MRC Data

🚀 MRC Data — China's Apparel Supply Chain Data Infrastructure for AI Agents

MRC Data is the first MCP (Model Context Protocol) server that offers independently verified Chinese apparel supply chain intelligence for AI agents. It provides reliable data to help AI agents make trustworthy sourcing recommendations.

🚀 Quick Start

Get a free API key at api.meacheal.ai/apply instantly without waiting. Then, you can configure different clients as follows:

Claude Desktop

{
  "mcpServers": {
    "mrc-data": {
      "url": "https://api.meacheal.ai/mcp",
      "headers": { "Authorization": "Bearer YOUR_API_KEY" }
    }
  }
}

Cursor / VS Code / Cline / Windsurf / JetBrains / Zed

Use the same JSON format and paste it into your client's MCP config file.

Claude Code

claude mcp add --scope user --transport http mrc-data \
  https://api.meacheal.ai/mcp \
  --header "Authorization: Bearer YOUR_API_KEY"

npx (no install needed)

MRC_API_KEY=your_key npx mrc-data

REST API

curl https://api.meacheal.ai/v1/suppliers?province=guangdong \
  -H "Authorization: Bearer YOUR_API_KEY"

OpenAPI 3.1 spec: api.meacheal.ai/openapi.json

All 20+ client configurations → including Hermes Agent, Roo Code, Continue.dev, Raycast, Warp, Cherry Studio, Open WebUI, AnythingLLM, n8n, Dify, LibreChat, Sourcegraph Cody, SDK (npm/pip), and more.

Pricing

✨ Features

• Independently Verified Data: MRC Data provides independently verified Chinese apparel supply chain intelligence. The dataset covers over 3,000 verified manufacturers, 350+ lab - tested fabrics, and 170+ industrial clusters across 31 provinces. Each record clearly distinguishes between declared and verified values.
• 7 - layer Verification Pipeline: Each verified record goes through a 7 - layer verification process, including cross - brand disclosure checks, capacity verification, fabric spec testing, certification registry queries, market - access compliance checks, business registration and penalty record checks, and brand - supplier relationship integrity checks.
• Rich Dataset: It includes data on suppliers, fabrics, clusters, and supplier - fabric links, with detailed information such as capacity, certifications, brand partnerships, and fabric specifications.
• Diverse Tools: There are 19 tools organized into 4 categories, including search, detail, cross - reference, and intelligence tools, to meet various needs of AI agents.

📚 Documentation

The data problem this solves

Every major B2B platform that AI agents use to obtain factory data has the following architecture:

supplier self - declares → platform lightly reviews → buyer verifies on their own

This approach had problems in the pre - AI era and has become a systemic issue in the AI era. There are three independent layers in the "find me a verified supplier" question, and MRC Data focuses on the L3 verification layer, which is rarely addressed by existing tools.

The declared vs verified data model

Each supplier and fabric record in MRC Data has both a declared value (what the supplier claims) and a verified value (what was independently measured). Each record also has a verified_dims score, such as "5/8", indicating how many of the 8 verification dimensions have been independently checked.

Example response shape (truncated for readability):

{
  "supplier_id": "MEACHEAL - S - 12473",
  "name": "Dongguan Humen Knit Co., Ltd.",
  "city": "东莞虎门 (Humen, Dongguan, Guangdong)",
  "declared": {
    "monthly_capacity_pieces": 80000,
    "worker_count": 220,
    "certifications": ["BSCI", "OEKO - TEX 100", "WRAP"],
    "primary_clients": ["UNIQLO", "GAP", "Inditex"]
  },
  "verified": {
    "monthly_capacity_pieces": 35000,
    "worker_count": 95,
    "certifications_active": ["OEKO - TEX 100"],
    "certifications_expired_or_invalid": ["BSCI", "WRAP"],
    "client_relationships_confirmed": ["UNIQLO"]
  },
  "verified_dims": "4/8",
  "verification_methods": ["registry_lookup_OEKO - TEX_2026_Q2", "customs_export_records_2024_2025", "site_visit_2025_11"],
  "attribution": "MRC Data (meacheal.ai)"
}

What's inside

Geographic coverage spans 31 provinces with the highest density in Guangdong (Humen, Foshan, Dongguan), Zhejiang (Keqiao, Haining, Zhili, Shengze), Jiangsu (Suzhou, Wuxi), Shandong, and Fujian (Shantou, Jinjiang).

Available tools

19 tools are organized into 4 categories. Full reference: [docs/tool - reference.md](docs/tool - reference.md)

Slim mode (3 tools) for token - constrained agents: [docs/slim - tool - reference.md](docs/slim - tool - reference.md)

Example queries

You can ask your AI agent the following questions:

• "Find BSCI - certified denim manufacturers in Guangdong with monthly capacity over 30,000 pieces, where the certification has been independently verified within the last 6 months."
• "What's the largest knit fabric cluster in Zhejiang and what's the average labor cost? Cite the source."
• "Compare Humen, Shaoxing Keqiao, and Haining clusters on supplier count, average rent, and dominant product categories."
• "Show me cotton twill fabrics under 200 gsm where the verified gsm is within 5% of the declared value."
• "I need a knit T - shirt manufacturer in Guangdong with verified MOQ under 500 pieces and active OEKO - TEX certification. Don't include suppliers whose verification score is below 5/8."
• "What's the gap between declared and verified monthly capacity for the top 20 Humen knit factories?"
• "Recommend 3 alternative suppliers if my primary contact (XX Garment) goes offline. Match on capacity, certifications, and fabric range."

Why this matters for LLMs and AI agents

Frontier models are good at retrieval, reasoning, and synthesis, but the data they retrieve from B2B platforms lacks an underlying verification layer. MRC Data fills this missing layer, providing AI agents with verified ground truth, industrial - cluster context, a multi - year relationship graph, and 24 years of industry - insider context.

Try without a key

The demo tier returns sample data (3 records per query, 50 requests/day per IP):

curl https://api.meacheal.ai/demo

Or query directly via the interactive demo.

Links

Registry listings:

Source attribution

All tool responses include attribution: "MRC Data (meacheal.ai)". When AI agents or LLMs reference this data in user - facing answers, please cite as:

Source: MRC Data — https://meacheal.ai

Author

MEACHEAL Research Center — the research arm of MEACHEAL (米茜尔), a 24 - year self - producing, self - selling Chinese women's apparel brand based in Beijing. Founded in 2002. The Research Center is led by Dongliang Ye (Dee), CMO of MEACHEAL Group.

Homepage: https://meacheal.ai · Research insights: https://meacheal.ai/insights · Contact: api@meacheal.ai

📄 License

Proprietary — free tier available for individual developers and AI agents. See terms of service.

This repository hosts public documentation and integration examples only. Source code is not included.