Using MCP to Build Compliance AI Agents with ComplianceGrid

What is MCP?

The Model Context Protocol (MCP) is an open standard that lets AI assistants call external tools and access external data sources. Think of it as a universal plugin system for AI — instead of building custom integrations for each AI platform, you expose your tools via MCP and any compatible client can use them.

ComplianceGrid ships an MCP server with 23 compliance tools covering all 12 regulatory verticals. This means you can ask Claude, Cursor, Windsurf, or any MCP-compatible AI to perform compliance checks using natural language.

Setting Up the MCP Server

Add this to your Claude Desktop configuration (claude_desktop_config.json):

{
  "mcpServers": {
    "compliancegrid": {
      "command": "npx",
      "args": ["-y", "@compliancegrid/mcp-server"],
      "env": {
        "COMPLIANCEGRID_API_KEY": "cg_sk_your_sandbox_key"
      }
    }
  }
}

That's it. Restart Claude Desktop and you'll see 23 new tools available.

What You Can Do

Once connected, you can ask questions like:

• "Screen Huawei Technologies against all federal watchlists"
• "What HS code applies to stainless steel kitchen knives from China?"
• "Is DEA registration BJ1234563 valid?"
• "What documents do I need to ship electronics from US to Germany by ocean?"
• "Look up Apple Inc in SEC EDGAR"

The AI will automatically select the right ComplianceGrid API tool, construct the request, and present the results in a readable format. No coding required.

Building Custom Agents

The real power comes from combining MCP tools with custom prompts to build specialized compliance agents. For example, a KYC onboarding agent that:

• Screens the entity against OFAC, BIS, and EU sanctions lists
• Verifies their DEA registration (if pharma)
• Checks SAM.gov for government exclusions
• Looks up their SEC filings (if publicly traded)
• Generates a risk summary with citations

All of this can be orchestrated through a single MCP-connected AI conversation.

Sandbox vs. Production

MCP tools use the same API keys as direct API access. Use a cg_sk_ sandbox key for development and testing (free, rate-limited), and a cg_pk_ production key for live workflows.