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Mrc Data

by meacheal-ai

Verified Chinese apparel supply-chain data for finding suppliers, fabrics, clusters, and compliance information.

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Install Mrc Data

Pick your client, then add it in one click or paste the config.

STDIONode.js
~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "meacheal-ai-mrc-data": {
      "command": "npx",
      "args": [
        "-y",
        "mrc-data"
      ],
      "env": {
        "MRC_API_KEY": "YOUR_VALUE_HERE"
      }
    }
  }
}

Settings → Developer → Edit Config, merge this into mcpServers, then fully quit and reopen Claude Desktop.

Values are written into the snippet above so you can paste it as is. They never leave your browser.

Automated check passed— started and listed 20 tools correctly (1mo ago).

Overview

The meacheal-ai/mrc-data MCP server gives AI agents access to Chinese apparel supply-chain data covering suppliers, fabrics, and industrial clusters. It supports filtered and ranked supplier discovery, lab-tested fabric searches, cluster analysis, compliance checks, comparisons, discrepancy detection, and cost estimates. Records distinguish declared values from verified or lab-tested measurements and expose coverage information where available. Reach for it when sourcing Chinese apparel manufacturers or textiles and when supplier claims need additional verification context.

Use cases

  • Find Chinese apparel factories by product, region, capacity, or certification
  • Compare lab-tested fabrics by weight, composition, price, and intended use
  • Check a supplier’s readiness for US, EU, Japanese, or Korean markets
  • Identify manufacturing clusters and regional sourcing concentrations
  • Audit declared supplier or fabric specifications against verified measurements

Key features

  • Supplier search with geographic, product, capacity, and compliance filters
  • Lab-tested fabric specifications using AATCC, ISO, and GB methods
  • Industrial cluster discovery and side-by-side comparison
  • Declared-versus-verified discrepancy detection
  • Supplier recommendations, alternatives, and compliance checks
  • Paginated records with verification coverage metadata

Tools20

What Mrc Data lets your agent do. Expand a tool for its parameters.

Verified live~15.0k tokens of context

Security & health

What it can reach and how reliably it runs — from our own checks, not the maintainer’s claims.

ActiveLast checked 2d ago

Recent health check succeeded.

7/7 checks healthy over the last 78d

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned 10d ago via OSV.dev · mrc-data (npm)

Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

GitHub stars2Stargazers on the source repository.
npm downloads57Package downloads in the last 30 days.
Last commit6mo agoMost recent push to the default branch.
Availability100%Our rolling endpoint + install checks that succeeded.
Install checkPassedOur sandbox started it and listed its tools.
Tools exposed20Callable tools this server registers over MCP.
Directory activity3 viewsConfig copies, upvotes, and views on AllMCPs.

How Mrc Data works

What meacheal-ai/mrc-data MCP server does

The meacheal-ai/mrc-data MCP server provides structured sourcing data for China’s apparel and textile industry. Its datasets cover verified or partially verified suppliers, lab-tested fabrics, industrial clusters, and links between suppliers and fabrics. The repository describes coverage of more than 3,000 suppliers, more than 350 fabrics, and more than 170 clusters across 31 provinces, while the listing emphasizes 1,000+ verified suppliers and 350+ lab-tested fabrics.

Supplier searches can filter by province, city, supplier type, product category, monthly capacity, compliance status, and quality score. Fabric searches support category, weight, composition, intended apparel use, and price filters. Cluster searches identify manufacturing concentrations and textile markets. Results are paginated and include identifiers for follow-up operations.

How it works

The meacheal-ai/mrc-data MCP server exposes MCP tools through the hosted endpoint https://api.meacheal.ai/mcp. It also supports a local npm invocation. Most detail and comparison operations use IDs returned by an earlier search: resolve a supplier with search_suppliers or recommend_suppliers, a fabric with search_fabrics, or a cluster with search_clusters before requesting deeper records.

The data model separates supplier-declared information from independently checked or measured values. Supplier and fabric records can include verification coverage, such as the number of verified dimensions out of eight for suppliers or five for fabrics. Fabric records may include measurements using AATCC, ISO, and GB methods. Discrepancy detection compares declared and tested values when both are present; it should be treated as a data-quality signal rather than proof of fraud.

Setup and configuration

The hosted service requires an API key. For a local npm setup, configure the key as MRC_API_KEY and run the package with npx.

Example client configuration uses the MCP URL and an Authorization: Bearer YOUR_API_KEY header. The README specifically documents Claude Desktop, Cursor, VS Code, Cline, Windsurf, JetBrains, Zed, and Claude Code configurations. Free access includes 100 daily requests; Pro, Team, and Enterprise tiers provide higher daily limits.

Tools and capabilities

The meacheal-ai/mrc-data MCP server includes tools for:

  • Searching suppliers, fabrics, and industrial clusters.
  • Retrieving full supplier and fabric records after resolving an ID.
  • Comparing up to 10 suppliers or clusters side by side.
  • Listing fabrics offered by a supplier or suppliers linked to a fabric.
  • Checking export-market compliance for the US, EU, Japan, or Korea.
  • Detecting declared-versus-tested discrepancies in capacity, workers, weight, or composition.
  • Recommending suppliers, finding alternatives, analyzing markets, and estimating sourcing costs.
  • Viewing product categories, province distributions, database statistics, and cluster suppliers.

Use search_suppliers for exact filtering and recommend_suppliers for ranked matches. Missing fields indicate incomplete verification, not necessarily non-compliance. The service also documents a 429 rate limit; callers should wait 60 seconds rather than retry immediately.

Read the full README View source on GitHub

Reviews

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Frequently Asked Questions about Mrc Data

Set the MRC_API_KEY environment variable and run `npx -y mrc-data`, or configure the hosted endpoint at https://api.meacheal.ai/mcp with a bearer token.

Yes. The README provides a Claude Desktop configuration using the hosted MCP endpoint and an Authorization bearer header.

It provides Chinese apparel suppliers, lab-tested fabrics, industrial clusters, supplier-fabric links, compliance information, market analysis, and declared-versus-verified data comparisons.

Yes. The documented hosted and local configurations use an API key, with MRC_API_KEY shown for the npm invocation.

It includes check_compliance for US, EU, Japan, and Korea market requirements, but incomplete fields should be reported as not confirmed rather than compliant or non-compliant.

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