plat-costmodel
Click on "Deploy 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., "@plat-costmodelEstimate per-unit renovation cost for a 1985 Class B property in Dallas with 800 sq ft units."
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.
plat-costmodel
Multifamily renovation cost estimation engine for Plat — a domain-expert real estate intelligence agent.
What It Does
Per-unit cost estimation with line-item breakdowns (flooring, kitchen, bath, paint, appliances, fixtures, contingency)
Scope of Work (SOW) generation — contractor-ready documents from property profile
Contractor bid evaluation — flags inflated line items, vague lump sums, unrealistic timelines
ROI gating — 15% minimum threshold check on all renovation plans
Risk flagging — age-based warnings (galvanized pipe, asbestos, foundation concerns)
Budget vs. actual tracking — Yardi Voyager integration for model calibration
Related MCP server: ritn3d-mcp
Architecture
MCP tool server callable by Plat's orchestration layer. CLI-first interface.
Plat (agent) ──MCP──▶ plat-costmodel (tool server)
├── estimate — per-unit cost range
├── sow — scope of work generation
├── evaluate — contractor bid evaluation
├── roi — ROI threshold check
└── ingest — Yardi CSV importTwo Scope Levels
Scope | Cost Range | Description |
Light | $3K-$5K/unit | Paint, clean, patch, hardware, carpet |
Standard Value-Add | $12K-$18K/unit | Full kitchen/bath update, LVP, appliances, fixtures |
Gut renos excluded — don't pencil at Class C rents.
Cost Model Inputs
Unit square footage (<700 small, 700-950 medium, 950+ large)
Finish tier (basic vs. upgraded)
Number of bedrooms/bathrooms
Property year built (drives risk flags)
Property class (B or C)
Market (Dallas, Birmingham — more later)
Data Sources
Brain dump knowledge — Day 1 baseline from operator experience
Yardi Voyager CSV exports — historical actuals tagged to unit numbers
RSMeans benchmarks — industry reference data (future)
Cross-user pooled data — anonymous Glassdoor-style model (SaaS future)
This server cannot be deployed
Maintenance
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