-mcp-server

🎯 Toolchain Comparison

Development Stage	Without Toolchain	With Complete Toolchain
Create project	Build from scratch, configure routing, build tools	`lovrabet create` one-click creation
Configure API	Check docs, write request code manually	`lovrabet api pull` auto-generates
Write code	Write HTTP requests manually, error-prone	SDK provides type-safe API
AI assistance	❌ AI doesn't understand business, code unusable	✅ MCP lets AI deeply understand data structure
Complex queries	Need to check docs, write data associations manually	AI auto-generates, works on first try
Local development	Need to set up dev server yourself	`lovrabet start` hot reload dev
Integrate main system	Configure menus manually, easy to miss	`lovrabet menu sync` one-click sync
Maintenance cost	Code scattered, hard to maintain	Independent repo, clear structure

📚 Next Steps

🚀 Development Best Practices - Learn complete development process and best practices
❓ FAQs - Answers to common questions in integration development
📖 Lovrabet SDK - Deep dive into SDK usage
🔧 Lovrabet CLI - Master CLI tools

🎉 Start Your Human-Machine Collaborative Development Journey

Through Lovrabet's integration development system, you can:

✅ AI handles standard features, you focus on core value
✅ Keep code independent with clear architecture
✅ Enjoy complete toolchain support (especially MCP)
✅ Achieve efficient team collaboration
✅ Human-machine collaboration, each excelling in their strengths

Ready? 👉 View Development Best Practices

💡 AI + Human: A Collaborative Model of Complementary Strengths
- AI's Capabilities and Boundaries
- Integration Development: Best Practice for Human-Machine Collaboration
🎯 Typical Integration Development Scenarios
🛠️ Complete Integration Development Toolchain
📚 Next Steps
🎉 Start Your Human-Machine Collaborative Development Journey