datalab_shopping_category
Analyze Naver Shopping category trends by specifying time units, date ranges, and category codes to identify market patterns and consumer behavior.
Instructions
Perform a trend analysis on Naver Shopping category. (네이버 쇼핑 카테고리별 트렌드 분석)
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| category | Yes | Array of category name and code pairs | |
| endDate | Yes | End date (yyyy-mm-dd) | |
| startDate | Yes | Start date (yyyy-mm-dd) | |
| timeUnit | Yes | Time unit |
Implementation Reference
- src/handlers/datalab.handlers.ts:76-78 (handler)Handler function that executes the core logic by delegating to the Naver client for shopping category trend analysis.
export async function handleShoppingCategoryTrend(params: DatalabShopping) { return client.datalabShoppingCategory(params); } - src/schemas/datalab.schemas.ts:22-32 (schema)Zod schema defining the input parameters for the datalab_shopping_category tool, including category details.
// 쇼핑 카테고리 스키마 export const DatalabShoppingSchema = DatalabBaseSchema.extend({ category: z .array( z.object({ name: z.string().describe("Category name"), param: z.array(z.string()).describe("Category codes"), }) ) .describe("Array of category name and code pairs"), }); - src/index.ts:283-296 (registration)MCP server tool registration for datalab_shopping_category, including description and input schema reference.
server.registerTool( "datalab_shopping_category", { description: "🛍️ STEP 2: Analyze shopping category trends over time. Use find_category first to get category codes. BUSINESS CASES: Market size analysis, seasonal trend identification, category performance comparison. EXAMPLE: Compare '패션의류' vs '화장품' trends over 6 months. For current period analysis, use get_current_korean_time to set proper date ranges. (네이버 쇼핑 카테고리별 트렌드 분석 - 먼저 find_category 도구로 카테고리 코드를 찾고, 현재 기간 분석시 get_current_korean_time으로 적절한 날짜 범위 설정)", inputSchema: DatalabShoppingSchema.shape, }, async (args) => { const result = await datalabToolHandlers.datalab_shopping_category(args); return { content: [{ type: "text", text: JSON.stringify(result, null, 2) }], }; } ); - Client method that performs the actual HTTP POST request to Naver DataLab API for shopping categories.
async datalabShoppingCategory( params: DatalabShoppingCategoryRequest ): Promise<DatalabShoppingResponse> { return this.post(`${this.datalabBaseUrl}/shopping/categories`, params); - src/handlers/datalab.handlers.ts:28-30 (handler)Handler map entry that logs args and delegates to the specific trend handler.
datalab_shopping_category: (args) => { console.error("datalab_shopping_category called with args:", JSON.stringify(args, null, 2)); return handleShoppingCategoryTrend(args);