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
• Pipeline analytics with real-time stats, score distribution, conversion rates
• Configurable scoring weights, high-value titles/industries, custom rules
• 8 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

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_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:

... View full README on GitHub