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.

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.

Related MCP server: trading-skills

Tools

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 .env

Connect 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.

Document analysis

The document tools (analyze_rent_roll, abstract_lease) work by pasting PDF text directly into the prompt. In Claude Desktop:

1. Open your rent roll or lease PDF

2. Copy all the text

3. 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.

Data sources

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

License

MIT