Server detail
apillow-mcp bridges the gap between LLM reasoning and real-world real estate intelligence by exposing granular Zillow datasets through the Model Context Protocol. Instead of relying on outdated training data or brittle web scraping scripts, developers can integrate this tool to give AI agents direct access to live property metrics. It supports high-fidelity queries, including ZIP-based searches, specific address lookups, and deep dives into historical pricing and Zestimates. For developers building autonomous real estate agents, investment analysis tools, or localized market bots, this provides a structured way to ingest over 50 distinct data fields per listing. Unlike general search tools that return messy HTML, apillow-mcp delivers clean, schema-ready property data, making it significantly easier to build reliable workflows for mortgage calculations, market trend analysis, or property management automation.
An MCP server that exposes apillow-mcp capabilities to MCP-compatible AI clients.
Collections featuring this MCP
Tool testing
apillow-mcp
Call the MCP capabilities provided by apillow-mcp and return a structured result.
inputPass arguments according to the server tool schema.Connection modes
{
"mcpServers": {
"apillow-mcp": {
"url": "Generated by the provider after deployment"
}
}
}The Remote endpoint is generated by the provider after deployment; this page does not fabricate an unusable endpoint.
No npm package is recorded. Open the source repository to complete command and args.If no npm package is registered, follow the installation method in the source repository.
How to use
- 01Step 1
Review server capabilities and permission scope.
- 02Step 2
Copy the install command or JSON configuration.
- 03Step 3
Run a small connection test in your client.
- 04Step 4
Adopt it long term only after reviewing access and maintenance.
Discussions
Use this space to keep checking source information, usage experience and maintenance status.
Open source page