LeadEnrich MCP Server

Waterfall lead enrichment for AI agents. Cascades through Apollo, Clearbit, and Hunter to build the most complete lead profile in a single call.

One-click install: Install on MCPize | pip install leadenrich-mcp

LeadEnrich MCP exposes lead and company enrichment through the Model Context Protocol (MCP), so tools like Claude and Cursor can run enrichment workflows directly. Give it an email, domain, or name and it returns a merged profile with field attribution showing which provider contributed each data point.

Quick Connect

1. Install and start the server

pip install leadenrich-mcp
leadenrich-mcp

The server starts on http://localhost:8300/mcp by default.

2a. Connect from Claude Desktop

Add to claude_desktop_config.json:

{
  "mcpServers": {
    "leadenrich": {
      "url": "http://localhost:8300/mcp"
    }
  }
}

2b. Connect from Claude Code

claude mcp add leadenrich --transport http http://localhost:8300/mcp

Tools

How It Works

LeadEnrich uses a waterfall strategy: each provider fills gaps left by the previous one. When email is known, all providers run concurrently for speed. When only name+domain is provided, Apollo discovers the email first, then Clearbit and Hunter run in parallel.

Input (email / domain / name+domain)
         |
         v
  +-----------+     +-----------+     +----------+
  |   Apollo  | --> |  Clearbit | --> |  Hunter  |
  +-----------+     +-----------+     +----------+
  |  Contact  |     |  Company  |     |  Email   |
  |  Company  |     |  Person   |     |  Verify  |
  |  LinkedIn |     |  Firmo    |     |  Domain  |
  +-----------+     +-----------+     +----------+
         |               |                |
         v               v                v
  +------------------------------------------+
  |        Merged Profile                    |
  |  16+ fields with per-field attribution   |
  |  Confidence score + lookup cost          |
  +------------------------------------------+

Each field in the result includes attribution so you know exactly which provider it came from. No duplicate API calls thanks to built-in caching.

Pricing

Requirements

• Python 3.11+
• pip

Quick Start

git clone https://github.com/carsonlabs/leadenrich-mcp.git
cd leadenrich-mcp
pip install -r requirements.txt
python main.py

MCP endpoint:

• http://localhost:8300/mcp

Environment Variables

|

... View full README on GitHub