Realty_in_us

Name: Realty_in_us
Author: BACH-AI-Tools

@BACH-AI-Tools

Repository

About Realty_in_us

Realty In Us API

#realty #real-estate #api

Basic information

Config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "realty_in_us": {
      "command": "uvx",
      "args": [
        "--from",
        "bach-realty_in_us",
        "bach_realty_in_us"
      ],
      "env": {
        "API_KEY": "your_api_key_here"
      }
    }
  }
}

Tools

No tools detected

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is Realty_in_us?

Realty_in_us is an MCP server that provides access to the Realty In Us API, enabling real estate data queries for property listings, agent information, and mortgage tools.

How to use Realty_in_us?

Install the bach-realty_in_us package via pip or run directly using uvx without installation. Set the API_KEY environment variable for authentication. Use with Claude Desktop by adding a realty_in_us entry to claude_desktop_config.json. Alternatively, configure through the EMCP platform for a zero‑setup experience.

Key features of Realty_in_us

List properties for sale, rent, or sold with filters
Search for agents by location, name, or postal code
Get agent profiles, listings, recommendations, and reviews
Check mortgage rates, calculate affordability, and get finance rates
Quick setup via uvx or EMCP platform without manual config

Use cases of Realty_in_us

Search for homes for sale in a specific city or postal code
Find top‑rated real estate agents in a given area
Estimate monthly mortgage payments based on price, down payment, and interest rate
Compare current mortgage and equity loan rates by zip code
Access agent contact details and recent recommendations

FAQ from Realty_in_us

What data can I access with Realty_in_us?

It provides access to property listings (for sale, rent, sold), agent profiles, listings, recommendations, reviews, and mortgage/finance rate information through the Realty In Us API.

What are the runtime dependencies?

Python and the bach-realty_in_us package. An active internet connection and a valid API_KEY are required.

How do I authenticate?

Set the API_KEY environment variable with your API key before running the server.

What transport protocol does Realty_in_us use?

It uses stdio transport.

Can I use Realty_in_us without manual configuration?

Yes, the EMCP platform offers one‑click installation and management, eliminating the need to edit configuration files manually.

Comments

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