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](https://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"

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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:

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

{

"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" } } }

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18 Tools

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Data Sources

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

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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_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

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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/ # lint uv run nyc-property-intel # run server locally (stdio)

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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