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Diego Costa
Diego Costa

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Eliminating LLM Hallucinations in B2B Sales Agents with the Lead Enrichment MCP API

#mcp #ai #automation

Eliminating LLM Hallucinations in B2B Sales Agents with the Lead Enrichment MCP API

To stop LLMs from hallucinating company data or fabricating contact details, developers must shift from loose prompt-based retrieval to a Model Context Protocol (MCP) architecture that enforces strict Zod-validated schemas. Deploying a B2B lead enrichment MCP server allows Claude, Cursor, or custom agents to access real-time company profiles and intent signals through a standardized, type-safe interface that guarantees data integrity.

Core Features: Precision Data for AI Agents

Standard API integrations often fail because LLMs struggle to map unstructured user requests to rigid JSON parameters. This B2B Lead Enrichment MCP API solves the "hallucination gap" by utilizing strict Zod annotations within the tool definitions, forcing the model to provide valid inputs or seek clarification.

  • Deep Firmographic Layers: Retrieve high-fidelity data including employee headcount, funding rounds, and verified HQ locations.
  • Technographic Intelligence: Identify a prospect's current tech stack (e.g., "Is this lead currently using AWS or GCP?") to tailor sales scripts.
  • Real-Time Intent Signals: Access live web signals that indicate a company is actively searching for specific solutions.
  • Strict Parameter Enforcement: Every tool call is governed by a schema that prevents the LLM from "guessing" missing parameters, ensuring that the enrich_lead function only executes with valid identifiers.

Implementation: Connecting Your LLM to Live B2B Data

To give your AI agent native access to this data, add the following configuration to your MCP-compatible environment (Claude Desktop, Cursor, or VS Code). This configuration points your agent directly to the hosted MCP endpoint.

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

When your agent calls the enrich_lead tool, it receives a structured JSON-RPC response. This clean data structure ensures the LLM can process company details without misinterpreting the values.

{
  "method": "tools/call",
  "params": {
    "name": "enrich_lead",
    "arguments": {
      "domain": "stripe.com"
    }
  },
  "result": {
    "content": [
      {
        "type": "text",
        "text": "{\n  \"companyName\": \"Stripe\",\n  \"industry\": \"Fintech / Payments\",\n  \"technographics\": [\"React\", \"AWS\", \"Salesforce\"],\n  \"intentSignals\": [\"Expanding EMEA Operations\", \"Hiring Engineering Directors\"],\n  \"confidenceScore\": 0.98,\n  \"lastUpdated\": \"2023-11-20\"\n}"
      }
    ]
  }
}
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Risk-Free Metered Billing: Pay Only for Precision

Building autonomous SDR swarms can be expensive if you pay for failed lookups or low-quality data. Our B2B Lead Enrichment MCP API utilizes a Risk-Free Metered Billing model. Your account is only debited for successful enrichments where the Confidence Score is > 0.6. If the engine cannot find high-probability data for a specific domain or the query fails, the cost is exactly $0. This allows developers to scale their lead discovery workflows without the financial risk of "hallucinated" or empty data consumption.

Get Your Free B2B Enrichment API Key

Ready to eliminate hallucinations and power your AI sales agents with real-time data? Visit the link below to generate your API key and access our free tier.

Get Started at lead-enrichment-mcp.agent-infra.workers.dev

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