BizIntel MCP

BizIntel MCP

Provides real-time website audits, lead scoring, tech-stack detection, and local-business search for AI agents doing sales outreach and competitor research.

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BizIntel MCP — Local Business Intelligence for AI Agents

Real-time website audits, lead scoring, tech-stack detection, and local-business search — exposed as an MCP server. Built for AI agents doing sales outreach, competitor research, and prospecting at scale.


MCPize Listing Copy

Title: BizIntel MCP — Real-Time Local Business Intelligence

Subtitle: Audit any website, score leads, find businesses with no booking system. Pay per call.

Description (2 paragraphs):

BizIntel is a paid MCP server that gives AI agents instant access to the kind of local-business intelligence sales teams used to pay analysts to gather. One call to audit_website returns a 0-100 score across SSL, mobile-readiness, page speed, contact form presence, and online booking — plus a tech-stack fingerprint (CMS, booking platform, email provider, analytics). Agents pointed at "find dentists in Austin with no booking system" get a ranked, contactable list in seconds, not hours.

The MCP exposes eight tools — audit_website, bulk_audit, search_businesses, get_business_details, score_lead, find_no_website, find_no_booking, get_tech_stack — backed by Yelp Fusion (or OSM/Overpass when no Yelp key is provided), an aiohttp scanner running 10 concurrent fetches, and a 24-hour SQLite cache so repeat calls don't burn quota. Drop it into Claude Desktop, Cursor, or any agent and your prospecting pipeline becomes one tool call wide.


Pricing

Tier Price Limits
Free / Dev $0 20 calls / 24h
Pro $19/mo Unlimited
Pay-as-you-go $0.05/call No floor

Upgrade: https://mcpize.com/bizintel-mcp


Tools

Tool Args Returns
audit_website url Score 0-100, SSL, HTTPS redirect, viewport, load_time_ms, contact form, booking, tech_stack
search_businesses niche, city, state, limit List of normalized business records
get_business_details business_name, city Full record: phone, address, website, hours, rating, lat/lon
bulk_audit urls (≤20) Audit results sorted worst→best (best leads first)
score_lead business_name, city, niche Composite 0-100 lead score with breakdown
find_no_website niche, city, state, limit Hottest cold-outreach leads — ranked
find_no_booking niche, city, state, limit Have a site, no online booking — SaaS-pitch ready
get_tech_stack url CMS / booking / email / analytics fingerprint

Quickstart

Add to Claude Desktop / Claude Code

claude mcp add bizintel-mcp --url https://mcp-bizintel.up.railway.app/mcp

Set your API key in the MCP config (header X-API-Key). The default dev key bizintel-dev-key-001 is good for 20 calls per day.

Direct HTTP

curl -X POST https://mcp-bizintel.up.railway.app/v1/find_no_booking \
  -H "X-API-Key: bizintel-dev-key-001" \
  -H "Content-Type: application/json" \
  -d '{"niche":"dentist","city":"Austin","state":"TX","limit":10}'

Example agent prompt

Find dentists in Austin with no booking system, audit the top 5, and write a one-line cold-email opener for each that references their actual tech stack.


Local Dev

pip install -r requirements.txt
cp .env.example .env  # fill in YELP_API_KEY (optional)
python -m uvicorn server:app --reload --port 8000
pytest -v

Without a Yelp key, search/details fall back to OSM (Nominatim + Overpass). Coverage is sparser but free.


Deploy

bash deploy.sh from Brett's Mac — pulls secrets from the shared workspace .deploy-secrets.env, links/initializes the Railway project, sets env vars, and runs railway up. Pre-deploy pytest is part of the script so you can't ship a broken build.


Architecture

server.py                FastAPI + fastmcp; HTTP at /v1/* and MCP at /mcp
tools/audit.py           Async aiohttp auditor (10 concurrent, 5s timeout)
tools/techstack.py       CMS / booking / email / analytics fingerprints
tools/search.py          Yelp Fusion primary, OSM Overpass fallback
tools/scoring.py         Composite lead score (0-100)
db/cache.py              SQLite cache + per-key call ledger
db/keys.py               Tier classification + 24h sliding window
nixpacks.toml            Railway build config

Caching: audits cached 6h, business details 24h, search results 12h. The cache is a single SQLite file with WAL mode — no Redis needed for the price point.


Known Limitations

  1. Yelp doesn't expose external website URL in /businesses/search. We return yelp_url as a stable handle; for a real domain, agents should chain get_business_details (returns hours/photos) and follow the Yelp page or use find_no_website (where OSM-tagged sites are surfaced).
  2. OSM coverage is uneven — some niches map cleanly (dentist, restaurant); long-tail US small business categories (pickleball coach, yacht detailer) won't resolve.
  3. No headless rendering — JS-heavy sites that gate content behind hydration won't expose contact/booking signals to the audit. This is intentional; we trade completeness for 5-second batched audits.
  4. Tech-stack detection is signature-based, not Wappalyzer-grade. We catch the common 90% (WP, Wix, Shopify, Squarespace, Calendly, Mindbody, GA4, Klaviyo) — not obscure custom stacks.
  5. Rate-limit window is sliding 24h, stored per-API-key in SQLite. Restart the container and the ledger persists; clear the DB to reset all dev quotas.

License

Proprietary — © 2026.

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