Pipes raw leads through AI qualification without burning enrichment credits. The ICP filter checks job titles, company size, country, and tech stack before you hit Hunter.io or your CRM API limits. Once a lead passes, it scores 0-100 across six weighted dimensions (title, industry, company size, engagement, recency, custom rules), then exports qualified contacts to HubSpot or Pipedrive. The pre-qualification tool is the standout here: it catches freemail domains and wrong-fit titles before you waste API calls. Useful if you're running inbound forms or CSV imports and need to triage volume before enrichment. Includes pipeline analytics and batch ingestion up to 100 leads at once. Pro features require a LemonSqueezy license.
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.
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"]
}
}
}
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.
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.
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"]
}
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" }
]
}
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.
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.
Search and filter leads with pagination.
{
"query": "acme",
"status": "qualified",
"min_score": 60,
"limit": 20,
"offset": 0
}
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.
Get pipeline analytics. No input required.
Returns: total leads, status/source breakdown, average score, score distribution, qualified rate, leads today/week/month.
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"
}
]
}
| 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 |
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.
Set the HUBSPOT_API_KEY environment variable with your HubSpot private app access token.
export HUBSPOT_API_KEY="pat-xxx-xxx"
Set the PIPEDRIVE_API_KEY environment variable.
export PIPEDRIVE_API_KEY="xxx"
No configuration needed. Export returns data directly.
LeadPipe extracts the domain from the lead's email and looks up company data:
HUNTER_API_KEY is set) — returns organization, industry, country, tech stack| 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.
npm run dev # Hot reload development
npm run build # Production build
npm test # Run unit tests
npm run inspect # Open MCP Inspector
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 analyticsBuy 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.
MIT License. See LICENSE for details.
Built by Automatia BCN.
explorium-ai/vibeprospecting-mcp
io.github.compuute/lead-enrichment
dev.workers.selbyventurecap.cf-worker/apollo-salesforce-mapper
io.github.br0ski777/company-enrichment
com.mcparmory/apollo
mambalabsdev/mcp-gtm-tech-stack-signal-scraper