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Diego Costa
Diego Costa

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How to Fix LLM Parameter Hallucinations in Sales Agents with Native B2B Lead Enrichment MCP

#mcp #ai #automation

How to Fix LLM Parameter Hallucinations in Sales Agents with Native B2B Lead Enrichment MCP

The most effective method for eliminating LLM hallucinations in sales automation is by replacing ambiguous system prompts with a Model Context Protocol (MCP) server that enforces strict JSON-RPC schemas for B2B lead enrichment. By connecting Claude or Cursor directly to this MCP-native API, agents gain real-time access to validated firmographics and intent data, ensuring every outbound signal is grounded in fact rather than probabilistic guesswork.

Core Features

Building reliable sales agents requires more than just a large context window; it requires deterministic data retrieval. Our B2B Lead Enrichment MCP server solves the "hallucination gap" by utilizing strict Zod-annotated schemas that force the LLM to provide precise input parameters before executing a search. This architectural constraint ensures that tools like enrich_lead and get_company_intent only fire when the agent has high-quality inputs, resulting in:

  • Comprehensive Firmographics: Real-time retrieval of headcount, revenue brackets, and industry classification.
  • Deep Technographics: Identification of a target company’s current software stack and infrastructure.
  • Intent Signal Mapping: Analysis of recent hiring trends, news, and funding events to prioritize high-intent accounts.
  • Schema-First Validation: Every tool definition is strictly typed, preventing the LLM from passing "guessed" or malformed data into your sales pipeline.

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 MCP settings. This establishes a secure, persistent connection to the enrichment server.

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

When an agent invokes the enrich_lead tool, it receives a clean, structured payload. This response allows the agent to reason over the confidenceScore and intentSignals to determine if a lead is worth pursuing.

{
  "method": "tools/call",
  "params": {
    "name": "enrich_lead",
    "arguments": {
      "domain": "stripe.com"
    }
  },
  "result": {
    "companyName": "Stripe, Inc.",
    "industry": "Financial Services",
    "headcount": "7000+",
    "technographics": ["AWS", "React", "Ruby on Rails", "Kubernetes"],
    "intentSignals": [
      { "type": "expansion", "description": "New office opened in Dublin", "date": "2023-11-15" }
    ],
    "confidenceScore": 0.98,
    "status": "success"
  }
}
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Risk-Free Metered Billing for Production SDRs

Traditional B2B data providers charge heavy upfront fees or per-query rates regardless of data quality. This MCP server implements a Risk-Free Metered Billing model optimized for autonomous agents. You are only billed for successful enrichments that return a Confidence Score > 0.6. If the server returns low-quality data or fails to find a match, the cost of that query is $0. This allows you to build cost-effective SDR swarms that can scan thousands of domains without the risk of burning your budget on "No Results Found" errors.

Get Your Free B2B Enrichment API Key

Ready to ground your sales agents in real-time data? Visit lead-enrichment-mcp.agent-infra.workers.dev to generate your API key and access the free tier instantly.

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