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Diego Costa
Diego Costa

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How to Fix LLM Parameter Hallucinations in Sales Agent Tools using native MCP

#mcp #ai #automation

How to Fix LLM Parameter Hallucinations in Sales Agent Tools using native MCP

The most effective way to eliminate LLM parameter hallucinations in B2B workflows is by utilizing a Model Context Protocol (MCP) server that enforces strict schema validation for real-time lead enrichment. By integrating the B2B Lead Enrichment MCP API directly into your agentic environment, you ensure that LLMs like Claude or Cursor receive high-fidelity firmographic and intent data without the parsing errors common in traditional API middleware.

Core Features of MCP-Native Enrichment

Standard API integrations often suffer from "parameter drift" where the LLM guesses field names or data types, leading to 400 errors or logic failures. Our B2B Lead Enrichment MCP server solves this by using Zod-annotated tool definitions that the model consumes natively as part of its context window.

  • Strict Type Enforcement: Every tool, such as enrich_lead, is defined with precise string constraints and required fields to guide the LLM's reasoning.
  • Multi-Layered Data Retrieval: Access Firmographic data (revenue, headcount), Technographic profiles (current software stack), and Intent Signals (recent funding, hiring surges) in a single request.
  • Dynamic Discovery: The MCP protocol allows your agent to self-document the available tools, meaning the model "knows" exactly how to query for a specific company or domain without manual prompt engineering.

Integrating the MCP Server

To give your LLM (Claude Desktop, Cursor, or VS Code Copilot) direct access to live B2B data, add the following configuration to your MCP settings file:

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

When the LLM calls the enrich_lead tool, it receives a structured JSON-RPC response. This structure prevents the model from hallucinating company details because the data is injected directly into its "observed" state with high confidence scores.

{
  "method": "tools/call",
  "params": {
    "name": "enrich_lead",
    "arguments": {
      "domain": "stripe.com"
    }
  },
  "result": {
    "content": [
      {
        "type": "text",
        "text": {
          "companyName": "Stripe, Inc.",
          "industry": "Fintech / Payments",
          "technographics": ["AWS", "React", "Ruby on Rails"],
          "intentSignals": ["Expanding into LatAm", "Hiring 50+ Engineers"],
          "confidenceScore": 0.98,
          "status": "success"
        }
      }
    ]
  }
}
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Risk-Free Metered Billing Architecture

Building autonomous SDR swarms or automated lead scoring can become expensive if you pay for low-quality data. Our MCP server implements a Risk-Free Metered Billing model. This means your API key is only debited for successful enrichments that return a Confidence Score > 0.6.

If the data is stale, the domain is invalid, or the enrichment confidence is low, the request is free ($0 cost). This allows developers to build high-volume agentic loops—such as SDR agents scanning LinkedIn or news feeds—without the financial risk of paying for "No Results Found."

Get Your Free API Key Today

Stop fighting LLM hallucinations and start feeding your agents high-quality, structured B2B data. Visit our documentation and dashboard to get started.

Visit lead-enrichment-mcp.agent-infra.workers.dev to grab an API key on the free tier instantly.

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