# CRE Intelligence

> Live CRE analysis: Federal Reserve rates, Census 1/3/5-mile demographics, DCF models, IC memos.

- name: io.github.Zwondra/cre-intelligence-mcp
- version: 1.1.0
- connection class: R0 (autonomous)
- trust: 90/100
- quality: 79/100 (good)
- owner: not claimed
- descriptor: https://api.protogrid.dev/v1/servers/io.github.Zwondra%2Fcre-intelligence-mcp
- tools: https://api.protogrid.dev/v1/servers/io.github.Zwondra%2Fcre-intelligence-mcp/tools

**An agent can connect right now, no human step.** Remote endpoint, no authentication, reachable on the last probe.

## Connection (mcpServers)

```json
{
  "mcpServers": {
    "cre-intelligence-mcp": {
      "type": "http",
      "url": "https://cre-intelligence-mcp.onrender.com/mcp"
    }
  }
}
```


## Trust

- hygiene: 100
- liveness: 100
- freshness: 65
- provenance: 90
- drivers: +repository +namespace-matches-repo +website +reachable +uptime-100% ~updated-132d-ago
- Derived from observable signals (official registry feed and our own credential-free probes); no code audit performed.

## Quality 79/100 (good)

### protocol: 75 (weight 25)

- warn `protocol.modern`: newest supported version is 2025-11-25; 2026-07-28 not supported, older versions are deprecated until 2027-07-28
- n/a `protocol.stateless`: only applies to 2026-07-28 servers
- pass `protocol.transport`: streamable HTTP
- n/a `protocol.list_ttl`: only applies to 2026-07-28 servers

### authorization: n/a (weight 15)

- n/a `auth.prm`, `auth.as_metadata`, `auth.cimd`: no remote uses OAuth
- n/a `auth.secret_in_url`: no templated URL

### tool hygiene: 71 (weight 30)

- pass `tools.descriptions`: every tool has a description
- pass `tools.description_length`: descriptions are concise
- pass `tools.schemas`: every tool has an object input schema
- fail `tools.annotations`: no tool declares readOnlyHint or destructiveHint, so clients cannot tell safe calls from risky ones
- fail `tools.directory_hints`: no tool declares all four of readOnlyHint, destructiveHint, idempotentHint and openWorldHint; missing: flag_lease_risks (readOnlyHint, destructiveHint, idempotentHint, openWorldHint); generate_deal_memo (readOnlyHint, destructiveHint, idempotentHint, openWorldHint); screen_parcel_dd (readOnlyHint, destructiveHint, idempotentHint, openWorldHint); …
- pass `tools.token_cost`: about 2,303 tokens to load every tool
- pass `tools.api_dump`: tools are not a one-to-one API dump

### stability: 100 (weight 15)

- pass `stability.changes`: no tool changes in 30 days
- pass `stability.rug_pull`: no tool changed its meaning under the same name

### dependencies: n/a (weight 15)

- n/a `deps.known_vulns`, `deps.mcp_sdk_version`, `deps.resolvable`: no npm or PyPI package

- tools: 13, about 2,303 tokens to load them all
- tool set hash: 023f8a6a70cbe6ffe1541a0d1297e567
- badge: [![protogrid quality](https://protogrid.dev/badge/io.github.Zwondra/cre-intelligence-mcp.svg)](https://protogrid.dev/servers/io.github.Zwondra/cre-intelligence-mcp)
- Checks run on what our credential-free, read-only probes observe; tools are never called and no code audit is performed.

### Tool changes

_No tool definition changes recorded._

## Remotes

- https://cre-intelligence-mcp.onrender.com/mcp (streamable-http, auth none, reachable true, uptime30d 1)

## Packages

_none_

## Tools (13)

- `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.
- `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.
- `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.
- `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.
Returns a download link valid for 60 minutes.
- `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.
- `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.
- `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`: 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.
- `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, 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.
- `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.

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.
- `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 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.