Real estate technology is booming, but building proptech tools means wrestling with fragmented data sources, MLS feeds, and property APIs that each have their own quirks. Claude Code with the right MCPs can streamline the entire development process.
The Challenge
Proptech developers face:
- Fragmented data — property data lives across MLS systems, county records, Zillow, Redfin, and private databases with no universal standard
- Complex search — building property search with filters for location, price, bedrooms, lot size, school districts, and dozens of other criteria
- Valuation models — comparable sales analysis requires pulling and processing large amounts of historical transaction data
- Agent workflows — CRM features, showing schedules, and offer management need tight integration with calendars and communication tools
MLS API MCP: Property Data in Your Terminal
The MLS API MCP connects Claude Code to MLS and property data APIs, letting you explore listings, comparables, and market data interactively while building your proptech features.
{
"mcpServers": {
"mls-api": {
"command": "npx",
"args": ["-y", "@anthropic-community/mcp-mls"],
"env": {
"MLS_API_KEY": "<YOUR_API_KEY>",
"MLS_REGION": "us-west"
}
}
}
}Available Tools
- search_listings — query active listings with filters (price range, beds, baths, location, property type)
- get_listing_detail — fetch full property details including photos, history, and tax records
- get_comparables — find comparable sales for valuation within a radius and time range
- get_market_stats — retrieve market statistics (median price, days on market, inventory) for a zip code or area
- search_agents — look up listing and buyer agents by name or MLS ID
Workflow: Building a CMA Tool
A Comparative Market Analysis (CMA) tool is a core feature for any real estate platform. Here's how to build one with Claude Code:
1. MLS API MCP — Claude queries recent comparable sales within a radius of the subject property, filtering by property type, square footage range, and time frame. It analyzes the data and generates a pricing recommendation.
2. PostgreSQL MCP — store historical CMA reports and property data for trend analysis. Claude writes the schema with proper indexing for geo-queries.
3. Slack MCP — notify agents when a new CMA is ready or when a property they're tracking has a price change.
4. Google Calendar MCP — automatically schedule property showings based on availability windows.
Building a Property Alert System
Combine the MLS API MCP with a cron job to monitor new listings:
1. Query new listings matching saved search criteria every hour 2. Compare against previously seen listings in your database 3. Send Slack notifications to interested agents or buyers 4. Log all alerts for compliance and audit purposes
More Resources on claudemcp.io
- MLS API MCP — property listings, comparables, and market stats
- PostgreSQL MCP — database operations for property data
- Slack MCP — team notifications and agent communication
- Google Calendar MCP — scheduling showings and open houses
Get Started
Browse all resources at claudemcp.io/browse or read the setup guide.