TOON 格式

{
  "products": [
    { "id": 1, "name": "Laptop", "price": 999 },
    { "id": 2, "name": "Mouse", "price": 29 },
    { "id": 3, "name": "Keyboard", "price": 79 }
  ]
}

products[3]{id,name,price}:
  1,Laptop,999
  2,Mouse,29
  3,Keyboard,79

import { encode, decode } from '@toon-format/toon'

// 您的扁平数据（TOON 理想选择）
const data = {
  products: [
    { id: 1, name: 'Laptop', price: 999 },
    { id: 2, name: 'Mouse', price: 29 },
    { id: 3, name: 'Keyboard', price: 79 }
  ]
}

// 编码为 TOON 用于 LLM 输入
const toonData = encode(data)
console.log(toonData)
// 输出：
// products[3]{id,name,price}:
//   1,Laptop,999
//   2,Mouse,29
//   3,Keyboard,79

// 解码回 JSON（无损往返）
const jsonData = decode(toonData)

# 将 JSON 转换为 TOON
npx @toon-format/cli input.json -o output.toon

# 将 TOON 转换回 JSON
npx @toon-format/cli input.toon -o output.json

import { Client } from '@modelcontextprotocol/sdk/client/index.js'
import { SSEClientTransport } from '@modelcontextprotocol/sdk/client/sse.js'
import { encode } from '@toon-format/toon'

// 使用 Bright Data 初始化 MCP 客户端（电商组用于 Amazon 工具）
const transport = new SSEClientTransport(
  new URL('https://mcp.brightdata.com/sse?token=YOUR_API_TOKEN&groups=ecommerce')
)

const client = new Client({
  name: 'toon-example-client',
  version: '1.0.0'
})

await client.connect(transport)

// 使用 MCP 获取 Amazon 产品数据（超时用于缓慢响应）
const result = await client.callTool(
  {
    name: 'web_data_amazon_product',
    arguments: {
      url: 'https://www.amazon.com/dp/B0EXAMPLE123'
    }
  },
  undefined,
  { timeout: 120000 } // 2 分钟超时
)

// MCP 响应是包含嵌套产品数据的数组
const mcpResponse = JSON.parse(result.content[0].text)
console.log('Raw MCP Response:', JSON.stringify(mcpResponse, null, 2))
// [
//   {
//     "title": "Ceramic Vase Set of 3...",
//     "final_price": 29.99,
//     "initial_price": 29.99,
//     "currency": "USD",
//     "rating": 4.5,
//     "reviews_count": 1250,
//     "seller_name": "HomeDecorStore",
//     "brand": "Lyeec",
//     "is_available": true,
//     "asin": "B0G13HFJNB",
//     ...
//   }
// ]

// 展平嵌套数据以进行 TOON 优化
// 将实际的 MCP 字段名称映射到扁平结构
function flattenProduct(product: any) {
  return {
    title: product.title,
    price: product.final_price,
    original_price: product.initial_price,
    currency: product.currency,
    rating: product.rating,
    reviews: product.reviews_count,
    seller: product.seller_name,
    brand: product.brand,
    in_stock: product.is_available
  }
}

// 响应是一个数组 - 展平所有产品
const flatProducts = mcpResponse.map(flattenProduct)

// 编码为 TOON - 现在它很高效！
const toonOutput = encode({ products: flatProducts })
console.log('TOON Output:', toonOutput)
// products[1]{title,price,original_price,currency,rating,reviews,seller,brand,in_stock}:
//   Ceramic Vase Set of 3...,29.99,29.99,USD,4.5,1250,HomeDecorStore,Lyeec,true

// 在您的 LLM 提示中使用 TOON 编码的数据
const prompt = `Analyze this product data and suggest pricing strategy:\n\n${toonOutput}`

import { Client } from '@modelcontextprotocol/sdk/client/index.js'
import { SSEClientTransport } from '@modelcontextprotocol/sdk/client/sse.js'
import { encode } from '@toon-format/toon'

const transport = new SSEClientTransport(
  new URL('https://mcp.brightdata.com/sse?token=YOUR_API_TOKEN&groups=ecommerce')
)

const client = new Client({ name: 'batch-example', version: '1.0.0' })
await client.connect(transport)

// 获取多个产品
const productUrls = [
  'https://www.amazon.com/dp/B0EXAMPLE1',
  'https://www.amazon.com/dp/B0EXAMPLE2',
  'https://www.amazon.com/dp/B0EXAMPLE3'
]

const results = await Promise.all(
  productUrls.map(async (url) => {
    const result = await client.callTool(
      { name: 'web_data_amazon_product', arguments: { url } },
      undefined,
      { timeout: 120000 }
    )
    // MCP 返回一个数组，获取第一个项目
    return JSON.parse(result.content[0].text)[0]
  })
)

// 使用实际的 MCP 字段名称展平所有产品用于 TOON
const flattenedProducts = results.map(p => ({
  title: p.title,
  price: p.final_price,
  currency: p.currency,
  rating: p.rating,
  reviews: p.reviews_count,
  seller: p.seller_name,
  brand: p.brand,
  in_stock: p.is_available
}))

// 转换为 TOON - 具有多个项目的大规模令牌节省！
const toonData = encode({ products: flattenedProducts })
console.log(toonData)
// products[3]{title,price,currency,rating,reviews,seller,brand,in_stock}:
//   Wireless Mouse,29.99,USD,4.5,1250,TechGear,Logitech,true
//   Gaming Keyboard,89.99,USD,4.7,890,KeyMaster,Razer,true
//   USB Hub,19.99,USD,4.2,2100,PortPlus,Anker,false

// 3 个产品的令牌比较：
// - JSON：~180 个令牌
// - TOON：~65 个令牌（64% 节省！）

import { encode } from '@toon-format/toon'

// 用于常见 MCP 数据结构的通用展平器
// 这些映射 Bright Data MCP 返回的实际字段名称
const flatteners = {
  amazon_product: (p: any) => ({
    title: p.title,
    price: p.final_price,
    original_price: p.initial_price,
    currency: p.currency,
    rating: p.rating,
    reviews: p.reviews_count,
    seller: p.seller_name,
    brand: p.brand,
    in_stock: p.is_available
  }),

  linkedin_profile: (p: any) => ({
    name: p.full_name,
    headline: p.headline,
    location: p.city,
    country: p.country,
    connections: p.connections_count,
    followers: p.followers_count,
    company: p.current_company_name,
    position: p.position
  }),

  instagram_post: (p: any) => ({
    caption: p.description?.substring(0, 100),
    likes: p.likes,
    comments: p.comments,
    posted: p.upload_date,
    author: p.channel
  })
}

// 辅助函数处理 MCP 响应并转换为 TOON
function mcpToToon<T>(
  data: T | T[],
  flattener: (item: T) => Record<string, any>,
  key: string = 'items'
): string {
  const items = Array.isArray(data) ? data : [data]
  const flattened = items.map(flattener)
  return encode({ [key]: flattened })
}

// 使用示例
const result = await client.callTool(
  { name: 'web_data_amazon_product', arguments: { url: '...' } },
  undefined,
  { timeout: 120000 }
)
const mcpData = JSON.parse(result.content[0].text)
const toonOutput = mcpToToon(mcpData, flatteners.amazon_product, 'products')