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kkamalvanshi

Tenant Leasing Analytics

by kkamalvanshi

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.

šŸ“Š 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

Related MCP server: Estaite Solutions

šŸ› ļø 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

šŸ“§ Email Generation

Tool

Description

generate_leasing_email(...)

Create professional leasing update email

šŸ“Š Visual Reports

Tool

Description

create_market_report()

Full 6-chart visual report (bar, pie, histogram)

create_individual_chart(type)

Generate specific chart types

šŸ“§ 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  • withdrawn_applications: Withdrawn apps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

šŸ“Š 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

šŸš€ 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"
    }
  }
}

šŸ’¬ 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"

šŸ“ Data Files

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

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

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