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.

Code

"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:

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 claude_desktop_config.json (Settings → Developer → Edit Config):

config.json

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

Then ask Claude:

Code

"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

bash

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

2. Configure environment

bash

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)

bash

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)

bash

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:

bash

psql -U nycdb -d nycdb -f scripts/create_indexes.sql
psql -U nycdb -d nycdb -f scripts/create_views.sql

4. Add to Claude Desktop

config.json

{
  "mcpServers": {
    "nyc-property-intel": {
      "command": "uv",
      "args": ["run", "nyc-property-intel"],
      "cwd": "/absolute/path/to/nyc-property-intel",
      "env": {
        "DATABASE_URL": "postgresql://nycdb:nycdb@localhost:5432/nycdb"
      }
    }
  }
}

5. Add to Claude Code

The .mcp.json in the project root auto-registers when you open this directory. Or add manually to ~/.claude.json:

config.json

{
  "mcpServers": {
    "nyc-property-intel": {
      "command": "uv",
      "args": ["run", "nyc-property-intel"],
      "cwd": "/absolute/path/to/nyc-property-intel"
    }
  }
}

18 Tools

Tool	Description
`lookup_property`	Resolve any NYC address or BBL to a full property profile: owner, building class, zoning, FAR, assessed value, lot dimensions. Always call this first.
`get_property_issues`	HPD housing violations (Class A/B/C), DOB building code violations, and ECB/OATH monetary penalties. Filter by severity, status, and date.
`get_property_history`	DOF sales records and ACRIS deed transfers. Price trajectory, buyer/seller names, document types going back to 2003.
`get_hpd_complaints`	Tenant-reported HPD complaints — leading indicators of building distress before formal violations are issued.
`get_hpd_litigations`	HPD housing court cases, open judgements, and harassment findings against building owners.
`get_hpd_registration`	Legal owner, managing agent, and head officer registration records.
`get_building_permits`	DOB job filings: new buildings, alterations, demolitions, sign permits. Status, cost estimate, applicant name.
`get_liens_and_encumbrances`	DOF tax lien sale list entries and ACRIS mortgage records. Outstanding liens, lender names, amounts, satisfactions.
`get_tax_info`	Tax assessments, market value estimates, taxable value, and active exemptions (421a, J-51, STAR).
`get_rent_stabilization`	Rent-stabilized unit counts by year (2007–2017). Trend analysis for deregulation signal.
`search_comps`	Comparable sales by zip code. Filter by building class, price, date. Includes quarterly market stats.
`search_neighborhood_stats`	Area-level aggregates: property stock, median sale prices, violation rates, rent stabilization share.
`get_fdny_fire_incidents`	FDNY fire and emergency incident history. Fire type, alarm level, spread, casualties, duration. 2013–present, loaded from NYC Open Data.
`get_311_complaints`	311 service requests at or near a property. Noise, rodents, heat, illegal dumping, and 200+ types. 2010–present, loaded from NYC Open Data.
`get_evictions`	Marshal-executed evictions by address. Residential and commercial. 2017–present, loaded from NYC Open Data.
`get_dob_complaints`	DOB complaints filed before formal violations — the earliest public signal of construction or safety issues.
`get_nypd_crime`	NYPD crime complaints within a configurable radius (default 300 m ≈ 3 blocks). Felony/misdemeanor breakdown, top offenses, year-over-year trend.
`analyze_property`	Full due diligence summary — runs all sub-queries concurrently. Property profile, FAR analysis, financials, risk factors, rent stabilization, comparable sales, and key observations.

Data Sources

Core data (~19 million rows) is loaded from nycdb. All datasets are loaded into PostgreSQL. Socrata API used as fallback only.

Dataset	Agency	Notes
PLUTO	DCP	Property profiles, zoning, FAR, building class
PAD	DCP	Address-to-BBL resolution
HPD Violations	HPD	Housing code violations by class and status
HPD Complaints	HPD	Tenant complaint records
HPD Registrations	HPD	Owner/agent/officer registration
HPD Litigations	HPD	Housing court cases
DOB Violations	DOB	Building code violations
ECB Violations	OATH/ECB	Environmental Control Board penalties
DOF Rolling Sales	DOF	Recent property sales
DOF Annual Sales	DOF	Historical sales 2003–present
DOF Assessments	DOF	Tax valuations and assessment rolls
DOF Exemptions	DOF	Tax exemption records (421a, J-51, STAR)
DOF Tax Liens	DOF	Annual lien sale list
Rent Stabilization	DOF	Stabilized unit counts by building, 2007–2017 (derived from DOF tax bills via taxbills.nyc / JustFix)
ACRIS	DOF	Deeds, mortgages, liens, satisfactions, UCC filings
FDNY Fire Incidents	FDNY	2013–present
311 Service Requests	311/DOITT	2010–present
Marshal Evictions	DOI	2017–present
DOB Complaints	DOB	Loaded from NYC Open Data
NYPD Crime Data	NYPD	2006–present, geospatial radius

Architecture

Code

src/nyc_property_intel/
  app.py              # FastMCP instance + system prompt
  server.py           # Entry point: lifespan, auth middleware, tool registration
  config.py           # pydantic-settings (reads .env / environment variables)
  db.py               # asyncpg connection pool + query helpers
  auth.py             # Token validation, rate limiting, usage logging
  analytics.py        # PostHog event capture (fire-and-forget)
  geoclient.py        # NYC GeoClient API + PAD fallback for address resolution
  socrata.py          # Socrata Open Data API client — fallback for FDNY, 311, NYPD, evictions
  loops_webhook.py    # Loops.so webhook → auto-provision trial tokens on signup
  tools/
    lookup.py         # lookup_property
    issues.py         # get_property_issues
    history.py        # get_property_history
    hpd_complaints.py # get_hpd_complaints
    hpd_litigations.py# get_hpd_litigations
    hpd_registration.py# get_hpd_registration
    permits.py        # get_building_permits
    liens.py          # get_liens_and_encumbrances
    tax.py            # get_tax_info
    rentstab.py       # get_rent_stabilization
    comps.py          # search_comps
    neighborhood.py   # search_neighborhood_stats
    fdny.py           # get_fdny_fire_incidents
    complaints_311.py # get_311_complaints
    evictions.py      # get_evictions
    dob_complaints.py # get_dob_complaints
    nypd_crime.py     # get_nypd_crime
    analysis.py       # analyze_property
scripts/
  seed_nycdb.sh         # Downloads and loads all nycdb datasets
  create_indexes.sql    # Performance indexes on critical columns
  create_views.sql      # Materialized views for fast property lookup
  manage_tokens.py      # CLI for provisioning and managing customer tokens

Development

bash

uv run pytest tests/test_utils.py -q          # unit tests (no DB needed)
uv run pytest tests/ -m integration -q        # integration tests (needs live DB)
uv run ruff check src/                         # lint
uv run nyc-property-intel                      # run server locally (stdio)

Fair Housing

NYC Property Intel provides building and property data from public city records only. It does not provide demographic data, tenant screening, or any analysis based on protected characteristics. See nycpropertyintel.com/#fair-housing for the full policy.

License

MIT