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Diego Costa
Diego Costa

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Building Cost-Effective Autonomous SDR Swarms with Metered B2B Lead Enrichment MCP

#mcp #ai #automation

Building Cost-Effective Autonomous SDR Swarms with Metered B2B Lead Enrichment MCP

Scaling autonomous SDR swarms requires an MCP-native infrastructure that provides LLMs with direct, real-time access to B2B firmographics and intent data without the latency of custom middleware. By integrating a B2B lead enrichment MCP server, developers can deploy cost-effective agentic workflows that utilize risk-free metered billing, ensuring compute and data costs only accrue for high-confidence lead enrichments.

Core Features

The B2B Lead Enrichment MCP server bridges the gap between static LLM knowledge and the dynamic corporate landscape. By exposing structured tools directly to the Model Context Protocol, AI agents can perform deep research tasks with zero-shot accuracy.

  • Firmographic & Technographic Data: Retrieve real-time data on company revenue, headcount, industry classification, and the specific software stack (SaaS, Cloud Infrastructure, CRM) used by a target.
  • Intent Signal Detection: Identify high-propensity buying signals such as recent funding rounds, executive leadership changes, and active hiring trends directly within the agent's context.
  • Zod-Validated Parameter Safety: To eliminate LLM hallucinations and invalid API calls, every tool in this MCP server uses strict Zod schema annotations, forcing the model to adhere to precise json-rpc specifications.
  • Confidence-Driven Reliability: Every enrichment returns a confidenceScore (0.0 - 1.0), allowing agents to autonomously decide whether to proceed with a lead or seek further verification.

Implementation: Claude Desktop & Cursor Configuration

To give your AI agent or IDE immediate access to live B2B data, add the following configuration to your claude_desktop_config.json or Cursor's MCP settings. This connects your environment to the production-ready MCP endpoint.

{
  "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_HERE"
      }
    }
  }
}
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JSON-RPC Response: enrich_lead Payload

When an agent invokes the enrich_lead tool, the MCP server returns a clean, structured JSON object designed for immediate LLM consumption and decision-making.

{
  "method": "tools/call",
  "params": {
    "name": "enrich_lead",
    "arguments": {
      "domain": "stripe.com"
    }
  },
  "result": {
    "content": [
      {
        "type": "text",
        "text": {
          "companyName": "Stripe, Inc.",
          "industry": "Fintech / Payments",
          "headcount": "7000+",
          "technographics": ["AWS", "React", "Ruby", "Salesforce"],
          "intentSignals": ["High: Expanding enterprise sales team", "Recent: New payment orchestration product"],
          "confidenceScore": 0.98,
          "isMetered": true
        }
      }
    ]
  }
}
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Risk-Free Metered Billing for AI Workflows

The primary bottleneck for autonomous SDR swarms is the cost of "hallucinated" or "low-quality" data queries. This MCP server implements a Risk-Free Metered Billing model. Instead of paying for every request, you are only billed for successful enrichments where the confidenceScore is greater than 0.6.

If the server cannot find a high-quality match or the data is fragmented, the query is marked as "low quality" and costs $0. This allows developers to loop through thousands of domains and prospects in an autonomous swarm without the risk of burning through budgets on failed lookups.

Get Your Free B2B Enrichment API Key

Ready to upgrade your AI agents from static text predictors to live B2B intelligence engines? Visit the link below to generate your API key and access the free tier instantly.

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

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