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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 stop AI agents from hallucinating company data, developers are shifting toward the Model Context Protocol (MCP) to provide strict, schema-validated access to live B2B firmographics and intent signals. By using a specialized B2B lead enrichment MCP server, LLMs like Claude or GPT-4o gain a standardized toolset that enforces Zod-validated input parameters, ensuring zero-shot accuracy for company profiles and technographic data.

Core Features

The B2B Lead Enrichment MCP API provides a robust, real-time data layer designed specifically for the latest generation of agentic workflows. Unlike traditional REST wrappers, this server utilizes the Model Context Protocol to expose data tools directly to the LLM's reasoning engine.

  • Verified Firmographics: Access real-time data on company size, revenue brackets, industry verticals, and global headquarters locations.
  • Deep Technographics: Identify the specific software stack, cloud infrastructure, and SaaS tools a target company is currently utilizing.
  • Real-Time Intent Signals: Track hiring surges, recent funding rounds, and product launches to prioritize high-value leads.
  • Zero-Hallucination Parameters: Every tool input (e.g., enrich_lead) uses strict Zod-schema annotations. This prevents the LLM from passing malformed domains or guessing company attributes, as the MCP protocol forces the model to adhere to the defined JSON-RPC 2.0 interface.

Implementation: Connecting Cursor or Claude Desktop

To integrate live enrichment data into your IDE or desktop assistant, add the following configuration to your claude_desktop_config.json or Cursor's MCP settings:

{
  "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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Standardized JSON-RPC Response Payload

When an LLM invokes the enrich_lead tool, it receives a structured JSON object. This eliminates the need for the model to "guess" or "hallucinate" details when it lacks sufficient context in its training data.

{
  "jsonrpc": "2.0",
  "id": "1",
  "result": {
    "companyName": "Acme Corp",
    "industry": "Enterprise Software",
    "headcount": "500-1000",
    "technographics": ["AWS", "Salesforce", "React", "PostgreSQL"],
    "intentSignals": {
      "funding": "Series C - $50M",
      "hiring": "High (Engineering & Sales)"
    },
    "confidenceScore": 0.98,
    "source": "verified_firmographic_index"
  }
}
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Risk-Free Metered Billing for Scalable AI

One of the primary barriers to building autonomous SDR agents is the cost of failed lookups or low-quality data. Our MCP server solves this with a Confidence-First Billing Model. Developers are only billed for successful enrichments that return a Confidence Score > 0.6. If the server returns a low-confidence result or fails to find the company, the query costs exactly $0. This allows for massive, risk-free batch processing of lead lists and autonomous "prospecting swarms" without the fear of burning through API credits on invalid data.

Get Your Free API Key

Ready to eliminate hallucinations and give your agents real-world B2B awareness? Visit lead-enrichment-mcp.agent-infra.workers.dev to generate your API key and start building on the free tier today.

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