MCP server

Realtystack

io.github.IsaiahDupree/realtystack-mcp

Checked 26 Oct 2026, 08:29 UTC · Connected to it and listed its tools

U.S. real-estate data: property records, AVM value + rent estimates, sale/rental listings.

Website Source

At a glance

Type

MCP server

Publisher

Not verified

Status

Working at last check

Tools

6

Token cost

About 3,438 tokens per request

Sets up in

Claude Code, Claude Desktop, Codex, Gemini CLI, Cursor, VS Code, Antigravity, ChatGPT, OpenAI API, Grok

Last checked

26 Oct 2026, 08:29 UTC

Connect it to your agent

Add to CursorAdd to VS CodeVS Code Insiders

Opens the app, which shows the server and asks you to confirm. For other apps, copy the setup below.

Claude Code

claude mcp add --transport http realtystack-mcp https://realtystack-mcp.vercel.app/mcp

Claude Desktop

Settings → Connectors → Add custom connector, and paste the URL.

Codex (config.toml)

[mcp_servers.realtystack-mcp]
url = "https://realtystack-mcp.vercel.app/mcp"

Gemini CLI

{"mcpServers":{"realtystack-mcp":{"httpUrl":"https://realtystack-mcp.vercel.app/mcp"}}}

Cursor

{"mcpServers":{"realtystack-mcp":{"url":"https://realtystack-mcp.vercel.app/mcp"}}}

VS Code

{"servers":{"realtystack-mcp":{"type":"http","url":"https://realtystack-mcp.vercel.app/mcp"}}}

Antigravity

agy mcp add realtystack-mcp https://realtystack-mcp.vercel.app/mcp

ChatGPT

Settings → Apps & Connectors → Advanced settings: turn on Developer mode, then Create a connector and paste the URL. Which plans can do this varies.

OpenAI API (Responses tools)

{"type":"mcp","server_label":"realtystack-mcp","server_url":"https://realtystack-mcp.vercel.app/mcp","require_approval":"always"}

Grok (xAI API tools)

{"type":"mcp","server_label":"realtystack-mcp","server_url":"https://realtystack-mcp.vercel.app/mcp"}

Tools

• avm_rent ~546 tokens
  Run RentCast's automated model for long-term (12-month lease) rent and return a point rent estimate, a rentRangeLow/rentRangeHigh band, the resolved subjectProperty, and comparables[] — recent comparable rentals each scored with distance and correlation. Same subject-pinning rules as avm_value (addr
• avm_value ~585 tokens
  Run RentCast's automated valuation model for a subject property and return a point price estimate, a priceRangeLow/priceRangeHigh band, the resolved subjectProperty, and comparables[] — recent comparable sales each scored with a distance (miles) and correlation (0-1 similarity). Pin the subject with
• get_property ~163 tokens
  Full detail for a single property record, keyed by its RentCast id (the same id returned on every search_properties, avm_value, avm_rent, and listings record). Returns 404 if no property matches the id. Cached 24h upstream.
• search_properties ~714 tokens
  Search normalized U.S. property records (owner, structural attributes, tax assessments, tax + sale history) by location. Pin a location one of three ways: a full address, a city+state(+zipCode), or a latitude+longitude point with a radius (miles). All other parameters narrow the result set. Records
• search_rental_listings ~698 tokens
  Return a page of long-term (12-month lease) rental listings — same record shape as search_sale_listings (monthly price is the asking rent), but each record is tagged listingKind:"rental-long-term". Same location-pinning rules and 30-minute upstream cache as the sale-listings endpoint.
• search_sale_listings ~732 tokens
  Return a page of for-sale listings (list price, status, days on market, MLS name/number, listing agent + office contact, and price/status history) for a location. Same location-pinning rules as search_properties (address, city+state(+zipCode), or latitude+longitude+radius). Each record is tagged lis

Browse

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• GitHub and code hosting

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