mcp server
CRE Intelligence
Live CRE analysis: Federal Reserve rates, Census 1/3/5-mile demographics, DCF models, IC memos.
Description as published by the maintainer. Source
- version 1.1.0
- active
active — Registry entry last updated 2026-06-10.
What this server can do
13 functions, named and described by the server itself. Parameter names are shown because they say more about what a function does than its name usually does.
abstract_lease(text)- Extract all key terms from a commercial lease document. Returns term, base rent schedule, escalations, TI allowance, CAM structure, renewal options, termination rights, exclusivity, co-tenancy, and red flags. Required: text.
analyze_rent_roll(text, property_name)- Extract structured tenant and lease data from a rent roll document. Paste the text content of your rent roll PDF here (copy-paste from PDF reader). Returns tenant list, suite/SF, lease dates, monthly rent, escalations, and options. Required: text.
build_dcf_model(loan_rate, noi_year1, equity_pct, hold_years, exit_cap_rate, purchase_price, noi_growth_rate, amortization_years)- Build a levered DCF model using live Federal Reserve rates. Automatically fetches current SOFR to derive the loan rate if not provided. Returns: annual cash flows, IRR, equity multiple, cash-on-cash, DSCR, and exit analysis. Required: noi_year1, purchase_price.
export_dcf_excel(address, loan_rate, noi_year1, equity_pct, hold_years, exit_cap_rate, property_name, purchase_price, noi_growth_rate, amortization_years)- Generate a downloadable Excel (.xlsx) underwriting model with LIVE formulas — editable assumptions, PMT/FV amortization, IRR, equity multiple, a sensitivity grid, live Fed rates, and (if an address is given) Census trade-area demographics. Returns a download link valid for 60 minutes. Required: noi_year1, purchase_price.
flag_lease_risks(rent_roll_json)- Analyze a parsed rent roll for investment risks. Feed the output from analyze_rent_roll directly into this tool. Returns: rollover risk, tenant concentration, credit risk, and actionable recommendations. Required: rent_roll_json.
generate_deal_memo(noi, asking_price, property_type, property_address, rent_roll_summary, additional_context)- Generate a formatted CRE acquisition memo / Investment Committee memo. Automatically pulls live rates from FRED and demographics from Census Bureau to provide real market context — not guesses. Required: property_address, property_type, noi, asking_price.
get_cre_market_data- Get Commercial Real Estate price index and broader market data from the Federal Reserve. Returns CRE price trends, office/retail/industrial vacancy proxies, and credit spreads. Provides macro context for deal underwriting and cap rate analysis.
get_current_rates- Get live interest rates from the Federal Reserve (FRED). Returns SOFR, 10-year Treasury, 5-year Treasury, Fed Funds Rate, and 30-day SOFR average. Also calculates implied cap rate ranges based on current treasury spreads. Use this BEFORE any DCF model or loan underwriting. These are real-time numbers Claude cannot access on its own.
get_inflation_data- Get current CPI and rent inflation data from the Federal Reserve. Returns overall inflation, shelter inflation, and rent-specific CPI with YoY changes. Use this to calibrate rent growth assumptions in your DCF model — don't guess.
get_market_demographics(address)- Get Census Bureau demographics for any US property address. Returns median income, population, employment rate, housing vacancy, median rents, and education levels for the census tract. This is address-specific data from the actual Census tract — not estimates. Claude cannot access this without the MCP. For 1/3/5-mile trade-area rings, use get_radius_demographics instead. Required: address.
get_radius_demographics(address, radii_miles)- Get aggregated Census demographics for radius rings around a US property address — the standard 1/3/5-mile trade-area format used in CRE site analysis. Aggregates every census tract whose centroid falls within each radius: population, household-weighted median income, employment rate, college attainment, housing vacancy, renter share, and median rent. Use this for trade-area / site analysis. Use get_market_demographics for the single census tract immediately around the address. Required: address.
screen_land_market(state, county)- Screen a US county as a LAND-INVESTING market (raw-land flip / Podolsky style). Grades the county on the signals that matter for buying cheap rural land and reselling on terms: population growth, demographics, owner share, and affordability. IMPORTANT: This screens on FREE Census data only (growth + demographics + a home-value affordability proxy). It does NOT include actual land sale prices or comps — those require county records or a paid service, and must be verified per-parcel before buying. Use this to rank/shortlist markets, not to buy. Required: state, county.
screen_parcel_dd(lat, lng)- Pre-screen a land parcel's location for the AUTOMATABLE due-diligence red flags: FEMA flood zone and federal wetlands. Pulls live from FEMA's National Flood Hazard Layer and the US Fish & Wildlife National Wetlands Inventory. Use this to kill obviously-bad parcels (flood zone, wetlands) at scale BEFORE spending time on manual due diligence. IMPORTANT: Checks flood + wetlands only. It does NOT check legal ACCESS (landlocked — the #1 land deal-killer), title/liens, or zoning — those stay MANUAL, per-parcel checks via county records. A clean screen here is necessary, NOT sufficient. Required: lat, lng.
Last successful function declaration observed on . Source: https://cre-intelligence-mcp.onrender.com/mcp. We list what the server declared; we do not call any of these functions.
Endpoint status observed on . Source: https://cre-intelligence-mcp.onrender.com/mcp.
Signals
These are separate measurements of different things. They are deliberately not combined into one score, because a popularity number that mixes website traffic with saves and stars cannot be checked or acted on.
| Signal | Value | What it measures | Window | Observed | Source |
|---|---|---|---|---|---|
| Latest published version | 1.1.0 | Latest version string the maintainer published to the registry. | as of fetch | Model Context Protocol | |
| Registry record last updated | 2026-06-10 | When the registry record was last updated by its maintainer. | point in time | Model Context Protocol | |
| First listed in the MCP Registry | 2026-06-10 | Date this server was first published to the official MCP Registry. Not a usage or quality measure. | point in time | Model Context Protocol | |
| mcp tools declared | 13 tools | Number of functions the server itself declared when asked to list them. This is what the server offers an agent, not a measure of how well any of them work. | as of probe | cre-intelligence-mcp.onrender.com | |
| mcp endpoint status | ok | The server listed 13 functions when asked. | as of probe | cre-intelligence-mcp.onrender.com |
Where to get it
This record as data
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