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Leadenrich MCP

作者:carsonroell-debug版本 0.2.0i★ –i在你的电脑上运行
注册名称io.github.carsonroell-debug/leadenrich-mcp

安装

概览

作者提供的说明(英文原文)

Waterfall lead enrichment — cascades Apollo, Clearbit, and Hunter for max coverage

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

  • 连接方式: 在你的电脑上运行
  • 传输方式: stdio
  • 分类: 其他
  • 你需要填写:APOLLO_API_KEY, CLEARBIT_API_KEY, HUNTER_API_KEY

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

  • 基础检查:1 项中通过 1 项
  • 在你的电脑上运行,拥有你的用户账户的权限(文件、网络、应用)。
  • 需要你自己填写: APOLLO_API_KEY, CLEARBIT_API_KEY, HUNTER_API_KEY

标为机密的值是你账户的钥匙。千万不要分享给别人,也不要粘贴到聊天里。

你需要

  • PyPI已安装 Python 的 uv(用于 uvx 命令)

你用的是哪个应用?

在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。

打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json

{
  "mcpServers": {
    "leadenrich": {
      "command": "uvx",
      "args": [
        "leadenrich-mcp"
      ],
      "env": {
        "APOLLO_API_KEY": "your-value",
        "CLEARBIT_API_KEY": "your-value",
        "HUNTER_API_KEY": "your-value"
      }
    }
  }
}

在终端中运行这条命令

claude mcp add leadenrich --env APOLLO_API_KEY=your-value --env CLEARBIT_API_KEY=your-value --env HUNTER_API_KEY=your-value -- uvx leadenrich-mcp

运行前请先填写空着的值。

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "leadenrich": {
      "command": "uvx",
      "args": [
        "leadenrich-mcp"
      ],
      "env": {
        "APOLLO_API_KEY": "your-value",
        "CLEARBIT_API_KEY": "your-value",
        "HUNTER_API_KEY": "your-value"
      }
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "leadenrich": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "leadenrich-mcp"
      ],
      "env": {
        "APOLLO_API_KEY": "your-value",
        "CLEARBIT_API_KEY": "your-value",
        "HUNTER_API_KEY": "your-value"
      }
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。

你的选择通过 Cookie 保存在这台设备上,无需账户。

需要你填写的值

  • APOLLO_API_KEY 机密 env
    Apollo.io API key for lead enrichment
  • CLEARBIT_API_KEY 机密 env
    Clearbit API key for company/contact enrichment
  • HUNTER_API_KEY 机密 env
    Hunter.io API key for email finding

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。

它能做什么

它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。

基础检查i

我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月7日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 carsonroell-debug 验证,该账户拥有此仓库

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • – 不适用

    端点有响应

    它在你的电脑上运行,没有互联网端点

  • – 不适用

    使用 OAuth 登录

    在你的电脑上运行,改用本地设置

  • … 尚未检查

    工具描述中没有隐藏指令

    它在你的电脑上运行;我们只能读取互联网端点的工具列表

与“其他”中的其他服务器比较i

  • 星标数多于此分类中其他 32742 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 32742 个服务器的 6% 更新
  • 基础检查结果等于或优于此分类中其他 32742 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。

常见问题

Leadenrich MCP 安全吗?

它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。

它需要哪些密钥或代码?

你需要填写:APOLLO_API_KEY, CLEARBIT_API_KEY, HUNTER_API_KEY

它在我的电脑上运行还是在云端?

它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(0.2.0)于7个月前进入注册中心。

哪些应用可以使用它?

支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Python (uv)。

有什么可以替代它?

同一分类中有:Spec Driven Development, Remote Desktop Commander, Asset Notation

替代选择

同一分类中其他作者的服务器,按星标数排序。

如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

Spec Driven Development

作者:formulahendry

MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.

在你的电脑上运行★ 440MIT14个月前更新
安装

Remote Desktop Commander

作者:desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

在云端运行★ 211前天更新
安装

Asset Notation

作者:assetnotation

Read and maintain an Asset Notation file on disk: net worth, holdings, valuations, CSV import.

在你的电脑上运行今天更新
安装

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

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

ToolDescription
enrich_leadFull waterfall enrichment for a single lead (email, domain, or name+domain)
find_emailDiscover an email from first name + last name + company domain
enrich_companyCompany firmographic data by domain (industry, size, revenue, etc.)
enrich_batchBatch enrich up to 25 leads concurrently
check_usageQuota, cost tracking, and remaining lookups
health_checkServer status, configured providers, and cache stats

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

TierCostDetails
Free$0.0050 lookups/month
1 provider hit$0.05/lookupSingle provider returned data
2 providers hit$0.10/lookupTwo providers contributed fields
3 providers hit$0.15/lookupFull waterfall, maximum coverage

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

VariableDescriptionRequired
APOLLO_API_KEYApollo.io API keyNo
CLEARBIT_API_KEYClearbit API keyNo
HUNTER_API_KEYHunter.io API keyNo
LEADENRICH_API_KEYClient auth key for usage meteringNo
LEADENRICH_FREE_TIER_LIMITFree tier limit (default: 50)No
PORTServer port (default: 8300)No

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

ToolFreePro ($29/mo)
enrich_leadYes (Hunter only)Yes (full waterfall: Apollo + Clearbit + Hunter)
check_usageYesYes
health_checkYesYes
find_email-Yes
enrich_company-Yes
enrich_batch-Yes

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](https://mcpize.com/mcp/leadenrich-mcp?ref=YHCCR&utm_source=github&utm_medium=readme) — $29/mo or $290/yr.


Built by Freedom Engineers

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