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Japan Real Estate Intel

Analyze Japanese property markets across 10 prefectures using land, risk, demographic, mobility, and renovation data.

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Install Japan Real Estate Intel

Pick your client, then add it in one click or paste the config.

STDIONode.js
~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "japan-real-estate-intel": {
      "command": "npx",
      "args": [
        "-y",
        "@sugukuru/japan-real-estate-intel-mcp"
      ]
    }
  }
}

Settings → Developer → Edit Config, merge this into mcpServers, then fully quit and reopen Claude Desktop.

Install not yet sandbox-tested— we haven't run this command through our automated sandbox yet. Not a red flag; we're working through the catalog.

Overview

Japan Real Estate Intel MCP server provides 38 tools for analyzing Japanese real estate across 10 prefectures. It combines land prices, transaction and route-value data, disaster risk, demographics, foot traffic, education, corporate presence, zoning, vacancy, transport, and other datasets. Use it through a local stdio process launched with npx or the public MCP endpoint, with free, Pro, and Enterprise access tiers. Reach for it when an agent needs area screening, price-trend analysis, risk assessment, renovation yield analysis, or related property research.

Use cases

  • Find investment-oriented areas within a supported prefecture
  • Forecast land-price trends for a city or prefecture
  • Compare transaction, route-value, and official land-price signals
  • Assess disaster, demographic, zoning, and vacancy conditions
  • Evaluate renovation yield or commercial location suitability

Key features

  • 38 real estate analysis tools
  • Coverage across 10 Japanese prefectures
  • Land-price and transaction analysis
  • Disaster, demographic, mobility, and facility datasets
  • 2D maps and PLATEAU 3D views
  • Free, Pro, and Enterprise access tiers

Security & health

What it can reach and how reliably it runs — from our own checks, not the maintainer’s claims.

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Scanned 8d ago via OSV.dev · @sugukuru/japan-real-estate-intel-mcp (npm)

Adoption & maintenance

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GitHub stars1Stargazers on the source repository.
npm downloads210Package downloads in the last 30 days.
Last commit24d agoMost recent push to the default branch.

How Japan Real Estate Intel works

What Japan Real Estate Intel does

Japan Real Estate Intel MCP server gives MCP-compatible clients access to Japanese real estate research tools covering 10 prefectures: Aichi, Tokyo, Osaka, Fukuoka, Hokkaido, Kanagawa, Kyoto, Hyogo, Saitama, and Chiba. Its 38 tools support market analysis, investment-area discovery, land-price forecasting, disaster-risk review, demographic analysis, vacancy and zoning research, renovation yield assessment, contract support, and building-code compliance audits.

The underlying coverage includes land prices, route values (rosenka), transaction information, earthquake and flood hazards, population and population projections, foot traffic, education, corporate locations, transport, commercial and medical facilities, and PLATEAU 3D building data. The project also provides a dashboard with 2D maps, 3D views, widgets, and price-triangulation features.

How it works

The server can run locally over stdio or remotely through https://realestate-mcp.jp/mcp. A local client starts it with the npm package, while a remote MCP configuration points directly to the public endpoint. The public connector does not require login, headers, or an API key.

Data is primarily supplied through bundled CSV files. The repository documents a refresh process using npm run data:fetch; live-source updates require the relevant credentials. An optional MLIT key can provide fresher transaction data for tools such as detect_arbitrage_signals, while an e-Stat application ID is listed for live data collection. Production users should account for the documented quarterly refresh recommendation and the fact that coverage is limited to 10 prefectures rather than all of Japan.

Japan Real Estate Intel MCP server uses tiered access. The Free tier allows approximately 50 tool calls per month in UTC, with the limit applying to both the public connector and self-hosted stdio use. Pro and Enterprise features require a license key passed through the supported license argument or header; that key is separate from a self-hosted API key.

Setup and configuration

For a local installation, use Node.js 20 or newer and run:

Terminal
npx @sugukuru/japan-real-estate-intel-mcp

Claude Desktop can use the local command or the remote MCP URL. Cursor can use the same npm command in its .cursor/mcp.json configuration. The public remote endpoint is suitable when avoiding a local installation. If you self-host and set API_KEY, clients must provide the corresponding API-key header. This is unrelated to the license key used to unlock paid tiers.

Optional data-update configuration includes MLIT_API_KEY and ESTAT_APP_ID. They are not required for the basic public connector or the standard local startup command. Generated reports and tabular artifacts can be exposed as downloadable resource links, using HTTP artifact paths for remote operation and artifact:// links for stdio operation.

Tools and capabilities

Key tool areas include:

  • Discovering investment-oriented areas and comparing local opportunities.
  • Forecasting land-price trends and reviewing macro conditions by prefecture.
  • Detecting price discrepancies using route values, official land prices, and transaction prices.
  • Assessing disaster exposure, population outlook, vacancy, zoning, education, mobility, and commercial context.
  • Estimating renovation yield and supporting contract-related workflows.
  • Evaluating corporate demand, family suitability, store locations, portfolios, and what-if scenarios where the selected tier permits them.
  • Reviewing building-code compliance and using PLATEAU-based 3D building views.

Tool descriptions and the interface support English and Japanese. MCP Apps UI support is documented for Claude Desktop and Cursor.

Limitations and notes

Coverage is limited to the 10 listed prefectures, and data freshness depends on the bundled files or an operator’s refresh process. Optional live-source credentials do not expand the geographic coverage stated in the repository. Free-tier limits also apply to self-hosted stdio usage, so local deployment does not automatically remove quota restrictions.

Paid-only tools should not be assumed to work on the default Free plan. The README specifically identifies PDF reports, Linear numeric simulation, and contract tools as requiring Pro, and lists additional Pro or Enterprise examples such as portfolio optimization, corporate-demand prediction, family-friendly scoring, scenario analysis, and store-location evaluation. Check the configured tier before building workflows around those capabilities.

Read the full README View source on GitHub

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Frequently Asked Questions about Japan Real Estate Intel

Japan Real Estate Intel is an MCP server that connects AI clients to Japanese real estate datasets across 10 prefectures. Its main tools analyze land prices, transactions, disaster risk, population, foot traffic, zoning, vacancy, forecasts, renovation yield, and price discrepancies, with local stdio and public remote MCP access.

Install it by running `npx @sugukuru/japan-real-estate-intel-mcp` with Node.js 20 or newer. Add that command to an MCP client such as Claude Desktop or Cursor, or configure the remote endpoint `https://realestate-mcp.jp/mcp` without login or headers.

Yes, Japan Real Estate Intel works with Cursor through a `.cursor/mcp.json` configuration. Set the server command to `npx` and pass `@sugukuru/japan-real-estate-intel-mcp` as its argument, or configure the documented remote MCP URL.

It supports Aichi, Tokyo, Osaka, Fukuoka, Hokkaido, Kanagawa, Kyoto, Hyogo, Saitama, and Chiba. The repository states that the bundled coverage does not include all 47 Japanese prefectures.

The basic server startup does not require environment variables. `MLIT_API_KEY` enables fresher MLIT transaction data, and `ESTAT_APP_ID` is used for live e-Stat data collection. A self-hosted deployment may set `API_KEY` for connector authentication.

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