RE Data Refinery MCP Server

RE Data Refinery MCP Server

Turns messy real estate data into clean, scored, AI-ready property intelligence for Columbus, OH metro, with pay-per-query via x402 micropayments. Enables natural-language search, investment scoring, and enrichment tools for MCP clients.

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README

RE Data Refinery MCP Server

A Model Context Protocol (MCP) server that turns messy real estate data into clean, scored, AI-ready property intelligence for Columbus, OH and surrounding metro cities.

Unlike generic property APIs, the RE Data Refinery combines live Zillow data with county-level enrichment (GIS, tax delinquency, sheriff sales, permits, probate records) and computes proprietary investment scores for every listing. Agents pay only for the queries they run — no subscriptions, no API tiers — via the x402 micropayment protocol on Base mainnet.

  • Live data source: ZillAPI
  • Coverage: 150+ properties seeded across 14 Columbus metro cities
  • Payment: USDC on Base, $0.35 per paid lookup
  • Transport: stdio / SSE for Claude Desktop, Claude Code, ChatGPT Desktop, Hermes, and other MCP clients

What makes it different

Feature RE Data Refinery BatchData / USDV Capital
Pricing Pay per query via x402 (no subscription) Free tiers or monthly subscriptions
Scoring Flip, wholesale, rental yield, market heat Usually absent or generic
Enrichment County GIS, tax delinquency, sheriff sales, permits, probate Typically surface-level listing data
On-chain settlement USDC on Base via Permit2 + CDP facilitator Not applicable

Tools (10)

Tool Description Price
refinery_health API health, cached property count, rate limit status Free
refinery_credits Upstream ZillAPI credit balance Free
refinery_properties List scored properties by city with optional price filters $0.35 (live), free (cached)
refinery_property_detail Full scored detail for a single property by ZPID $0.35
refinery_property_price_history Price/transaction timeline for a property $0.25
refinery_property_tax_history Tax and assessment history for a property $0.25
refinery_property_schools School ratings near a property $0.25
refinery_search Natural-language property search $0.50
refinery_scored_search Search filtered/scored by investment criteria $0.50
refinery_payment_status Show x402 configuration and active API base URL Free

Quick start

1. Install dependencies

pip install "x402>=2.20.0" eth-account httpx

2. Clone the repository

git clone https://github.com/areshms/re-refinery-mcp.git
cd re-refinery-mcp

3. Configure your environment

Create a .env file in the project root:

# Required for paid Worker lookups
EVM_PRIVATE_KEY=0x...

# Optional
X402_SPEND_CAP=$1                    # max per-payment USD cap (default: $1)
REFINERY_BASE_URL=https://re-data-refinery.ares-hms.workers.dev
REFINERY_LOCAL_URL=http://localhost:5004

Your wallet must hold USDC on Base to pay for lookups.

4. Add to your MCP client

Claude Desktop / Claude Code:

{
  "mcpServers": {
    "re_refinery_mcp": {
      "command": "python3",
      "args": ["/path/to/re-refinery-mcp/re_refinery_mcp.py"],
      "env": {
        "EVM_PRIVATE_KEY": "${EVM_PRIVATE_KEY}",
        "X402_SPEND_CAP": "$1"
      }
    }
  }
}

Local development mode

To develop or test without spending USDC, disable x402 and point at a free local API:

export REFINERY_ENABLE_X402=false
export REFINERY_LOCAL_URL=http://localhost:5004
python3 re_refinery_mcp.py --transport stdio

Paid endpoints then call localhost:5004 instead of the Worker.


How payments work

  1. Your agent requests a paid endpoint.
  2. The Worker responds with HTTP 402 Payment Required and an x402 payment requirement.
  3. The MCP client signs a Permit2 USDC transaction on Base.
  4. The CDP facilitator verifies the signature and settles the payment on-chain.
  5. The Worker returns the requested data.

All of this is handled automatically once EVM_PRIVATE_KEY is configured.


Scoring methodology

Every property is enriched with:

  • flip_score (0–100): discount vs. Zestimate, days on market, neighborhood median, age, lot size
  • wholesale_score (0–100): equity spread, tax delinquency, DOM, owner-occupancy, price vs. Zestimate
  • rental_yield_pct: annual rent estimate ÷ price
  • market_heat: Hot / Warm / Cool based on days on market and recent price trend

Scores are recomputed against neighborhood medians drawn from the live-refinery cache.


Requirements

  • Python 3.11+
  • x402>=2.20.0
  • eth-account
  • httpx
  • A wallet with USDC on Base mainnet

Worker

The Cloudflare Worker backing this server is deployed at:

https://re-data-refinery.ares-hms.workers.dev

It is the first real estate data refinery using Cloudflare's x402 monetization gateway.


License

MIT


Built by Hightower Marketing — making real estate data work for AI agents.

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