72BPM Lead-Gen MCP Server

An MCP server that turns discovery → enrichment → scoring → outreach into callable tools, scoped to 72BPM's four practice areas:

• SaaS Product Development
• E-mobility (EV) Applications & Infrastructure
• IoT Platforms
• AI Agent Creation

Why no LinkedIn API/scraper?

LinkedIn's Terms of Service prohibit automated scraping, and LinkedIn actively detects and blocks it — both technically (rate limits, IP bans) and legally. Rather than build something that breaks on day one and creates legal exposure, this server:

• Crawls companies' own public websites directly (careers pages, blog posts, about pages) — fully fair game, standard practice.
• Uses a real search engine (Brave Search API) to read back publicly indexed snippets — including of LinkedIn company/people pages — the same way a human researcher googling site:linkedin.com/company acme would. This is a search-engine query, not a scrape of linkedin.com itself.
• Reads public job postings the same way.

If your team later gets access to LinkedIn's official Talent/Sales Navigator API (via their Partner Program) or a compliant data provider, swap src/services/searchProvider.ts — every tool depends only on that one file's webSearch() function.

Tools

Tool	Purpose
leadgen_discover_companies	Search-based candidate discovery for one category + region
leadgen_enrich_company	Crawl a company's site + indexed LinkedIn/job signal, matched against all 4 categories
leadgen_score_lead	Weighted 0-100 fit score + tier (hot/warm/cold) + confidence for one category
leadgen_find_contact	Search-based candidate engineering contact (CTO/VP Eng/etc.) — unverified, always double-check before outreach
leadgen_generate_pitch	Drafts 2 outreach email variants using the value-lead framework
leadgen_save_lead / leadgen_list_leads / leadgen_update_lead	Simple pipeline tracking (JSON file by default)

Typical workflow: discover → enrich → score → find_contact → generate_pitch → save_lead, then update_lead as deals progress.

Setup

npm install
cp .env.example .env
# edit .env and set BRAVE_API_KEY (free tier: https://brave.com/search/api/)
npm run build

Run locally (stdio) — for Claude Desktop / Claude Code

npm start

Add to your Claude Desktop / Claude Code MCP config:

{
  "mcpServers": {
    "72bpm-leadgen": {
      "command": "node",
      "args": ["/absolute/path/to/72bpm-leadgen-mcp-server/dist/index.js"],
      "env": {
        "BRAVE_API_KEY": "your-key-here"
      }
    }
  }
}

Run as a hosted server (streamable HTTP) — for team-wide access

TRANSPORT=http PORT=3000 npm start
# or: npm run start:http

Exposes POST /mcp (the MCP endpoint) and GET /health. Point your team's MCP clients at https://your-host/mcp. Deploy behind your normal reverse proxy/TLS termination — this server does not handle auth itself, so put it behind your existing auth layer if exposing it beyond your VPN.

Customizing the ICP signals

src/constants.ts holds the weighted signal dictionary per category (ICP_SIGNALS). These are the phrases the scoring engine looks for and how many points each is worth. Tune them as you learn what actually converts — e.g. if "battery swapping" mentions never turn into real deals, drop its weight; if a new signal phrase keeps showing up in your best deals, add it.

Tier thresholds (tierFromScore) and confidence thresholds (confidenceFromSourceCount) live in the same file.

Customizing outreach voice

src/tools/pitch.ts has one AUTHORITY_LINES entry per category — the "parallel domain authority" sentence 72BPM's pitches lean on. Edit these to match your team's actual case studies as they accumulate; specific, verifiable claims outperform generic ones.

Known limitations (by design, not oversights)

• No paid enrichment APIs (Apollo/Clearbit/Crunchbase/BuiltWith) — you said you don't have those yet. The signal quality here is real but bounded by what's publicly crawlable. If you add API keys later, this is the natural next upgrade — add a new services/ client and feed its text into matchSignals() alongside the site crawl.
• Contact finding is unverified — leadgen_find_contact parses search snippet text, which is sometimes ambiguous. It's a research shortcut, not a verified contact database. Always confirm before sending outreach.
• Pipeline storage is a JSON file — fine for one person or a small team running the stdio server locally. For the hosted HTTP deployment with multiple concurrent users, swap src/services/storage.ts for a real database (Postgres/SQLite) — every other tool only depends on the four functions that file exports.
• Brave Search rate limits apply — the free tier is fine for exploration but will need a paid tier for high-volume prospecting.

Project structure

src/
├── index.ts              # Entry point, dual transport (stdio/HTTP)
├── constants.ts           # ICP signal weights, category labels, thresholds
├── types.ts                # Shared TypeScript types
├── services/
│   ├── searchProvider.ts   # Brave Search API wrapper (swap for another provider here)
│   ├── webCrawler.ts        # Company-site crawler (robots.txt-aware)
│   ├── companyIntel.ts       # Combines crawl + search into cached text bundles
│   ├── scoring.ts             # Weighted signal matching + scoring
│   └── storage.ts              # JSON-file lead pipeline (swap for a DB for hosted use)
└── tools/
    ├── discover.ts
    ├── enrich.ts
    ├── score.ts
    ├── contact.ts
    ├── pitch.ts
    └── pipeline.ts