Connect CRE Intelligence and your agent gets 13 tools, among them abstract_lease, analyze_rent_roll, build_dcf_model. It answers at https://cre-intelligence-mcp.onrender.com/mcp over streamable HTTP, and it listed its tools to an anonymous client, so no sign-in was needed for that. Our probes reached it 6 of 6 times since 11 September 2026; the last check, on 21 October 2026, succeeded.
Live CRE analysis: Federal Reserve rates, Census 1/3/5-mile demographics, DCF models, IC memos.
Description as the publisher wrote it.
| Tool | What it does |
|---|---|
abstract_lease | 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. Inputs: text |
analyze_rent_roll | 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. Inputs: text, property_name |
build_dcf_model | 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. Inputs: noi_year1, purchase_price, hold_years, noi_growth_rate, exit_cap_rate, equity_pct |
export_dcf_excel | 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. Inputs: noi_year1, purchase_price, address, property_name, hold_years, noi_growth_rate |
flag_lease_risks | 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. Inputs: rent_roll_json |
generate_deal_memo | 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. Inputs: property_address, property_type, noi, asking_price, rent_roll_summary, additional_context |
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 analy |
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 an |
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 | 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 t Inputs: address |
get_radius_demographics | 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, house Inputs: address, radii_miles |
screen_land_market | 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 Inputs: state, county |
screen_parcel_dd | 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 ki Inputs: lat, lng |
Every block below points at https://cre-intelligence-mcp.onrender.com/mcp. Pick your client and copy.
claude mcp add --transport http cre-intelligence https://cre-intelligence-mcp.onrender.com/mcp
{
"mcpServers": {
"cre-intelligence": {
"command": "npx",
"args": ["-y", "mcp-remote", "https://cre-intelligence-mcp.onrender.com/mcp"]
}
}
}{
"mcpServers": {
"cre-intelligence": {
"url": "https://cre-intelligence-mcp.onrender.com/mcp"
}
}
}{
"servers": {
"cre-intelligence": {
"type": "http",
"url": "https://cre-intelligence-mcp.onrender.com/mcp"
}
}
}{
"context_servers": {
"cre-intelligence": {
"url": "https://cre-intelligence-mcp.onrender.com/mcp"
}
}
}{
"mcpServers": {
"cre-intelligence": {
"serverUrl": "https://cre-intelligence-mcp.onrender.com/mcp"
}
}
}{
"mcpServers": {
"cre-intelligence": {
"url": "https://cre-intelligence-mcp.onrender.com/mcp"
}
}
}name: CRE Intelligence
version: 0.0.1
schema: v1
mcpServers:
- name: CRE Intelligence
type: streamable-http
url: https://cre-intelligence-mcp.onrender.com/mcp{
"mcpServers": {
"cre-intelligence": {
"httpUrl": "https://cre-intelligence-mcp.onrender.com/mcp"
}
}
}{
"mcpServers": {
"cre-intelligence": {
"type": "http",
"url": "https://cre-intelligence-mcp.onrender.com/mcp"
}
}
}{
"mcpServers": {
"cre-intelligence": {
"url": "https://cre-intelligence-mcp.onrender.com/mcp"
}
}
}goose://extension?url=https%3A%2F%2Fcre-intelligence-mcp.onrender.com%2Fmcp&type=streamable_http&id=cre-intelligence&name=CRE%20Intelligence
It answered our last check on 21 October 2026 in 209 ms. Over 6 checks since 11 September 2026 it answered 6. Status here comes from Neuronto's own probes, not from the publisher.
13, as returned by the server's own tools/list on 13 September 2026: abstract_lease, analyze_rent_roll, build_dcf_model, export_dcf_excel, flag_lease_risks, generate_deal_memo, get_cre_market_data, get_current_rates, and 5 more.
It answered our last check on 21 October 2026 in 209 ms. Over 6 checks since 11 September 2026 it answered 6.
Put the server under mcpServers in ~/.cursor/mcp.json with the URL https://cre-intelligence-mcp.onrender.com/mcp. The exact JSON is above, with the same setup for Claude Code, Claude Desktop, VS Code, Windsurf, Zed, Gemini CLI and the rest.
It listed its tools to an anonymous client, so reading the tool list needs no key. Individual tools can still ask for credentials in their own inputs.
Publisher: io.github.zwondra. Endpoint host: cre-intelligence-mcp.onrender.com. ARD identifier: urn:air:io.github.zwondra:mcp:cre-intelligence-mcp.
First indexed 10 September 2026. The tools are exactly what the server returned; nothing on this page
is inferred from its name. Ranking in Neuronto search is never for sale.