Connect to a Multiple Listing Service data feed via a Cloud Function that authenticates with RESO Web API credentials, fetches property listings, and normalizes them into Firestore documents. Run the sync on a 4-hour schedule to keep listings current. Display properties on a Google Map with markers and build filter controls for price, beds, baths, and property type. Always show the required MLS disclaimers and data attribution for IDX compliance.
Connecting Real Estate MLS Data to Your FlutterFlow App
MLS integration is the backbone of any real estate app. It connects your app to the centralized database of property listings maintained by real estate boards. This tutorial covers authenticating with the RESO Web API, syncing listings to Firestore on a schedule, displaying properties on a map with filters, and meeting the strict IDX compliance requirements that come with MLS data access.
Prerequisites
- A FlutterFlow project with Firestore and Firebase Authentication configured
- MLS board membership with approved IDX data feed access and RESO Web API credentials
- Firebase Blaze plan for Cloud Functions and Cloud Scheduler
- Google Maps API key configured in FlutterFlow for map display
Step-by-step guide
Set up the Firestore schema for normalized MLS property data
Set up the Firestore schema for normalized MLS property data
Create a properties collection with fields: mlsId (String, unique listing ID from MLS), status (String: Active/Pending/Sold/Withdrawn), address (String), city (String), state (String), zip (String), lat (Double), lng (Double), price (Double), beds (Int), baths (Double), sqft (Int), propertyType (String: Single Family/Condo/Townhouse/Multi-Family/Land), yearBuilt (Int), description (String), photos (Array of Strings, image URLs), listingAgent (Map: name, phone, email, brokerage), mlsName (String, the MLS that provided the data), lastSynced (Timestamp), listDate (Timestamp). Add Firestore indexes on status + price and status + propertyType for filtered queries. The mlsId field ensures idempotent syncing — update existing docs rather than creating duplicates.
Expected result: Firestore has a properties collection with a normalized schema that maps cleanly to MLS data fields, with indexes supporting common search filters.
Build the Cloud Function to authenticate and fetch MLS data via RESO Web API
Build the Cloud Function to authenticate and fetch MLS data via RESO Web API
Deploy a Cloud Function syncMLSListings() that authenticates with the RESO Web API using OAuth 2.0 client credentials (client_id and client_secret stored in Cloud Function environment config). After obtaining an access token, make paginated GET requests to the Property resource endpoint with $filter for ModificationTimestamp greater than the last sync time (stored in a Firestore metadata doc). For each property in the response, normalize field names from RESO standard (ListPrice, BedroomsTotal, BathroomsTotal, LivingArea) to your Firestore schema. Use Firestore batch writes to create or update property docs, matching on mlsId. Update the metadata doc with the current sync timestamp. Handle pagination by following the @odata.nextLink until no more pages.
Expected result: The Cloud Function fetches new and updated listings from the MLS, normalizes them, and writes them to Firestore without duplicates.
Schedule automatic sync every 4 hours and handle delistings
Schedule automatic sync every 4 hours and handle delistings
Configure Firebase Cloud Scheduler to trigger the syncMLSListings function every 4 hours using a cron expression. In the sync function, after processing updates, fetch a list of currently active mlsIds from the MLS. Query Firestore for properties with status Active whose mlsId is not in the active list — these have been delisted. Update their status to Withdrawn and set lastSynced to now. This ensures your app never shows stale listings. Add error alerting: if the sync function fails, write an error doc to an admin_alerts collection that triggers a notification to the admin.
Expected result: MLS data syncs automatically every 4 hours, delisted properties are marked as withdrawn, and sync failures trigger admin alerts.
Display listings on a Google Map with property markers and filter controls
Display listings on a Google Map with property markers and filter controls
Create a PropertySearchPage with FlutterFlowGoogleMap taking up the top 60% of the screen and a draggable BottomSheet with listing cards taking the bottom 40%. Place filter controls above the map: DropDown for property type, a RangeSlider for price (min/max), and Row of increment buttons for beds and baths. Query properties where status is Active with the selected filters. For each result, add a map marker at the lat/lng coordinates. Tapping a marker scrolls the bottom ListView to the corresponding listing card and highlights it. Each card shows the first photo, price, address, beds/baths/sqft, and listing agent. Tapping a card navigates to PropertyDetailPage with full photo carousel, description, and agent contact.
Expected result: Users see property listings as markers on a map, can filter by price, beds, baths, and type, and tap markers to view listing details.
Add IDX compliance disclaimers and MLS data attribution
Add IDX compliance disclaimers and MLS data attribution
IDX compliance is mandatory for any app displaying MLS data. At the bottom of every page that shows MLS listings, add a Container with the required disclaimer text: the MLS logo image (from your MLS board), the text 'Listing data provided by [MLS Name]. Information deemed reliable but not guaranteed.', a last-updated timestamp from the lastSynced field, and the broker attribution text required by your specific MLS board. On the PropertyDetailPage, show the listing agent's name, brokerage, and contact information. Add a Firestore document mls_settings with fields: disclaimerText, logoUrl, brokerAttributionText — so the admin can update compliance text without republishing. Never allow users to modify or hide MLS data fields — display them exactly as provided.
Expected result: Every listing display includes the required MLS disclaimer, data source logo, timestamp, and broker attribution for full IDX compliance.
Complete working example
1FIRESTORE DATA MODEL:2 properties/{docId}3 mlsId: String (unique, e.g., 'MLS-12345678')4 status: String (Active | Pending | Sold | Withdrawn)5 address: String6 city: String7 state: String8 zip: String9 lat: Double10 lng: Double11 price: Double12 beds: Int13 baths: Double14 sqft: Int15 propertyType: String16 yearBuilt: Int17 description: String18 photos: Array of Strings (image URLs)19 listingAgent: Map { name, phone, email, brokerage }20 mlsName: String21 lastSynced: Timestamp22 listDate: Timestamp2324 mls_sync_metadata/{metaDocId}25 lastSyncTimestamp: Timestamp26 lastSyncStatus: String (success | failed)27 listingsProcessed: Int2829 mls_settings/{settingsDocId}30 disclaimerText: String31 logoUrl: String32 brokerAttributionText: String3334CLOUD FUNCTION: syncMLSListings (scheduled every 4 hours)35 1. OAuth 2.0 authenticate with MLS RESO Web API36 2. GET /Property?$filter=ModificationTimestamp gt lastSync37 3. Normalize RESO fields → Firestore schema38 4. Batch write: create or update by mlsId39 5. Mark delisted properties as Withdrawn40 6. Update lastSyncTimestamp4142PAGE: PropertySearchPage43 Column44 Row (filters)45 DropDown (property type)46 RangeSlider (price: $0 - $2M)47 Row: beds +/- buttons | baths +/- buttons48 Expanded Stack49 FlutterFlowGoogleMap (60% height)50 Markers from query results at lat/lng51 On Marker Tap → scroll to listing card52 DraggableScrollableSheet (bottom 40%)53 ListView (horizontal)54 Card55 Image (photos[0], width: 280, height: 180)56 Text (price, titleMedium, bold)57 Text (address, bodyMedium)58 Row: beds icon + baths icon + sqft icon59 On Tap → Navigate PropertyDetailPage60 Container (IDX disclaimer)61 Row: Image (MLS logo) + Text (disclaimer + lastSynced)Common mistakes
Why it's a problem: Not displaying the required MLS disclaimers and data attribution on listing pages
How to avoid: Always show the MLS logo, data source attribution, last-updated timestamp, and broker credit on every page displaying MLS data. Store disclaimer text in Firestore for easy updates.
Why it's a problem: Fetching MLS data on every app load instead of syncing to Firestore
How to avoid: Sync MLS data to Firestore on a schedule (every 4 hours). The app queries Firestore for fast local reads. Only the Cloud Function talks to the MLS API.
Why it's a problem: Creating duplicate property documents on each sync instead of updating by mlsId
How to avoid: Use mlsId as the deduplication key. Query Firestore for an existing doc with the same mlsId before writing. If found, update the existing doc. If not, create a new one.
Best practices
- Use mlsId as the unique key for idempotent sync — update existing docs rather than creating duplicates
- Store MLS API credentials exclusively in Cloud Function environment config, never in client code
- Sync incrementally using ModificationTimestamp to fetch only new and updated listings
- Mark delisted properties as Withdrawn rather than deleting them, preserving historical data
- Store IDX disclaimer text and MLS logo URL in a Firestore settings document for admin-updatable compliance
- Add Firestore composite indexes on status + price and status + propertyType for efficient filtered queries
- Cache map markers in Page State to avoid re-querying Firestore on every map pan or zoom
Still stuck?
Copy one of these prompts to get a personalized, step-by-step explanation.
I need to integrate MLS property listing data into a FlutterFlow real estate app. Show me how to authenticate with the RESO Web API in a Cloud Function, sync listings to Firestore on a schedule, display them on a Google Map with filters, and maintain IDX compliance.
Create a property search page with a Google Map taking the top 60% of the screen and a draggable bottom sheet with horizontal scrolling property cards. Add a filter row above the map with dropdowns for property type and price range.
Frequently asked questions
How do I get access to MLS data?
You need membership in a local MLS board or a partnership with a licensed real estate broker who has IDX feed access. Apply through your local MLS board for a RETS or RESO Web API data feed.
What is IDX compliance and why does it matter?
IDX (Internet Data Exchange) rules govern how MLS data can be displayed publicly. Violations include missing disclaimers, modifying listing data, or not showing agent attribution. Non-compliance results in feed access revocation.
How often should I sync MLS data?
Every 4-6 hours is standard. Hot markets may benefit from hourly syncs. Check your MLS board's API rate limits and adjust accordingly. Always sync incrementally using modification timestamps.
Can I display sold property data for market analysis?
It depends on your MLS board's rules. Some boards allow sold data display for a limited time (6-12 months). Check your IDX agreement. If allowed, include sold listings with the Sold status clearly indicated.
What if the MLS API format changes?
RESO Web API follows a standardized schema, so major changes are rare. If your MLS board migrates from RETS to RESO, update the Cloud Function's API endpoint and field mapping. The Firestore schema can remain the same.
What if I need a production-ready real estate app with MLS integration?
RapidDev has built real estate platforms in FlutterFlow with MLS data sync, interactive map search, saved searches, agent CRM features, and full IDX compliance across multiple MLS boards.
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