Model Match
Connect your agents

Put Model Match inside Claude and ChatGPT

Connect Model Match to any MCP-compatible AI assistant. Ask about lenders, loan officers, agents, and borrowers in plain English — and get answers grounded in real mortgage and real estate records, not the open web.

Trusted by 5,000+ industry professionals

modelMatch_MovementMortgage modelMatch_RocketPro modelMatch_UnionHomeMortgage

One command to connect

Add the MCP server once, use it everywhere

Drop the Model Match MCP server into Claude, ChatGPT, or any MCP-compatible client. No integration code, no CSV exports, no stale data — your assistant can query originators, market signals, and loans directly.

terminal
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Added MCP server “modelmatch”

search_originators · market_signals · analyze_loans — ready in your assistant

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Market intelligence in Claude

Size up any market without leaving the chat

Ask Claude for the top lenders or loan officers in a metro and it pulls the numbers over the Model Match connection — sorted by volume, sourced, and current — then keeps the thread going as you drill in.

Claude Model Match
Who are the top mortgage lenders in the Charlotte metro this year?
Pulling lender production for Charlotte, NC metro, last 12 months:
companyAnalytics · metro: Charlotte, NC 2.0s

Top mortgage lenders · Charlotte, NC metro · 2026

Lender Volume Share YoY
Beacon Lending Group $1.84B 9.2% +1.4 pt
Summit Mortgage $1.57B 7.8% +0.6 pt
Acme Home Loans $1.31B 6.5% −0.9 pt
Meridian Home Loans $1.06B 5.3% +0.3 pt
Company records Market data

Agent search in ChatGPT

Find the active agents worth courting

Ask ChatGPT for the most active buyer's agents in a market and it returns a real, current list from Model Match data — names, brokerages, and recent activity — ready to work into your outreach.

ChatGPT Model Match
Find the most active buyer's agents in Mesa, AZ this year — include their brokerage.
Searching agents in Mesa, AZ (85201), sorted by buy-side volume:
listAgents · sort: buySideVolume 2.2s

Most active buyer's agents · Mesa, AZ · 2026

Agent Brokerage Buy-side Volume
Priya Nair Desert Sky Realty 41 $15.6M
Marcus Delgado Red Rock Group 34 $12.8M
Hannah Brooks Saguaro Homes 29 $10.4M
Theo Vance Valley & Co. 26 $9.1M
Emails and phone numbers come through on export — ask to add these to a pipeline.

Production on demand

Pull any originator's production history

Ask for a loan officer's funded production and your assistant charts it straight from Model Match — across years of history, back to 2017, with no dashboards to open and no exports to reconcile.

Claude Model Match
Look up Daniel Okafor at Summit Mortgage in Austin — how's his production trending?
Pulling 12-month production from Model Match:
originatorAnalytics · nmls: 1142087 1.9s

Daniel Okafor · Summit Mortgage · Austin, TX

Last 12 months: $58.4M funded · 184 units · 68% purchase

Funded volume · last 12 months

Trending up — Q4 his strongest quarter

Volume $0M
Units 0
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Originator profile Loan records
Who recently left his branch?

Renee Alvarez → Lone Star Lending · $31M, last quarter

Marcus Hadley → Capital Peak Mortgage · $22M, 2 mo ago

Context is everything

Give your AI agents 6B+ records of context

An assistant is only as sharp as the data behind it. Connect Model Match over MCP and your agents can reason over 6+ billion mortgage and real estate records — the same data that powers the app — and carry that context into the other tools you already run, so answers stay grounded in the real market instead of the open web.

Ask Model Match Share
How did my team's funded volume trend in May?
Team Volume · authenticated as you 1.8s

Your team · May 2026

Funded volume: $48.3M · up 6% from April

Units: 132 loans · 9 loan officers

Strongest market: Charlotte metro · 41% of volume

Scoped to your seat's permissions — the same data you'd see in the app, nothing from the open web.

Connect Model Match to your AI in minutes

Start a 14-day free trial, add the MCP server, and query live mortgage and real estate data from Claude, ChatGPT, or any MCP assistant.

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