Naver Search MCP Server

import { z } from "zod"; // 기본 DataLab 스키마 export const DatalabBaseSchema = z.object({ startDate: z.string().describe("Start date (yyyy-mm-dd)"), endDate: z.string().describe("End date (yyyy-mm-dd)"), timeUnit: z.enum(["date", "week", "month"]).describe("Time unit"), }); // 검색어 트렌드 스키마 export const DatalabSearchSchema = DatalabBaseSchema.extend({ keywordGroups: z .array( z.object({ groupName: z.string().describe("Group name"), keywords: z.array(z.string()).describe("List of keywords"), }) ) .describe("Keyword groups"), }); // 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"), }); // 기기별 트렌드 스키마 export const DatalabShoppingDeviceSchema = DatalabBaseSchema.extend({ category: z.string().describe("Category code"), device: z.enum(["pc", "mo"]).describe("Device type"), }); // 성별 트렌드 스키마 export const DatalabShoppingGenderSchema = DatalabBaseSchema.extend({ category: z.string().describe("Category code"), gender: z.enum(["f", "m"]).describe("Gender"), }); // 연령별 트렌드 스키마 export const DatalabShoppingAgeSchema = DatalabBaseSchema.extend({ category: z.string().describe("Category code"), ages: z .array(z.enum(["10", "20", "30", "40", "50", "60"])) .describe("Age groups"), }); // 키워드 트렌드 스키마 export const DatalabShoppingKeywordsSchema = DatalabBaseSchema.extend({ category: z.string().describe("Category code"), keyword: z .array( z.object({ name: z.string().describe("Keyword name"), param: z.array(z.string()).describe("Keyword values"), }) ) .describe("Array of keyword name and value pairs"), }); // 키워드 기기별 트렌드 스키마 export const DatalabShoppingKeywordDeviceSchema = DatalabBaseSchema.extend({ category: z.string().describe("Category code"), keyword: z.string().describe("Search keyword"), device: z.enum(["pc", "mo"]).describe("Device type"), }); // 키워드 성별 트렌드 스키마 export const DatalabShoppingKeywordGenderSchema = DatalabBaseSchema.extend({ category: z.string().describe("Category code"), keyword: z.string().describe("Search keyword"), gender: z.enum(["f", "m"]).describe("Gender"), }); // 키워드 연령별 트렌드 스키마 export const DatalabShoppingKeywordAgeSchema = DatalabBaseSchema.extend({ category: z.string().describe("Category code"), keyword: z.string().describe("Search keyword"), ages: z .array(z.enum(["10", "20", "30", "40", "50", "60"])) .describe("Age groups"), }); // 카테고리 디바이스/성별/연령별 트렌드 스키마 export const DatalabShoppingCategoryDeviceSchema = 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"), device: z.enum(["pc", "mo"]).optional().describe("Device type"), gender: z.enum(["f", "m"]).optional().describe("Gender"), ages: z .array(z.enum(["10", "20", "30", "40", "50", "60"])) .optional() .describe("Age groups"), }); // 키워드 디바이스/성별/연령별 트렌드 스키마 export const DatalabShoppingKeywordTrendSchema = DatalabBaseSchema.extend({ category: z.string().describe("Category code"), keyword: z .array( z.object({ name: z.string().describe("Keyword name"), param: z.array(z.string()).describe("Keyword values"), }) ) .describe("Array of keyword name and value pairs"), device: z.enum(["pc", "mo"]).optional().describe("Device type"), gender: z.enum(["f", "m"]).optional().describe("Gender"), ages: z .array(z.enum(["10", "20", "30", "40", "50", "60"])) .optional() .describe("Age groups"), }); export type DatalabSearch = z.infer<typeof DatalabSearchSchema>; export type DatalabShopping = z.infer<typeof DatalabShoppingSchema>; export type DatalabShoppingDevice = z.infer<typeof DatalabShoppingDeviceSchema>; export type DatalabShoppingGender = z.infer<typeof DatalabShoppingGenderSchema>; export type DatalabShoppingAge = z.infer<typeof DatalabShoppingAgeSchema>; export type DatalabShoppingKeywords = z.infer<typeof DatalabShoppingKeywordsSchema>; export type DatalabShoppingKeywordDevice = z.infer<typeof DatalabShoppingKeywordDeviceSchema>; export type DatalabShoppingKeywordGender = z.infer<typeof DatalabShoppingKeywordGenderSchema>; export type DatalabShoppingKeywordAge = z.infer<typeof DatalabShoppingKeywordAgeSchema>;