Nyc Property Intel MCP server

NYC Property Intel

MCP server that gives Claude AI access to 20+ NYC public record datasets for real estate due diligence. Ask Claude about any NYC property in plain English — violations, liens, sales history, ownership, permits, rent stabilization, zoning, fire history, crime data, and more.

This is a due diligence tool, not an appraisal tool. It surfaces public record data only; it does not estimate property values.

Quickstart — Web Chat (no setup)

The fastest way to try it: open nycpropertyintel.com/chat and ask about any NYC property in plain English. 3 free queries, no signup — no install, no token, and no Claude client needed.

"What violations does 123 Atlantic Ave, Brooklyn have?"

Free guides & lookups

• NYC Property Due Diligence Checklist — the complete pre-offer checklist across 20+ city data sources
• NYC HPD Violations Lookup — Class A/B/C breakdown by address
• NYC DOB & ECB Violations Lookup — open violations, ECB penalties, Local Law 153 lien risk
• NYC Property Owner Lookup — the owner and HPD contacts behind an LLC
• NYC Eviction History by Address — City Marshal executed evictions, 2017–present
• Check If You Have an Eviction on Your Record (NYC) — tenant-facing guide to court records, screening files, and your rights

Quickstart — Claude Code / Desktop (hosted MCP)

Sign up at nycpropertyintel.com to get a free trial token (10 queries/day for 30 days, including up to 5 full due-diligence reports). Then:

Claude Code — run once in your terminal:

claude mcp add --transport http nyc-property-intel \
  "https://nyc-property-intel-production.up.railway.app/mcp" \
  --header "Authorization: Bearer YOUR_TOKEN" \
  --scope user

Claude Desktop — add to claudedesktopconfig.json (Settings → Developer → Edit Config):

{
  "mcpServers": {
    "nyc-property-intel": {
      "type": "http",
      "url": "https://nyc-property-intel-production.up.railway.app/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_TOKEN"
      }
    }
  }
}

Then ask Claude:

"Look up 350 5th Ave, Manhattan"
"What violations does 123 Atlantic Ave, Brooklyn have?"
"Full due diligence on 123 Atlantic Ave, Brooklyn"

Self-Hosting

Prerequisites

• Python 3.12+
• uv package manager
• PostgreSQL 16+
• nycdb CLI (pip install nycdb)

1. Clone and install

git clone https://github.com/ccedacero/nyc-property-intel.git
cd nyc-property-intel
uv sync

2. Configure environment

cp .env.example .env
# Edit .env:
#   DATABASE_URL=postgresql://nycdb:nycdb@localhost:5432/nycdb
#   NYC_GEOCLIENT_SUBSCRIPTION_KEY=your_key  (optional, improves address resolution)
#   SOCRATA_APP_TOKEN=your_token             (optional, higher rate limits for 311/FDNY/NYPD)

3. Set up the database

Option A: Restore from dump (~10 min)

createuser -s nycdb 2>/dev/null; createdb -O nycdb nycdb 2>/dev/null
pg_restore -U nycdb -d nycdb --no-owner --jobs=4 data/nycdb.dump

Option B: Load from source (~2.5 hours)

createuser -s nycdb 2>/dev/null; createdb -O nycdb nycdb 2>/dev/null
chmod +x scripts/seed_nycdb.sh
./scripts/seed_nycdb.sh              # all phases
# or incrementally:
./scripts/seed_nycdb.sh --phase A    # core data (~30 min)
./scripts/seed_nycdb.sh --phase B    # sales + DOB (~45 min)
./scripts/seed_nycdb.sh --phase C    # ACRIS + permits (~90 min)

Then create indexes and materialized views:

Shortened. The full README is on GitHub.