Nyc Property Intel

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 claude_desktop_config.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.gitcd nyc-property-inteluv 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/nullpg_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/nullchmod +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:

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

4. Add to Claude Desktop

{  "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:

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

18 Tools

Data Sources

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

Architecture

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_propertyscripts/  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

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/                         # lintuv 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