Tenant Leasing Analytics

Tenant Leasing Analytics

Enables analysis of prospective tenant inquiries and market rent comparisons through database queries, guest card analytics, and automated generation of leasing emails and visual market reports with charts.

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README

Tenant Leasing Analytics - MCP Server

A specialized MCP (Model Context Protocol) server for tenant leasing analytics, focused on guest card management and market rent comparisons.

📊 Data Architecture

This MCP server only uses data from the tenant-info/ folder:

Table Description Rows
guest_cards Prospective tenant inquiries with preferences 100
nearby_units Comparable rental listings in the area 100

🛠️ Available Tools

Schema & Query

Tool Description
get_schema() View database schema and column descriptions
query_database(sql) Execute any SELECT query

Guest Card Analytics

Tool Description
guest_card_summary() Comprehensive summary of all inquiries
qualified_prospects(min_income, min_credit) Find prospects meeting criteria

Market Analytics

Tool Description
market_rent_analysis() Analyze nearby rental market conditions

📧 Email Generation

Tool Description
generate_leasing_email(...) Create professional leasing update email

📊 Visual Reports

Tool Description
create_market_report() Full 6-chart visual report (bar, pie, histogram)
create_individual_chart(type) Generate specific chart types

📧 Email Generation

The generate_leasing_email() tool creates professional leasing update emails like:

Good Morning Chi,

Last week in total we received 17 inquiries and I had no groups confirm showings. 
As discussed, we decreased the rate to $2400 and have received 4 new inquiries...

Parameters:

  • recipient_name: Email recipient
  • sender_name: Your name
  • current_rate: Current advertised rent
  • previous_rate: Previous rent rate
  • showings_confirmed: Number of confirmed showings
  • showings_attended: Number who attended
  • interested_parties: Number who seemed interested
  • pending_applications: Current pending apps
  • withdrawn_applications: Withdrawn apps
  • upcoming_showings: Scheduled future showings

📊 Visual Reports

Full Market Report (create_market_report())

Generates a comprehensive 6-panel report including:

  1. Rent Distribution Histogram - Nearby rental price spread
  2. Credit Score Pie Chart - Prospect credit quality
  3. Pet Preferences Bar Chart - Pet ownership breakdown
  4. Budget Distribution Histogram - Prospect max rent budgets
  5. Price Comparison Bar Chart - Market vs our rate
  6. Activity Types Pie Chart - Prospect engagement

Individual Charts (create_individual_chart(type))

Available chart types:

  • rent_histogram - Distribution of nearby rental prices
  • credit_pie - Credit score distribution
  • pet_bar - Pet preferences breakdown
  • budget_histogram - Prospect budget distribution
  • price_comparison - Market vs our pricing
  • activity_pie - Prospect activity types
  • income_vs_rent - Income vs max rent scatter
  • similarity_rent - Property similarity vs rent scatter

🚀 Setup

Prerequisites

  • Python 3.10+
  • uv package manager

Installation

cd /Users/kkamalva/financial_analysis/MCP/kurt-data
uv sync

Claude Desktop Configuration

Add to ~/Library/Application Support/Claude/claude_desktop_config.json:

{
  "mcpServers": {
    "tenant-leasing": {
      "command": "/Users/kkamalva/financial_analysis/MCP/kurt-data/run_server.sh"
    }
  }
}

💬 Example Questions

Guest Card Questions

  • "Show me a summary of all guest cards"
  • "Find qualified prospects with income over $8,000"
  • "What's the credit score distribution of our prospects?"

Market Questions

  • "Analyze the nearby rental market"
  • "How does our price compare to the market?"
  • "What's the average rent in the area?"

Email & Reports

  • "Generate a leasing update email for Chi"
  • "Create a market report with charts"
  • "Generate a rent histogram"

📁 Data Files

This MCP server is self-contained within the kurt-data/ folder and only uses data from tenant-info/:

kurt-data/
├── server.py              ← MCP server
├── run_server.sh          ← Launch script
├── pyproject.toml         ← Dependencies
├── tenant-info/
│   ├── synthetic_guest_cards.csv
│   └── nearby_advertised_units.csv
└── charts/
    └── (generated visualizations)

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