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

All provider keys are optional. The server uses whichever providers are configured and skips the rest.

Example:

export APOLLO_API_KEY="your-apollo-key"
export CLEARBIT_API_KEY="your-clearbit-key"
export HUNTER_API_KEY="your-hunter-key"
python main.py

Running Options

Run directly:

python main.py

Run via FastMCP CLI:

fastmcp run main.py --transport streamable-http --port 8300

Tool Details

enrich_lead

Inputs:

• email (optional): Contact email address (best identifier)
• domain (optional): Company domain (e.g. "stripe.com")
• first_name / last_name (optional): Contact name (combine with domain)
• providers (optional): Limit which providers to use
• api_key (optional): Your LeadEnrich API key

Returns merged lead profile with field attribution, confidence score, and lookup cost.

find_email

Inputs:

• first_name (required): Contact's first name
• last_name (required): Contact's last name
• domain (required): Company domain

Returns discovered email with confidence score and verification status.

enrich_company

Input:

• domain (required): Company domain

Returns company-level firmographic data: industry, size, revenue, description, location.

enrich_batch

Inputs:

• leads (required): List of lead objects (max 25), each with optional email/domain/name
• providers (optional): Limit which providers to use
• api_key (optional): Your LeadEnrich API key

Returns list of enriched profiles with batch summary.

check_usage

Input:

• api_key (optional): Your LeadEnrich API key

Returns usage stats: lookup count, cost, tier, remaining quota, and cache stats.

health_check

No input. Returns server status, configured providers, cache stats, and version info.

Try It

fastmcp list-tools main.py
fastmcp call-tool main.py health_check '{}'
fastmcp call-tool main.py enrich_lead '{"email":"jane@stripe.com"}'
fastmcp call-tool main.py find_email '{"first_name":"Jane","last_name":"Smith","domain":"stripe.com"}'
fastmcp call-tool main.py enrich_company '{"domain":"stripe.com"}'

Deployment

Smithery

This repo includes smithery.yaml for Smithery deployment.

1. Push repository to GitHub
2. Create/add server in Smithery
3. Point Smithery to this repository

Docker / Hosting Platforms

A Dockerfile is included for Railway, Fly.io, and other container hosts.

# Railway
railway up

# Fly.io
fly launch
fly deploy

Set your provider API keys in your host environment.

Architecture

Agent (Claude, Cursor, etc.)
  -> MCP
LeadEnrich MCP Server (this repo)
  -> Apollo API    (contact + company data)
  -> Clearbit API  (person + firmographic data)
  -> Hunter API    (email finding + verification)

This server is a translation layer between MCP tool calls and multiple enrichment provider APIs, with built-in caching, usage metering, and waterfall merge logic.

Free vs Pro

Free tier gives you single-provider lookups via Hunter. Pro unlocks the full 3-provider waterfall, email finder, company enrichment, and batch operations.

Upgrade to Pro on MCPize — $29/mo or $290/yr.

Built by Freedom Engineers

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