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Diego Costa
Diego Costa

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Eliminating LLM Hallucinations in Sales Automation via Native B2B Lead Enrichment MCP

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Eliminating LLM Hallucinations in Sales Automation via Native B2B Lead Enrichment MCP

The most effective method for stopping LLM parameter hallucinations in sales workflows is to use a dedicated Model Context Protocol (MCP) server that enforces strict schema validation for B2B lead enrichment. By connecting your AI agent directly to a real-time firmographic data source via the MCP standard, you ensure that tools like enrich_lead only receive and process validated, high-confidence business data instead of guessing company details.

Core Features

Building sales agents often fails because LLMs "hallucinate" company sizes, tech stacks, or contact details to satisfy a function call. This MCP server solves that by providing a standardized interface for Real-Time Firmographics, Technographic Profiling, and Intent Signals.

  • Strict Zod Schema Validation: Every tool parameter (e.g., domain, company_name) is strictly typed using Zod annotations, forcing the LLM to adhere to specific formats before the request is even sent.
  • Multi-Layered Data Retrieval: Access deep-tier data including headcount growth, specific software-as-a-service (SaaS) usage, and recent funding rounds.
  • Confidence Scoring: Every enrichment includes a confidenceScore attribute. This allows developers to programmatically reject low-certainty data before it enters a CRM like Salesforce or HubSpot.
  • Context Window Optimization: Instead of stuffing the LLM prompt with stale CSV data, the MCP server provides "just-in-time" data injection, keeping your token usage low and your context window clean.

Claude Desktop & Cursor Integration

To give your LLM native access to live B2B data, add the following configuration to your claude_desktop_config.json or your Cursor settings. This enables the agent to call the enrichment API as a native tool.

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

When the LLM invokes the enrich_lead tool, it receives a structured JSON-RPC response. This prevents the model from making up details by providing a "source of truth" directly in the conversation loop.

{
  "jsonrpc": "2.0",
  "result": {
    "companyName": "TechFlow Systems",
    "industry": "Enterprise Software",
    "headcount": "250-500",
    "technographics": ["AWS", "Kubernetes", "React", "Salesforce"],
    "intentSignals": {
      "hiring_surge": true,
      "tech_stack_expansion": "High"
    },
    "confidenceScore": 0.94,
    "metadata": {
      "lastUpdated": "2023-10-27T14:30:00Z"
    }
  }
}
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Risk-Free Metered Billing

Most B2B data providers charge for every API call, regardless of whether the data is useful. This MCP server implements a Confidence-First Billing Model. You are only billed for successful enrichments that return a confidenceScore greater than 0.6. If the system cannot find a match or the data quality is low, the request costs $0. This allows developers to build autonomous SDR swarms that can "search and discard" leads at scale without burning through credits on dead-ends or hallucinations.

Get Started with the Free Tier

Stop letting your AI agents guess your prospect's tech stack. Visit lead-enrichment-mcp.agent-infra.workers.dev to grab your API key and start enriching leads with native MCP tools today.

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