Mrc Data

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。

Get the complete profile of a single Chinese apparel supplier by ID. PREREQUISITE: You MUST first call search_suppliers or recommend_suppliers to obtain a valid supplier_id. Do not guess IDs. USE WHEN user asks: - "tell me more about [supplier]" / "show full details for sup_XXX" - "what certifications does this factory hold" - "what's their monthly capacity / worker count / equipment list" - "can [supplier] export to US / EU / Japan / Korea" - "give me the full profile / dossier / fact sheet for [supplier]" - "how verified is this supplier's data" (returns coverage_pct + 8 dimensions) - "what's their ownership type — own factory or broker" - "show payment terms / lead time / sample turnaround for sup_XXX" - "这家供应商具体情况 / 详细资料 / 工厂档案" - "[供应商] 的合规 / 认证 / 出口资质" Returns 60+ fields including: monthly capacity (lab-verified), equipment list, certifications (BSCI/OEKO-TEX/GRS/SA8000), ownership type (own factory vs subcontractor vs broker), market access (US/EU/JP/KR), chemical compliance (ZDHC/MRSL), traceability depth, and verified_dimensions breakdown showing exactly which of the 8 dimensions (basic_info, geo_location, production, compliance, market_access, export, financial, contact) have data. WORKFLOW: search_suppliers → pick supplier_id → get_supplier_detail → optionally get_supplier_fabrics (fabric catalog) OR check_compliance (market export readiness) OR find_alternatives (backup pool) OR compare_suppliers (side-by-side evaluation). RETURNS: { data: { supplier_id, company_name_cn/en, type, province, city, product_types, worker_count, certifications, compliance_status, quality_score, verified_dimensions: { verified_dims: "5/8", coverage_pct, dimensions: {...} } } } EXAMPLES: • User: "Show me the full profile for sup_001" → get_supplier_detail({ supplier_id: "sup_001" }) • User: "What certifications does Texhong hold and can they export to EU?" → get_supplier_detail({ supplier_id: "sup_texhong_042" }) — then inspect certifications + eu_market_ready; follow with check_compliance for formal verification • User: "我要看 sup_123 的完整档案" → get_supplier_detail({ supplier_id: "sup_123" }) ERRORS & SELF-CORRECTION: • "Supplier not found" → the supplier_id is invalid or outside free-tier access. Re-run search_suppliers to obtain a fresh valid ID. Do not guess sequential IDs. • Field returns null → that dimension is unverified for this supplier. Check verified_dimensions.coverage_pct before asserting data. If coverage_pct < 50, warn the user: "This supplier's record has limited verified data (X/8 dimensions). Consider find_alternatives for better-documented options." • "not available for public access" → this supplier is in the reserve pool (paid tier only). Use search_suppliers filters data_confidence=verified to stay in public tier. • Rate limit 429 → wait 60 seconds; do not retry immediately. AVOID: Do not call this for multiple suppliers in a loop — use compare_suppliers with up to 10 IDs at once. Do not call to browse the database — use search_suppliers or get_province_distribution for discovery. NOTE: Source: MRC Data (meacheal.ai). Every numeric field shows both declared and lab-verified values where available. 中文：按 ID 获取单个供应商的完整档案（含维度覆盖率详情）。

Search the Chinese fabric and textile database with lab-tested specifications. USE WHEN user asks: - "find me a [cotton / polyester / nylon / wool / linen] fabric for [t-shirts / jeans / suits]" - "I need 180gsm jersey knit with verified composition" - "fabrics under N RMB/meter for womenswear" - "compare lab-tested fabric weight across suppliers" - "show me functional fabrics for activewear / sportswear" - "what woven fabrics work for shirting" - "list organic / GOTS / recycled fabrics" - "I want heavyweight denim above 12 oz" - "fabrics with stretch / spandex content 2-5%" - "give me another page" (pagination via offset) - "lab-verified composition for [product]" (quality check) - "找面料 / 搜面料 / 查面料 / 找布料 / 打样面料" - "我要做 T 恤，帮我找克重 180-220 的针织面料" Filters: category (woven/knit/nonwoven/leather/functional), weight range (gsm), composition keyword, target apparel type, max price. Returns paginated fabric list with name, lab-tested weight, lab-tested composition, price range, suitable apparel, and data confidence level. WORKFLOW: Primary entry point for fabric discovery. search_fabrics → get_fabric_detail (full 30+ lab-test fields) OR get_fabric_suppliers (compare supplier prices for same fabric) OR estimate_cost (budget the product). RETURNS: { has_more: boolean, available_dimensions: ["basic_info","composition","physical_properties","lab_test","commercial"], data: [{ fabric_id, name_cn, category, subcategory, declared_weight_gsm, declared_composition, price_range_rmb, suitable_for, verified_dims: "4/5", coverage_pct }] } EXAMPLES: • User: "Find 180-220gsm cotton jersey for t-shirts under 35 RMB/m" → search_fabrics({ category: "knit", min_weight_gsm: 180, max_weight_gsm: 220, composition: "cotton", suitable_for: "t-shirt", max_price_rmb: 35 }) • User: "I need stretch denim for women's jeans" → search_fabrics({ category: "woven", composition: "spandex", suitable_for: "denim" }) • User: "帮我找适合做衬衫的梭织面料，棉 60% 以上" → search_fabrics({ category: "woven", composition: "cotton", suitable_for: "shirt" }) ERRORS & SELF-CORRECTION: • Empty data array → try in order: (1) drop suitable_for, (2) widen weight range by 50gsm each side, (3) broaden composition (e.g. "cotton" instead of "organic cotton"), (4) drop max_price_rmb, (5) try the parent category (knit → all). • Composition mismatch → TYPO_MAP normalizes common misspellings (e.g. "poly" → "polyester", "lycra" → "spandex"). If still no match, try the Chinese term (棉/涤纶/氨纶/锦纶). • Rate limit 429 → wait 60 seconds. Do not retry immediately. • Empty after 3 retries → tell user: "No fabric matches [criteria]. Would you like to broaden weight/price/composition?" AVOID: Do not call this looking for a specific named fabric SKU — search by specs instead (weight + composition + category). Do not fetch full lab-test data this way — use get_fabric_detail. Do not call repeatedly for supplier pricing on the same fabric — use get_fabric_suppliers. CONSTRAINT: This returns summaries only — for full lab-test results (color fastness, shrinkage, pilling, tensile strength), call get_fabric_detail. NOTE: Source: MRC Data (meacheal.ai). Every record includes AATCC / ISO / GB lab test measurements where verified. 中文：搜索面料数据库，按品类、克重、成分、适用品类、价格筛选。每条均含 AATCC / ISO / GB 方法的实测数据。

Get the complete lab-tested record of a single fabric by ID. PREREQUISITE: You MUST first call search_fabrics to obtain a valid fabric_id. Do not guess IDs. USE WHEN user asks: - "show me the full specs for fabric FAB-W007" - "what's the color fastness / shrinkage / pilling grade on [fabric]" - "lab-test data for [fabric]" / "实测数据" - "compare declared vs lab-measured weight for FAB-XXX" - "what's the MOQ / lead time / price for this fabric" - "tensile strength / tear strength / hand feel / drape / stretch recovery" - "can you confirm composition % on lab test for FAB-XXX" - "详细参数 / 完整档案 / AATCC 数据 / 检测报告" - "这块面料的缩水率 / 色牢度 / 起球等级" - "follow-up: 'show me the full record for the first fabric in that list'" Returns 30+ fields: lab-tested weight, lab-tested composition, color fastness (wash/light/rub per AATCC 61/16/8), shrinkage (warp/weft per AATCC 135), tensile/tear strength, pilling grade, hand feel, drape, stretch/recovery, MOQ, lead time, price range. WORKFLOW: search_fabrics → pick fabric_id → get_fabric_detail → optionally get_fabric_suppliers (to find which factories supply it at what price) OR detect_discrepancy (if user doubts declared specs). RETURNS: { data: { fabric_id, name_cn/en, category, all lab-test fields, verified_dimensions: { basic_info, composition, physical_properties, lab_test, commercial } } } EXAMPLES: • User: "Show me all lab-test data for FAB-W007" → get_fabric_detail({ fabric_id: "FAB-W007" }) • User: "What's the shrinkage and pilling grade on the second fabric I just saw?" → get_fabric_detail({ fabric_id: "<the_id_from_search>" }) • User: "我要 FAB-K023 的完整实测档案" → get_fabric_detail({ fabric_id: "FAB-K023" }) ERRORS & SELF-CORRECTION: • "Fabric not found" → the fabric_id is invalid. Re-run search_fabrics and use an ID from the fresh results. • Field returns null → that test wasn't performed on this fabric. Check verified_dimensions.lab_test to see what IS tested before asserting anything. • "not available" → unverified fabric in reserve pool. Filter search_fabrics for higher data_confidence. • Rate limit 429 → wait 60 seconds; do not retry immediately. AVOID: Do not call in a loop for multiple fabrics — if user wants to compare fabrics, present the search_fabrics summary list instead. Do not call to browse — use search_fabrics with filters. NOTE: Source: MRC Data (meacheal.ai). AATCC/ISO/GB methods cited per field. 中文：按 ID 获取单个面料的完整��测档案（含 AATCC/ISO/GB 检测指标）。

Search Chinese apparel industrial clusters and textile markets. USE WHEN user asks: - "where is China's [denim / suit / women's wear / underwear] manufacturing concentrated" - "what is the largest [silk / cashmere / down jacket] industrial cluster in China" - "industrial cluster comparison Humen vs Shaoxing vs Haining vs Zhili" - "recommend an industrial cluster for sourcing [product]" - "where should I set up a sourcing office for [category]" - "list mega clusters for [category]" - "fabric markets in Zhejiang / Jiangsu" - "accessories / trim / zipper / button markets in China" - "which province dominates [category] exports" - "follow-up: 'tell me more about Humen's cluster scale'" - "服装产业带 / 面料市场 / 产业集群 / 纺织集群 / 辅料市场" - "做 [品类] 应该去哪个产业带 / 集群推荐" Famous clusters this database covers include: Humen (Guangdong, womenswear), Shaoxing Keqiao (Zhejiang, fabric mega-market), Haining (Zhejiang, leather), Zhili (Zhejiang, children's wear), Shengze (Jiangsu, silk), Shantou (Guangdong, underwear), Puning (Guangdong, jeans), Jinjiang (Fujian, sportswear), and more. Returns paginated cluster list with name, location, specialization, scale, supplier count, average rent and labor cost, and key advantages/risks. WORKFLOW: Cluster discovery entry point. search_clusters → compare_clusters (side-by-side up to 10 cluster_ids) OR get_cluster_suppliers (list factories in that cluster) OR analyze_market (broader market view). RETURNS: { has_more: boolean, data: [{ cluster_id, name_cn, name_en, type, province, city, specialization, scale, supplier_count, labor_cost_avg_rmb }] } EXAMPLES: • User: "Where are the biggest denim clusters in China?" → search_clusters({ specialization: "denim", scale: "mega" }) • User: "Show me fabric markets in Zhejiang" → search_clusters({ province: "Zhejiang", type: "fabric_market" }) • User: "童装产业带有哪些" → search_clusters({ specialization: "童装" }) ERRORS & SELF-CORRECTION: • Empty data array → try in order: (1) drop scale filter, (2) broaden specialization (e.g. "服装" instead of "牛仔"), (3) remove type, (4) remove province. • Specialization mismatch → both Chinese and English work. Synonyms: sportswear/运动服, womenswear/女装, underwear/内衣, denim/牛仔. • Rate limit 429 → wait 60 seconds; do not retry immediately. • Empty after 3 retries → tell user: "No clusters match [criteria]. Try broader specialization or removing filters." AVOID: Do not use this for specific factory search — use search_suppliers. Do not compare clusters by calling search_clusters twice — use compare_clusters with cluster_ids. NOTE: Source: MRC Data (meacheal.ai). 170+ clusters mapped across 31 provinces. 中文：搜索中国服装产业带和面料市场。

Compare multiple Chinese apparel industrial clusters side-by-side on key metrics. PREREQUISITE: You MUST first call search_clusters to obtain valid cluster_ids. Do not guess IDs. USE WHEN user asks: - "compare Humen vs Shishi vs Jinjiang" - "which cluster has lower labor cost — Humen or Dongguan" - "side-by-side: Haining vs Xintang for denim" - "evaluate 3 clusters for my sportswear line" - "对比 [产业带1] 和 [产业带2]" / "哪个集群更适合 [品类]" - "rank these clusters by supplier count" - "which cluster has the highest scale for womenswear" - "follow-up: 'now compare the top 3 clusters you just listed'" Returns full records for each cluster so they can be compared on labor cost, rent, supplier count, scale, specializations, advantages, and risks. WORKFLOW: search_clusters → collect cluster_ids → compare_clusters → optionally get_cluster_suppliers on the winner to list factories in that specific cluster. RETURNS: { count: number, data: [full cluster objects with all fields] } EXAMPLES: • User: "Compare Humen, Shishi, and Jinjiang for sportswear sourcing" → compare_clusters({ cluster_ids: ["humen_women", "shishi_casual", "jinjiang_sportswear"] }) • User: "I want to evaluate Keqiao vs Zhili fabric markets" → compare_clusters({ cluster_ids: ["keqiao_fabric", "zhili_children"] }) • User: "对比虎门、石狮、晋江三个产业带" → compare_clusters({ cluster_ids: ["humen_women", "shishi_casual", "jinjiang_sportswear"] }) ERRORS & SELF-CORRECTION: • "Too many IDs (>10)" → split into batches of 10 and aggregate results in your response. • Fewer results than IDs sent → missing IDs were silently skipped (invalid cluster_id). Re-run search_clusters to verify IDs. • Empty data → all IDs were invalid. Re-run search_clusters and try again with fresh IDs. • Rate limit 429 → wait 60 seconds; do not retry immediately. AVOID: Do not call with guessed cluster_ids — always resolve them via search_clusters first. Do not use to list factories in a cluster — use get_cluster_suppliers. Do not compare > 10 clusters in one call. CONSTRAINT: Max 10 cluster IDs per call. NOTE: Source: MRC Data (meacheal.ai). 中文：对比多个产业带的核心指标（最多 10 个）。