Autonomous B2B Lead Generation with Python and Model Context Protocol (MCP)

Finding high-intent B2B distributors, suppliers, and verified contact emails typically means spending hundreds of dollars a month on SaaS databases like Apollo or ZoomInfo.

To automate this workflow locally, I created LeadDirect-MCP — an open-source Model Context Protocol server that turns Claude or Cursor into an autonomous outbound lead hunter.

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Why Use MCP for Lead Generation?

The Model Context Protocol (MCP) connects LLMs directly to custom scrapers, live search engines, and verification tools without complex third-party infrastructure.

With LeadDirect, your AI agent can:

• Discover Distributors & Partners: Perform multi-query web crawling across specific geographic territories.
• Extract Verified Contacts: Parse corporate websites for decision-maker titles (Procurement, Managing Director, Head of Sales) and direct email addresses.
• Verify Deliverability: Run MX record lookups and syntax verification to prevent email bounces.
• Export Clean Datasets: Output structured lead lists ready for CRM import or outbound sequences.

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Complete Outbound Suite

LeadDirect is part of a 3-tool autonomous ecosystem:

1. JobsDirect: Multi-portal job discovery & ATS fit evaluation.
2. LeadDirect: B2B lead generation & contact enrichment.
3. ReachDirect: Multi-channel outreach via Brevo Transactional Email & WhatsApp Web.

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Getting Started

git clone https://github.com/netizen4-bit/leaddirect-mcp.git
cd leaddirect-mcp
pip install -r requirements.txt

Plug it into your MCP client config and command your AI:

"Find 10 industrial automation equipment distributors in Germany with contact details and verify their emails."

⭐ GitHub Repository:
👉 https://github.com/netizen4-bit/leaddirect-mcp