LeadPipe MCP

AI-powered lead qualification engine for the Model Context Protocol

![License: MIT](LICENSE) ![TypeScript](https://www.typescriptlang.org/) ![MCP](https://modelcontextprotocol.io/)

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.

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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

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Quick Start

Install from MCPize Marketplace

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

Build from Source

git clone https://github.com/enzoemir1/leadpipe-mcp.git
cd leadpipe-mcp
npm ci
npm run build

Add to your MCP client config:

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

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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.

{}

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.

{
  "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.

{
  "email": "jane@acme.com",
  "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.

{
  "leads": [
    { "email": "lead1@corp.com", "job_title": "CEO" },
    { "email": "lead2@startup.io", "job_title": "CTO" }
  ]
}

lead_enrich

Enrich a lead with company data using the email domain.

{ "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.

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

Returns score + detailed breakdown across all 6 dimensions.

lead_search

Search and filter leads with pagination.

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

lead_export

Export leads to CRM or file format.

{
  "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.

{
  "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"
    }
  ]
}

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Resources

| Resource | Description | |----------|-------------| | leads://recent | The 50 most recently added leads | | leads://pipeline | Pipeline summary with status counts, scores, conversion rates | | leads://config | Current scoring engine configuration |

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Scoring Engine

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

| Dimension | Default Weight | How It Works | |-----------|---------------|--------------| | Job Title | 25% | C-level/Founder: 100, VP/Director: 85, Manager: 65, Senior: 50, Junior: 15 | | Company Size | 20% | Preferred sizes (11-50, 51-200, 201-500): 90, others scaled accordingly | | Industry | 20% | High-value industries (SaaS, fintech, etc.): 90, others: 40 | | Engagement | 15% | Phone provided, full name, tags, source type (landing page > CSV) | | Recency | 10% | Today: 100, last week: 75, last month: 35, 3+ months: 5 | | Custom Rules | 10% | 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.

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CRM Integration

HubSpot

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

export HUBSPOT_API_KEY="pat-xxx-xxx"

Pipedrive

Set the PIPEDRIVE_API_KEY environment variable.

export PIPEDRIVE_API_KEY="xxx"

CSV / JSON

No configuration needed. Export returns data directly.

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Enrichment

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

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

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Pricing

| Tier | Price | Tools | Features | |------|-------|-------|----------| | Free | €0 | lead_demo_seed, lead_ingest, lead_batch_ingest, lead_search, lead_score, config_scoring | Ingest, manual scoring, ICP pre-qualification | | Pro | €19 lifetime | + lead_qualify, lead_enrich, lead_export, pipeline_stats | AI 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.

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Development

npm run dev        # Hot reload development
npm run build      # Production build
npm test           # Run unit tests
npm run inspect    # Open MCP Inspector

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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:

export LEMONSQUEEZY_LICENSE_KEY=YOUR-KEY-HERE

Or in your Claude Desktop / MCP client config:

{
  "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.

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License

MIT License. See LICENSE for details.

Built by Automatia BCN.

leadpipe-mcp