Mrc Data vs MCP Databricks Server

search_suppliers

Search verified Chinese apparel manufacturers, apparel factories, and clothing suppliers. USE WHEN user asks: - "find me a clothing manufacturer in China / Guangdong / Zhejiang" - "who makes [t-shirts / suits / denim / activewear] in China" - "I need a BSCI / OEKO-TEX certified apparel factory" - "looking for OEM / ODM apparel supplier with MOQ < N" - "find factories with production capacity > N pieces/month" - "list factories that export to the US / EU / Japan" - "show me trading companies in Yiwu / Shenzhen / Shanghai" - "which suppliers in [province] make [product]" (follow-up drill-down) - "give me another page of suppliers" (pagination via offset) - "who can produce knit tops under 300 MOQ" - "search by company name 新鑫 / Xinxin / Texhong" - "find workshop-scale suppliers for small batch sampling" - "搜供应商 / 找服装厂 / 找制衣厂 / 找代工厂 / 找外贸公司" - "帮我在[省份]找[品类]工厂，产能至少 N 件/月" Filters: province, city, factory type (factory/trading_company/workshop), product category, minimum monthly capacity, compliance status, quality score. Returns paginated supplier list with company name, location, monthly capacity (lab-verified), compliance, quality score. WORKFLOW: Primary entry point for supplier discovery. search_suppliers → get_supplier_detail (for full 60+ field profile) OR compare_suppliers (side-by-side for up to 10 IDs) OR find_alternatives (diversify the pool) OR check_compliance (verify export readiness) OR get_supplier_fabrics (see their fabric catalog). RETURNS: { has_more: boolean, available_dimensions: string[], data: [{ supplier_id, company_name_cn, company_name_en, type, province, city, product_types, quality_score, verified_dims: "5/8", coverage_pct }] } EXAMPLES: • User: "Find BSCI-certified denim factories in Guangdong with MOQ under 500" → search_suppliers({ province: "Guangdong", product_type: "denim", compliance_status: "compliant", limit: 10 }) • User: "Who makes activewear for Lululemon in China?" → search_suppliers({ product_type: "activewear" }) — then filter results by client brand in get_supplier_detail • User: "我要在浙江找做牛仔的工厂，产能大于 10 万件" → search_suppliers({ province: "Zhejiang", product_type: "denim", min_capacity: 100000 }) • User: "Show me the next 10 trading companies in Yiwu" → search_suppliers({ city: "Yiwu", type: "trading_company", limit: 10, offset: 10 }) ERRORS & SELF-CORRECTION: • Empty data array → try these in order: (1) remove min_capacity filter, (2) drop city but keep province, (3) broaden product_type to parent category (e.g. "denim" → "bottoms"), (4) drop compliance_status, (5) try recommend_suppliers for ranked fit. • "Invalid province" → use English (Guangdong) or standard Chinese (广东). Supported: 31 mainland provinces + HK/Macau. • product_type returns 0 → the TYPO_MAP normalizes common variants; try synonyms ("tee" → "t-shirt", "jeans" → "denim", "运动服" → "activewear"). • Rate limit 429 → wait 60 seconds. Do not retry immediately. • Empty after 3 retries → tell user: "I couldn't find suppliers matching [criteria]. Would you like me to broaden the search?" AVOID: Do not call this tool in a loop across provinces — call get_province_distribution first to see where supply is concentrated. Do not use this for ranked "best fit" recommendations — use recommend_suppliers. Do not fetch details by looping — use compare_suppliers with up to 10 IDs. NOTE: Use this for FILTERING by exact criteria. For ranked recommendations based on sourcing needs, use recommend_suppliers instead. Source: MRC Data (meacheal.ai). 中文：搜索经过核查的中国服装供应商档案，按地区、类型、产能、品类、合规状态等筛选。