Find real estate agents in a market

Agents match on any of their location signals by default: their office, their listed city, and the markets where they close. Set locationSource to production to rank by where they actually transact.

The request#

curl -X POST https://api.modelmatch.com/v1/agents \
  -H "x-api-key: mm_your_key_here" \
  -H "Content-Type: application/json" \
  -d '{
    "flatFilters": { "city": "Austin, TX", "producersOnly": true },
    "locationSource": "production",
    "period": "last12Months",
    "sort": [{ "field": "volume", "order": "desc" }],
    "pagination": { "size": 25 }
  }'

import { createClient } from "@model-match/api";

const client = createClient({ apiKey: process.env.MODEL_MATCH_API_KEY });

const result = await client.agents.list({
  body: {
    flatFilters: { city: "Austin, TX", producersOnly: true },
    locationSource: "production",
    period: "last12Months",
    sort: [{ field: "volume", order: "desc" }],
    pagination: { size: 25 },
  },
});

const rows = result.data.data; // one row per agent

Write cities as "City, ST" so the name binds to the right state. county takes a 5-digit FIPS code; zip takes a 5-digit ZIP.

What comes back#

{
  "data": [
    {
      "id": "mma_8d5072986d54c67e",
      "fullName": "Priya Natarajan",
      "office": "Lakeline Realty Group",
      "city": "austin",
      "state": "TX",
      "zip": "78731",
      "volume": 118400000,
      "units": 142,
      "avgSoldPrice": 833802,
      "buyerVolume": 51200000,
      "buyerUnits": 61,
      "sellerVolume": 64700000,
      "sellerUnits": 78,
      "dualUnits": 3,
      "totalOriginatorsWorkedWith": 48,
      "totalLendersWorkedWith": 31,
      "phone": "5125550198",
      "email": "priya@example.com",
      "licenseNumber": "0523468"
    }
  ],
  "total": 14293,
  "cursor": "WyJtbTp2MiIsMjk2OTAxNzYwLCJtbWFfNzMyOWM1NTZkNjc4MmIwZiJd"
}

• buyerUnits is the number of buyers the agent represented, the deals where a mortgage introduction happens.
• totalOriginatorsWorkedWith tells you how spread out their referrals are. { "lte": 1 } finds agents loyal to a single loan officer.
• Each row costs one credit. Use the same body on /v1/agents/count first to size the list for free.

Make it yours#

• Buyer-side agents only: add "sideDominance": ["buyer"] next to flatFilters.
• Financed deals: "percentUnitsMortgaged": { "gte": 80 } keeps agents whose buyers almost always use a mortgage.
• Around an office: replace city with "near": [{ "lat": 30.27, "lon": -97.74, "radius": "15mi" }].
• Agents you don’t work with yet: "losOnMyTeam": { "relationship": "doesNotWorkWith" } excludes anyone your company’s loan officers already finance.