Startup Helper MCP

Instructions

Implementation Reference

• src/tools/commercial-area.ts:91-169 (handler)

  The core handler function `analyzeCommercialArea` that performs commercial area analysis: gets coordinates, counts categories and competitors via Kakao API, computes metrics like saturation score, area type, characteristics, and recommendation.
  export async function analyzeCommercialArea( location: string, businessType: string, radius: number = 500 ): Promise<ApiResult<CommercialAreaData>> { try { // 1. 위치 좌표 얻기 const coords = await kakaoApi.getCoordinates(location); if (!coords) { return { success: false, error: { code: "LOCATION_NOT_FOUND", message: `입력하신 위치를 찾을 수 없습니다: ${location}`, suggestion: "강남역, 홍대입구 등 구체적인 지명을 입력해주세요.", }, }; } // 2. 업종별 업체 수 조회 const categoryBreakdown = await kakaoApi.countByCategories( String(coords.lng), String(coords.lat), radius ); // 3. 해당 업종 업체 검색 const competitors = await kakaoApi.findCompetitors( businessType, location, radius, 15 ); const sameCategoryCount = competitors.length; // 4. 분석 결과 계산 const totalStores = Object.values(categoryBreakdown).reduce((a, b) => a + b, 0); const saturationScore = calculateSaturationScore(businessType, sameCategoryCount, totalStores); const areaType = estimateAreaType(categoryBreakdown); const characteristics = analyzeCharacteristics(categoryBreakdown, location); const recommendation = generateRecommendation(businessType, saturationScore, sameCategoryCount); return { success: true, data: { location: { name: location, address: location, coordinates: coords, }, areaType, characteristics, density: { totalStores, categoryBreakdown, sameCategoryCount, saturationLevel: getSaturationLevel(saturationScore), saturationScore, }, recommendation, }, meta: { source: DATA_SOURCES.kakaoLocal, timestamp: new Date().toISOString(), }, }; } catch (error) { console.error("상권 분석 실패:", error); return { success: false, error: { code: "ANALYSIS_FAILED", message: `상권 분석 중 오류가 발생했습니다: ${error instanceof Error ? error.message : "Unknown error"}`, suggestion: "잠시 후 다시 시도해주세요.", }, }; } }
• src/index.ts:24-39 (registration)

  MCP server registration of the 'analyze_commercial_area' tool, including description, Zod input schema, and wrapper handler that calls the core function and formats response.
  server.tool( "analyze_commercial_area", "특정 위치의 상권을 분석합니다. 업종별 밀집도, 포화도, 상권 특성을 제공합니다. 카카오맵 데이터를 기반으로 합니다.", { location: z.string().describe("분석할 위치 (예: 강남역, 홍대입구, 부산 서면)"), business_type: z.string().describe("창업 예정 업종 (예: 카페, 음식점, 편의점, 미용실)"), radius: z.number().optional().default(500).describe("분석 반경 (m), 기본값: 500"), }, async ({ location, business_type, radius }) => { const result = await analyzeCommercialArea(location, business_type, radius); return { content: [{ type: "text", text: JSON.stringify(result, null, 2) }], isError: !result.success, }; } );
• src/types.ts:33-45 (schema)

  TypeScript interface defining the structured output data for the commercial area analysis tool.
  export interface CommercialAreaData { location: Location; areaType: string; characteristics: string[]; density: { totalStores: number; categoryBreakdown: Record<string, number>; sameCategoryCount: number; saturationLevel: string; saturationScore: number; }; recommendation: string; }
• src/tools/commercial-area.ts:71-89 (helper)

  Helper function to compute saturation score based on business type and competitor count relative to predefined optimal densities.
  function calculateSaturationScore( businessType: string, sameCategoryCount: number, _totalStores: number ): number { // 업종별 적정 개수 기준 (반경 500m 기준) const optimalCounts: Record<string, number> = { 카페: 10, 음식점: 20, 편의점: 5, 미용실: 8, default: 10, }; const optimal = optimalCounts[businessType] || optimalCounts.default; const ratio = (sameCategoryCount / optimal) * 100; return Math.min(100, Math.round(ratio)); }