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Diego Costa
Diego Costa

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How to Eliminate LLM Hallucinations in AI Sales Agents Using the Model Context Protocol

#mcp #ai #automation

How to Eliminate LLM Hallucinations in AI Sales Agents Using the Model Context Protocol

The most effective way to eliminate LLM hallucinations in sales automation is by implementing a B2B lead enrichment MCP server that enforces strict input validation through the Model Context Protocol. This architecture allows AI agents to retrieve real-time company profiles and firmographics directly within their native runtime environment, ensuring every tool call is grounded in verified, structured data rather than probabilistic guesses.

Core Features

Our MCP server provides a high-fidelity bridge between your AI models and live B2B intelligence. By utilizing strict Zod-schema annotations for every tool parameter, we provide the LLM with a rigid boundary that prevents the "guessing" of company domains or contact details. The data layers include:

  • Real-time Firmographics: Deep metadata including employee count, revenue range, and precise industry classification.
  • Technographic Intelligence: Identification of the software stack (e.g., "Is this lead using Salesforce or HubSpot?") to tailor outreach.
  • Intent Signals: Recent funding rounds, job surges, and organizational changes that signal a high propensity to buy.
  • Native Tool Integration: Full compatibility with Claude Desktop, Cursor, and VS Code Copilot via the standard MCP JSON-RPC interface.

Quickstart Configuration

To connect your AI agent (like Claude Desktop) to live B2B enrichment tools, add the following entry to your claude_desktop_config.json file:

{
  "mcpServers": {
    "b2b-lead-enrichment": {
      "command": "npx",
      "args": [
        "-y",
        "@agent-infra/mcp-server-lead-enrichment"
      ],
      "env": {
        "LEAD_ENRICHMENT_API_KEY": "YOUR_FREE_API_KEY",
        "MCP_ENDPOINT": "https://lead-enrichment-mcp.agent-infra.workers.dev/mcp"
      }
    }
  }
}
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Validated JSON-RPC Response Example

When your agent calls the enrich_lead tool, it receives a clean, structured payload. This format ensures the LLM can parse technographics and intent signals without ambiguity:

{
  "jsonrpc": "2.0",
  "id": "1",
  "result": {
    "companyName": "Acme Corp",
    "domain": "acme.com",
    "industry": "Enterprise SaaS",
    "technographics": ["PostgreSQL", "AWS", "Stripe", "React"],
    "intentSignals": {
      "fundingRound": "Series B",
      "hiringVelocity": "High",
      "recentNews": "Expanded operations to EMEA"
    },
    "confidenceScore": 0.98,
    "status": "success"
  }
}
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Risk-Free Metered Billing

Efficiency is at the core of our infrastructure. We utilize a Risk-Free Metered Billing model designed specifically for autonomous workflows. Unlike legacy APIs that charge for every request, our system only bills your credits when the confidenceScore of the enrichment is greater than 0.6. If our engine cannot find high-quality, verified data for a query, the request costs $0, allowing you to scale SDR swarms and agentic workflows without the risk of paying for "No Results Found."

Get Your Free API Key

Ready to upgrade your sales agents with real-time firmographic intelligence? Stop dealing with stale CSV exports and give your LLMs the live tools they deserve.

Visit lead-enrichment-mcp.agent-infra.workers.dev to grab your API key on our free tier and start enriching leads natively within Claude or Cursor today.

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