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Diego Costa
Diego Costa

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Eliminating LLM Hallucinations in Sales Agents with a Native B2B Lead Enrichment MCP Server

#mcp #ai #automation

Eliminating LLM Hallucinations in Sales Agents with a Native B2B Lead Enrichment MCP Server

To eliminate LLM hallucinations in B2B workflows, developers are transitioning to the Model Context Protocol (MCP) to provide agents with a high-fidelity B2B lead enrichment MCP server for real-time company profiles. This architecture replaces probabilistic generation with deterministic data retrieval, ensuring that firmographics and intent signals are strictly verified via Zod-enforced schemas before they reach the model's context window.

Core Features

The primary challenge in building autonomous sales agents is the "hallucination gap"—where an LLM confidently invents a company's tech stack or headcount. The B2B Lead Enrichment MCP API solves this by exposing a suite of tools that utilize strict parameter validation to ensure the AI only requests and receives authenticated data.

  • Strict Zod Schema Enforcement: Every tool in the MCP server uses detailed JSON Schema descriptions, forcing models like Claude 3.5 Sonnet or GPT-4o to pass valid, properly formatted arguments (e.g., domain strings, ISO country codes).
  • Multi-Layered Data Enrichment: Retrieve deep Firmographic (revenue, headcount), Technographic (current software stack), and Intent Signals (hiring trends, recent funding) in a single request.
  • Stateful Tool Discovery: As an MCP-native server, it supports dynamic tool discovery, allowing Cursor or Claude Desktop to "see" exactly which enrichment capabilities are available without manual prompt engineering.

Implementation: Connecting Your AI Agent

To give your LLM or IDE native access to live B2B data, add the following configuration to your claude_desktop_config.json or your Cursor settings. This bypasses the need for custom middleware or complex API integration code.

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

When your agent invokes the enrich_lead tool, the MCP server returns a clean, structured payload. This high-density context allows the agent to make informed decisions without "guessing" company details.

{
  "jsonrpc": "2.0",
  "result": {
    "companyName": "Acme Corp",
    "industry": "Enterprise SaaS",
    "technographics": ["Salesforce", "AWS", "HubSpot", "Datadog"],
    "employeeCount": 1250,
    "intentSignals": {
      "hiringTrend": "high",
      "expansionSignal": "Series C Funding"
    },
    "confidenceScore": 0.98,
    "status": "success"
  }
}
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Risk-Free Metered Billing

Unlike traditional B2B data providers that charge per query regardless of quality, this MCP server utilizes a Confidence-First Billing model. You are only billed for successful enrichments where the confidenceScore exceeds 0.6. If the data is low-quality, the record is missing, or the query fails to find a match, the cost is $0. This allows developers to build high-volume SDR swarms and autonomous research agents with a predictable, performance-linked ROI.

Get Started for Free

Stop letting your sales agents hallucinate lead data. Deploy a robust, schema-validated context layer to your AI today.

Visit lead-enrichment-mcp.agent-infra.workers.dev to generate your API key and access the free tier instantly.

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