Leadpipe Mcp

io.github.enzoemir1Published by GitHub account enzoemir1v1.4.0Updated Oct 24, 2026

AI lead qualification: ICP filter, 0-100 scoring, Hunter.io enrichment, HubSpot/Pipedrive export.

VerifiedSTDIODesktop onlyData & AnalyticsBusiness & Commerce

Overview

AI-generated overview

A local MCP server that ingests leads, enriches company data, scores prospects 0-100 against an ICP, and exports qualified leads to HubSpot, Pipedrive, CSV or a

What you can do
Ingest single leads or batches of up to 100, with duplicates skipped, and seed a demo dataset for testing without API keys. Filter leads against an ideal customer profile using local signals such as email domain, title, country, industry and tech stack before spending enrichment credits. Enrich leads with company name, industry, size, country, tech stack and LinkedIn URL from the email domain. Score leads 0-100 across six weighted dimensions with custom rules, and search or filter the pipeline with pagination. Export qualified leads to HubSpot, Pipedrive, CSV or JSON, and read pipeline analytics plus recent leads, pipeline summary and scoring configuration as resources.
When to use it
Useful when a sales or marketing workflow needs an assistant to triage inbound leads, apply a consistent qualification score, and push only qualified contacts into a CRM. Also handy for prototyping lead pipelines with the demo dataset before connecting real data.
Requirements
Runs as a local Node.js process (npm package leadpipe-mcp-server, started with node). Optional environment variables HUNTER_API_KEY for enrichment, HUBSPOT_API_KEY for HubSpot export and PIPEDRIVE_API_KEY for Pipedrive export; CSV and JSON export need no configuration. A paid Pro license (€19 lifetime, 3 machines) is required for lead_qualify, lead_enrich, lead_export and pipeline_stats.
Before you install
Lead data, including names, emails and job titles, is sent to Hunter.io when HUNTER_API_KEY is set, and to HubSpot or Pipedrive on export. Export writes contacts into your CRM. The Pro tier is a one-time €19 purchase; enrichment calls may consume Hunter.io credits, which the ICP filter is designed to reduce. The demo seed appends new leads on every call.

Installation

In SourceWeft

  1. Open Leadpipe Mcp in the dashboard and add it to a workspace.
  2. Enable the server for the chats that should use its tools.

Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.

Other MCP clients

Follow the launch instructions in the repository.

README

LeadPipe MCP

AI-powered lead qualification engine for the Model Context Protocol

[License: MIT] [TypeScript] [MCP]

LeadPipe ingests leads from any source, enriches them with company data, scores them 0-100 using configurable AI rules, and exports qualified leads to your CRM — all through the MCP protocol.


Features

  • Lead ingestion from webhooks, forms, APIs, or CSV — single or batch (up to 100)
  • Auto-enrichment with company data: industry, size, country, tech stack (via Hunter.io or domain heuristics)
  • AI scoring engine (0-100) with 6 weighted dimensions + custom rules
  • CRM export to HubSpot, Pipedrive, CSV, or JSON
  • ICP pre-qualification to filter leads on freemail/title/country/tech-stack before spending a single enrichment credit
  • Pipeline analytics with real-time stats, score distribution, conversion rates
  • Configurable scoring weights, high-value titles/industries, custom rules
  • 10 MCP tools + 3 MCP resources covering the full lead lifecycle

Quick Start

Install from MCPize Marketplace

  1. Search for LeadPipe MCP on mcpize.com
  2. Click Install and select your subscription tier
  3. Tools and resources are automatically available in any MCP-compatible client (Cursor, VS Code, etc.)

Build from Source

bash
git clone https://github.com/enzoemir1/leadpipe-mcp.gitcd leadpipe-mcpnpm cinpm run build

Add to your MCP client config:

json
{  "mcpServers": {    "leadpipe": {      "command": "node",      "args": ["path/to/leadpipe-mcp/dist/index.js"]    }  }}

Tools

lead_demo_seed

Seed the pipeline with a realistic demo dataset — 14 leads across 5 archetypes (hot decision-makers, warm mid-level, cold junior/small-co, raw unenriched, and disqualified) — so every downstream tool returns meaningful output without any API keys. Safe to call multiple times; each call appends a fresh batch with new UUIDs.

json
{}

Returns: counts by status plus sample_lead_ids you can feed into lead_enrich, lead_score, or lead_export.

lead_qualify

Filter leads against your Ideal Customer Profile before spending any enrichment credits. Uses only locally-available signals — email domain, job title, country, industry, company size, tech stack — so nothing is charged to Hunter.io, HubSpot, or Pipedrive.

json
{  "criteria": {    "reject_freemail": true,    "required_title_keywords": ["vp", "director", "head", "founder"],    "target_countries": ["US", "CA", "GB"],    "min_company_size": "11-50",    "required_tech_stack": ["shopify"]  },  "auto_disqualify": true}

Returns per-lead qualified/rejected decisions with reasons and an estimated credit savings figure.

Pairs well with platform detection tools. If you chain a tool like Detecto (detect_platform) before lead_qualify, the detected tech stack populates company.tech_stack, and required_tech_stack can drop wrong-platform leads before they ever reach enrichment or scoring.

lead_ingest

Add a single lead to the pipeline.

json
{  "email": "[email protected]",  "first_name": "Jane",  "last_name": "Smith",  "job_title": "VP of Engineering",  "company_name": "Acme Corp",  "company_domain": "acme.com",  "source": "website_form",  "tags": ["demo-request"]}

lead_batch_ingest

Add 1-100 leads at once. Duplicates are automatically skipped.

json
{  "leads": [    { "email": "[email protected]", "job_title": "CEO" },    { "email": "[email protected]", "job_title": "CTO" }  ]}

lead_enrich

Enrich a lead with company data using the email domain.

json
{ "lead_id": "uuid-of-lead" }

Returns: company name, industry, size, country, tech stack, LinkedIn URL.

lead_score

Calculate a qualification score (0-100). Leads scoring 60+ are marked qualified.

json
{ "lead_id": "uuid-of-lead" }

Returns score + detailed breakdown across all 6 dimensions.

lead_search

Search and filter leads with pagination.

json
{  "query": "acme",  "status": "qualified",  "min_score": 60,  "limit": 20,  "offset": 0}

lead_export

Export leads to CRM or file format.

json
{  "target": "hubspot",  "min_score": 60}

Targets: hubspot, pipedrive, csv, json

Google Sheets export is on the roadmap. Currently returns Sheets-ready formatted data.

pipeline_stats

Get pipeline analytics. No input required.

Returns: total leads, status/source breakdown, average score, score distribution, qualified rate, leads today/week/month.

config_scoring

View or update scoring configuration.

json
{  "job_title_weight": 0.30,  "high_value_titles": ["ceo", "cto", "vp", "founder"],  "custom_rules": [    {      "field": "company_industry",      "operator": "equals",      "value": "fintech",      "points": 15,      "description": "Bonus for fintech companies"    }  ]}

Resources

ResourceDescription
leads://recentThe 50 most recently added leads
leads://pipelinePipeline summary with status counts, scores, conversion rates
leads://configCurrent scoring engine configuration

Scoring Engine

Leads are scored 0-100 using a weighted average of 6 dimensions:

DimensionDefault WeightHow It Works
Job Title25%C-level/Founder: 100, VP/Director: 85, Manager: 65, Senior: 50, Junior: 15
Company Size20%Preferred sizes (11-50, 51-200, 201-500): 90, others scaled accordingly
Industry20%High-value industries (SaaS, fintech, etc.): 90, others: 40
Engagement15%Phone provided, full name, tags, source type (landing page > CSV)
Recency10%Today: 100, last week: 75, last month: 35, 3+ months: 5
Custom Rules10%User-defined rules with -50 to +50 points each

Formula: score = sum(dimension_score * weight)

Leads with score >= 60 are qualified. Below 60 are disqualified.


CRM Integration

HubSpot

Set the HUBSPOT_API_KEY environment variable with your HubSpot private app access token.

bash
export HUBSPOT_API_KEY="pat-xxx-xxx"

Pipedrive

Set the PIPEDRIVE_API_KEY environment variable.

bash
export PIPEDRIVE_API_KEY="xxx"

CSV / JSON

No configuration needed. Export returns data directly.


Enrichment

LeadPipe extracts the domain from the lead's email and looks up company data:

  1. Hunter.io (if HUNTER_API_KEY is set) — returns organization, industry, country, tech stack
  2. Domain heuristics — maps known domains to company data
  3. Freemail detection — gmail.com, yahoo.com, etc. are flagged (no company enrichment)

Pricing

TierPriceToolsFeatures
Free€0lead_demo_seed, lead_ingest, lead_batch_ingest, lead_search, lead_score, config_scoringIngest, manual scoring, ICP pre-qualification
Pro€19 lifetime+ lead_qualify, lead_enrich, lead_export, pipeline_statsAI scoring, Hunter.io enrichment, CRM export, pipeline analytics

One-time €19 lifetime license (3 machines) — no subscription. See Pro License below to buy and activate.


Development

bash
npm run dev        # Hot reload developmentnpm run build      # Production buildnpm test           # Run unit testsnpm run inspect    # Open MCP Inspector

Pro License

LeadPipe ships in Free mode — lead_demo_seed, lead_ingest, lead_batch_ingest, lead_search, lead_score, and config_scoring are open. The following tools require a Pro license:

  • lead_qualify — ICP pre-filter
  • lead_enrich — domain knowledge-base enrichment
  • lead_export — HubSpot / Pipedrive / Google Sheets / CSV / JSON
  • pipeline_stats — portfolio analytics

Buy a Pro License (€19, lifetime, 3 machines): https://automatiabcn.lemonsqueezy.com/buy/360565a3-2577-45e2-93dd-1548a881f456

Or get the Indie MCP Stack Bundle (€69, all 4 servers).

Then activate by setting the env var:

bash
export LEMONSQUEEZY_LICENSE_KEY=YOUR-KEY-HERE

Or in your Claude Desktop / MCP client config:

json
{  "mcpServers": {    "leadpipe-mcp": {      "command": "npx",      "args": ["-y", "leadpipe-mcp-server"],      "env": { "LEMONSQUEEZY_LICENSE_KEY": "YOUR-KEY-HERE" }    }  }}

Validation is cached locally for 24 h, so the server is fully offline-capable after the first run.


License

MIT License. See LICENSE for details.

Built by Automatia BCN.

Source: README.md at commit a0f71ff

Tools

0
SourceWeft has not started this package in its sandbox yet, so its tools are not known.

Version history

1
  1. v1.4.0LatestSep 16, 2026

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