How to Deploy a Real-Time B2B Lead Enrichment MCP Server for Claude and Cursor

Integrating a dedicated B2B lead enrichment MCP server allows LLMs like Claude 3.5 Sonnet and GPT-4o to perform real-time firmographic lookups and intent analysis natively within their reasoning loops. By utilizing the Model Context Protocol (MCP), developers can eliminate manual data entry and "copy-paste" workflows, providing agents with standardized, tool-based access to live company profiles and technographic data.

Core Features

The B2B Lead Enrichment MCP API provides a robust bridge between Large Language Models and high-fidelity corporate datasets. Unlike static databases, this server provides a dynamic interface through Zod-annotated tool definitions, which virtually eliminate parameter hallucinations by forcing the LLM to adhere to strict schema requirements.

• Deep Firmographics: Access real-time data on employee headcount, annual revenue, industry vertical, and global headquarters location.
• Technographic Mapping: Identify a company's current tech stack, including cloud providers, CRM usage, and marketing automation tools.
• Intent Signals: Retrieve real-time indicators of buying intent and organizational changes to prioritize high-value leads.
• Zod Schema Validation: Every tool (e.g., enrich_lead) uses strict input validation to ensure the LLM provides valid domains or email addresses before a request is ever processed.

Configuration for Claude Desktop and Cursor

To give your AI coding assistant or desktop agent native access to B2B data, add the following configuration to your claude_desktop_config.json or your Cursor MCP settings. This connects the client directly to the hosted MCP endpoint via Server-Sent Events (SSE).

{
  "mcpServers": {
    "b2b-lead-enrichment": {
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/server-http",
        "--url",
        "https://lead-enrichment-mcp.agent-infra.workers.dev/mcp"
      ],
      "env": {
        "API_KEY": "YOUR_FREE_API_KEY"
      }
    }
  }
}

Standardized JSON-RPC Response Payload

When the LLM calls the enrich_lead tool, the MCP server returns a clean, structured JSON-RPC object. This ensures the model receives a high-density context window without extraneous HTML or marketing noise.

{
  "method": "tools/call",
  "params": {
    "name": "enrich_lead",
    "arguments": {
      "domain": "stripe.com"
    }
  },
  "result": {
    "content": [
      {
        "type": "text",
        "text": {
          "companyName": "Stripe, Inc.",
          "industry": "Financial Services / Fintech",
          "headcount": "7,000+",
          "technographics": ["AWS", "React", "Ruby on Rails", "Salesforce"],
          "intentSignals": ["High: Expanding EMEA operations", "Medium: Hiring for AI/ML roles"],
          "confidenceScore": 0.98
        }
      }
    ]
  }
}

Risk-Free Metered Billing for AI Workflows

Most B2B data providers charge per "match attempt," which is prohibitively expensive for autonomous agents that might encounter low-quality data or non-existent domains. Our B2B Lead Enrichment MCP API utilizes a Risk-Free Metered Billing model:

1. Confidence Thresholding: You are only billed for successful enrichments that return a Confidence Score > 0.6.
2. Zero-Cost Failures: Queries that result in no data found or low-confidence matches cost $0.
3. Cost-Effective SDR Swarms: This allows you to scale autonomous SDR swarms that can process thousands of leads without worrying about billing spikes from "hallucinated" or junk lead lists.

Get Started with a Free API Key

Ready to upgrade your AI agents with real-time B2B intelligence? You can grab a free-tier API key and start enriching leads directly from your terminal or LLM interface in seconds.

Visit lead-enrichment-mcp.agent-infra.workers.dev to get your API key and view the full documentation.