MCP Server Suggestion: MRC Data — Chinese Apparel Supply Chain Database

[meacheal-ai]

Use Case

Continue users working in fashion / sourcing / manufacturing domains often need to query Chinese apparel supply chain data while coding (sourcing automation, supplier verification, compliance reporting). Current options require manual research across fragmented B2B platforms — none of which separates supplier-declared data from independently verified data.

Proposed MCP Server

MRC Data — verified Chinese apparel supply chain data infrastructure for AI agents:

• 3,000+ verified Chinese apparel manufacturers across 31 provinces
• 350+ lab-tested fabric specifications (AATCC / ISO / GB methods)
• 170+ industrial clusters (Humen, Shaoxing, Haining, Zhili, Shengze, etc.)
• Compliance certifications: BSCI, OEKO-TEX, GRS, GOTS, SA8000, WRAP, REACH

Key differentiator: explicitly distinguishes declared (what suppliers claim) vs verified (what was independently lab-measured) — addressing the structural gap that makes Chinese supply chain data unreliable for AI agents.

Continue config.yaml

mcpServers:
  - name: mrc-data
    command: npx
    args: ["-y", "mrc-data"]

Or use the hosted API endpoint: https://api.meacheal.ai/mcp

Resources

• Repository: https://github.com/meacheal-ai/mrc-data
• Homepage: https://meacheal.ai
• Smithery (96/100 score): https://smithery.ai/server/@meacheal-ai/mrc-data
• License: MIT (npm wrapper package)

Already listed in

• punkpeye/awesome-mcp-servers (85k⭐)
• TensorBlock/awesome-mcp-servers
• collabnix/awesome-mcp-lists (PR Docs: Align READMEs / VS Code extension / PyPi with docs language / content #51 merged)
• mcpservers.org (submission ID 1556)

Happy to provide additional config examples or test cases if useful for Continue users.