Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Tenant Leasing Analyticsanalyze the nearby rental market and show me a rent histogram"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
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.
π Data Architecture
This MCP server only uses data from the tenant-info/ folder:
Table | Description | Rows |
| Prospective tenant inquiries with preferences | 100 |
| Comparable rental listings in the area | 100 |
π οΈ Available Tools
Schema & Query
Tool | Description |
| View database schema and column descriptions |
| Execute any SELECT query |
Guest Card Analytics
Tool | Description |
| Comprehensive summary of all inquiries |
| Find prospects meeting criteria |
Market Analytics
Tool | Description |
| Analyze nearby rental market conditions |
π§ Email Generation
Tool | Description |
| Create professional leasing update email |
π Visual Reports
Tool | Description |
| Full 6-chart visual report (bar, pie, histogram) |
| Generate specific chart types |
π§ 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 recipientsender_name: Your namecurrent_rate: Current advertised rentprevious_rate: Previous rent rateshowings_confirmed: Number of confirmed showingsshowings_attended: Number who attendedinterested_parties: Number who seemed interestedpending_applications: Current pending appswithdrawn_applications: Withdrawn appsupcoming_showings: Scheduled future showings
π Visual Reports
Full Market Report (create_market_report())
Generates a comprehensive 6-panel report including:
Rent Distribution Histogram - Nearby rental price spread
Credit Score Pie Chart - Prospect credit quality
Pet Preferences Bar Chart - Pet ownership breakdown
Budget Distribution Histogram - Prospect max rent budgets
Price Comparison Bar Chart - Market vs our rate
Activity Types Pie Chart - Prospect engagement
Individual Charts (create_individual_chart(type))
Available chart types:
rent_histogram- Distribution of nearby rental pricescredit_pie- Credit score distributionpet_bar- Pet preferences breakdownbudget_histogram- Prospect budget distributionprice_comparison- Market vs our pricingactivity_pie- Prospect activity typesincome_vs_rent- Income vs max rent scattersimilarity_rent- Property similarity vs rent scatter
π Setup
Prerequisites
Python 3.10+
uvpackage manager
Installation
cd /Users/kkamalva/financial_analysis/MCP/kurt-data
uv syncClaude 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"
}
}
}π¬ 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"
π Data Files
This MCP server is self-contained within the kurt-data/ folder and only uses data from tenant-info/:
kurt-data/
βββ server.py β MCP server
βββ run_server.sh β Launch script
βββ pyproject.toml β Dependencies
βββ tenant-info/
β βββ synthetic_guest_cards.csv
β βββ nearby_advertised_units.csv
βββ charts/
βββ (generated visualizations)This server cannot be installed
Resources
Looking for Admin?
Admins can modify the Dockerfile, update the server description, and track usage metrics. If you are the server author, to access the admin panel.