CRE Intelligence MCP
Live market data for commercial real estate analysis — inside Claude.
Connect this MCP to Claude Desktop and instantly access Federal Reserve interest rates, Census Bureau demographics, DCF modeling, rent roll parsing, lease abstraction, and IC memo generation — all from a single prompt.
"Analyze this deal: 2201 South Blvd, Charlotte NC. NOI $400k, asking $6M, retail strip." → Pulls live SOFR from the Fed. Pulls Census demographics for that exact block. Builds a full levered 10-year DCF. Writes an institutional-quality IC memo. 30 seconds.
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Why this exists
The #1 problem with AI in CRE: 66% of professionals use it daily, but only 5% trust it for actual deal decisions.
The reason? AI guesses at rates and demographics. A DCF built on a hallucinated SOFR rate is worthless.
This MCP fixes that. Every number comes from a verified public source:
- Interest rates → Federal Reserve (FRED API)
- Demographics → US Census Bureau ACS
- Document analysis → Claude AI with structured output
Zero data licensing fees. Zero hallucinations on financial inputs.
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Tools
| Tool | What it does | Data source | |------|-------------|-------------| | get_current_rates | Live SOFR, 10yr Treasury, Fed Funds + implied cap ranges by property type | FRED | | get_inflation_data | CPI, shelter inflation, rent CPI + DCF rent growth guidance | FRED | | get_cre_market_data | CRE price index, C&I loan trends, delinquency rates, credit spreads | FRED | | get_market_demographics | Median income, employment, vacancy, rents for any US address | Census Bureau | | get_radius_demographics | 1/3/5-mile trade-area rings: population, weighted income, renter share, rents | Census Bureau | | analyze_rent_roll | Paste PDF text → structured JSON: tenant, SF, rent, dates, expirations | Claude AI | | abstract_lease | Paste lease text → term, rent schedule, TI, options, red flags | Claude AI | | flag_lease_risks | Rent roll JSON → rollover risk, concentration risk, due diligence checklist | Claude AI | | build_dcf_model | Full levered 10-year DCF with live rates auto-fetched from FRED | Python + FRED | | generate_deal_memo | Address + NOI + price → full IC memo with live rates and demographics | Claude AI + FRED + Census | | export_dcf_excel | Downloadable .xlsx underwriting model with live formulas, sensitivity grid, market data | Python + FRED + Census |
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Example output
Prompt: "Get me current interest rates"
SOFR: 3.63% (June 8, 2026)
SOFR 30-day: 3.59%
10yr Treasury: 4.55%
5yr Treasury: 4.29%
Fed Funds: 3.63%
Implied cap rates (spread over 10yr T):
Core Multifamily: 5.30% – 6.05%
Core Industrial: 5.55% – 6.30%
Core Office: 6.05% – 7.05%
Value-Add: 6.05% – 7.05%
Loan rate guidance:
Floating: SOFR + 150–250bps = ~5.38%–5.88%
Fixed: 10yr T + 150–200bps = ~6.05%–6.55%Prompt: "Analyze this deal: 2201 South Blvd Charlotte NC, NOI $400k, asking $6M, retail strip"
The MCP automatically chains get_current_rates + get_market_demographics + build_dcf_model + generate_deal_memo and returns a full IC memo including:
Entry Cap Rate: 6.67% (+212bps over 10yr Treasury)
Loan Rate: 5.38% (derived from live SOFR 3.63% + 175bps)
Year 1 DSCR: 1.53x
IRR: 14.6%
Equity Multiple: 3.11x
Census Tract demographics (2023 ACS):
Median HHI: $141,419
Employment rate: 97.2%
College educated: 64.9%
Vacancy rate: 8.6%
Recommendation: GO — subject to rent roll review and comp analysis.---
Setup
Option A — Hosted (fastest, no API keys)
Add this to your claude_desktop_config.json and restart Claude Desktop:
{
"mcpServers": {
"cre-intelligence": {
"type": "streamable-http",
"url": "https://cre-intelligence-mcp.onrender.com/mcp"
}
}
}If your MCP client only supports stdio servers, use the mcp-remote bridge instead:
{
"mcpServers": {
"cre-intelligence": {
"command": "npx",
"args": ["-y", "mcp-remote", "https://cre-intelligence-mcp.onrender.com/mcp"]
}
}
}Free during beta. All data fetching runs server-side.
Option B — Self-hosted
Prerequisites
- Claude Desktop
- Python 3.11+
- Free API keys (takes ~2 minutes total):
- FRED: fred.stlouisfed.org/docs/api/api_key.html
- Census: api.census.gov/data/key_signup.html
- Anthropic: console.anthropic.com
Install
git clone https://github.com/Zwondra/cre-intelligence-mcp
cd cre-intelligence-mcp
python3.11 -m venv venv
venv/bin/pip install -r requirements.txt
cp .env.example .env
# Add your API keys to .envConnect to Claude Desktop
Add to ~/Library/Application Support/Claude/claude_desktop_config.json:
{
"mcpServers": {
"cre-intelligence": {
"command": "/path/to/cre-intelligence-mcp/venv/bin/python3",
"args": ["/path/to/cre-intelligence-mcp/server.py"],
"env": {
"ANTHROPIC_API_KEY": "sk-ant-...",
"FRED_API_KEY": "your_fred_key",
"CENSUS_API_KEY": "your_census_key"
}
}
}
}Restart Claude Desktop. The tools will appear automatically.
Test it
Open Claude Desktop and say:
"Get me current interest rates"
You should see it call get_current_rates and return live Federal Reserve data.
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Document analysis
The document tools (analyze_rent_roll, abstract_lease) work by pasting PDF text directly into the prompt. In Claude Desktop:
- Open your rent roll or lease PDF
- Copy all the text
- Say: "Analyze this rent roll: [paste text]"
The tool extracts every tenant, suite, SF, rent, lease dates, and expiration into structured JSON — then flag_lease_risks can immediately analyze it for rollover and concentration risk.
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Data sources
| Source | What | Cost | |--------|------|------| | FRED (Federal Reserve) | SOFR, Treasury yields, Fed Funds, CPI, CRE price index | Free | | Census Bureau ACS | Income, employment, housing, rents by census tract | Free | | Anthropic Claude | Document parsing, risk analysis, memo generation | Pay per use |
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Roadmap
- [ ] Comparable sales search (CREXI public listings)
- [ ] Multi-property portfolio analysis
- [ ] Sensitivity table generation (cap rate / NOI / LTV scenarios)
- [ ] Export to Excel / Word
- [ ] Deal history / comparison across sessions
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License
MIT
