DEV Community

Diego Costa
Diego Costa

Posted on

How to Connect Cursor and VS Code to a Live B2B Lead Enrichment MCP API

#mcp #ai #automation

How to Connect Cursor and VS Code to a Live B2B Lead Enrichment MCP API

Integrating real-time B2B firmographics and intent data directly into IDEs like Cursor and VS Code is now possible using a dedicated Model Context Protocol (MCP) server. This architecture allows LLMs to perform live lead enrichment and company research natively within the coding environment, eliminating the need for manual browser-based data collection or custom middleware.

Core Features

The B2B Lead Enrichment MCP API provides a robust bridge between AI agents and deep organizational intelligence. Unlike static datasets, this server offers several technical advantages:

  • Multilayered Data Retrieval: Access comprehensive firmographic (revenue, headcount, industry), technographic (software stack, infrastructure), and intent signals (hiring patterns, recent funding) via a single tool call.
  • Zero-Hallucination Schemas: All tool parameters are defined using strict Zod annotations. This ensures the LLM provides valid inputs and understands exactly which fields are required, virtually eliminating parameter hallucinations.
  • Contextual Awareness: By utilizing the MCP standard, the server allows Cursor or Claude to "reason" about a company based on real-time data before suggesting a sales script, a cold email, or a technical architecture for a specific prospect.

Integration Configuration

To enable these tools in Cursor or Claude Desktop, add the following configuration to your mcpServers settings. This uses the HTTP-to-MCP bridge to communicate with the production endpoint.

{
  "mcpServers": {
    "b2b-enrichment": {
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/server-http",
        "https://lead-enrichment-mcp.agent-infra.workers.dev/mcp"
      ],
      "env": {
        "LEAD_ENRICHMENT_API_KEY": "YOUR_FREE_API_KEY_HERE"
      }
    }
  }
}
Enter fullscreen mode Exit fullscreen mode

JSON-RPC Response Example

When the LLM invokes the enrich_lead tool, the MCP server returns a structured JSON-RPC response. This allows the AI to parse technical and financial data with high precision.

{
  "method": "tools/call",
  "params": {
    "name": "enrich_lead",
    "arguments": {
      "domain": "stripe.com"
    }
  },
  "result": {
    "companyName": "Stripe, Inc.",
    "industry": "Fintech / Payments",
    "technographics": ["AWS", "Ruby on Rails", "React", "GraphQL"],
    "intentSignals": {
      "hiringTrend": "Increasing",
      "recentNews": "Expanding global payout infrastructure"
    },
    "confidenceScore": 0.98,
    "estimatedRevenue": "$14B+"
  }
}
Enter fullscreen mode Exit fullscreen mode

Risk-Free Metered Billing

Traditional B2B data providers charge for every API call, regardless of data quality. This MCP server utilizes a Performance-Based Billing model designed for autonomous agents. You are only billed for successful enrichments that return a Confidence Score > 0.6. If the server cannot find a match or the data quality is low, the query cost is exactly $0. This allows for cost-effective scaling of SDR swarms and automated research agents without the risk of burning credits on "Not Found" responses.

Get Started with the Free Tier

Ready to upgrade your AI agent's firmographic intelligence? Visit the link below to generate your API key and access the full suite of B2B enrichment tools.

Visit lead-enrichment-mcp.agent-infra.workers.dev to get your API Key

Top comments (0)