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AI lead qualification: ICP filter, 0-100 scoring, Hunter.io enrichment, HubSpot/Pipedrive export.
About
AI lead qualification: ICP filter, 0-100 scoring, Hunter.io enrichment, HubSpot/Pipedrive export.
Security Report
Valid MCP server (1 strong, 1 medium validity signals). No known CVEs in dependencies. Package registry verified. Imported from the Official MCP Registry. Trust signals: trusted author (4/4 approved).
3 files analyzed · 1 issue found
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How to Install
Add this to your MCP configuration file:
{
"mcpServers": {
"io-github-enzoemir1-leadpipe-mcp": {
"args": [
"-y",
"leadpipe-mcp-server"
],
"command": "npx"
}
}
}Documentation
View on GitHubFrom the project's GitHub README.
LeadPipe MCP
AI-powered lead qualification engine for the Model Context Protocol
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
- 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"]
}
}
}
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) beforelead_qualify, the detected tech stack populatescompany.tech_stack, andrequired_tech_stackcan 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"
}
]
}
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 |
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.
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.
Enrichment
LeadPipe extracts the domain from the lead's email and looks up company data:
- Hunter.io (if
HUNTER_API_KEYis 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)
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.
Development
npm run dev # Hot reload development
npm run build # Production build
npm test # Run unit tests
npm 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-filterlead_enrich— domain knowledge-base enrichmentlead_export— HubSpot / Pipedrive / Google Sheets / CSV / JSONpipeline_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.
License
MIT License. See LICENSE for details.
Built by Automatia BCN.
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