japan-real-estate-intel (sugukurukabe/japan-real-estate-intel-mcp) is an MCP server listed on the M8ven Trust Index. It scores 56 out of 100, grade D. It declares 24 tools. No publisher has claimed this listing.
| 地価トレンド予測 | 新宿区の5年後地価をAI予測。CAGR・投資シグナル付き | | 企業立地需要分析 | 名古屋市中区のオフィス・工場需要スコアを算出 | | ファミリー向け適性評価 | 横浜市西区の教育・安全・医療スコアを総合評価 | | ポートフォリオ最適化 | 東京・大阪・埼玉の3エリアに投資配分を最適化 | | What-If シナリオ分析 | 大阪市中央区で新駅開設シナリオを試算 | | 店舗出店適地評価 | 福岡市博多区の人流・商業施設・交通データで出店適性を判定 |
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The grade above is for the source repository. Registries can serve a different version, so we mark the ones we were not able to read.
These names and descriptions are the publisher's own, read from the source code. We print them as written. Our assessment is the findings above, not this list.
searchSearch the real estate data catalog for areas, tools, and data sources. ChatGPT-compatible. | 不動産データカタログを検索し、関連するエリア・ツール・データソースの候補一覧を返す。
fetchFetch full document by ID from search results. Returns area analysis, forecasts, and summaries in Markdown. | 検索結果のIDからドキュメント全文を取得する。分析レポート・将来予測・データサマリをMarkdownで返す。
search_area_candidatesSearch municipality name candidates by partial text. Supports hiragana. | 市区町村名の候補検索。部分文字列から有効な市区町村候補を返す。ひらがな対応。
cross_analyze_real_estate_marketCross-analyze real estate market: land price trends, investment score, foot traffic, education, corporate presence. 10 prefectures. | 不動産市場クロス分析。地価・投資スコア・人流・教育・企業立地を総合分析。10都道府県対応。
assess_property_riskAssess property disaster risk: flood, landslide, earthquake. Integrated scoring across 10 prefectures. | 災害リスク評価。浸水・土砂・地震リスクを統合スコアリング。全10都道府県対応。
assess_family_friendly_scoreAssess family-friendliness: education, safety, healthcare across 3 axes. 10 prefectures. | ファミリー向け適性評価。教育・安全・医療の3軸で住宅適地を総合評価。全10都道府県。
predict_corporate_demandPredict corporate demand: manufacturing, office, retail demand scores. 10 prefectures. | 企業立地需要予測。製造業・オフィス・小売の企業需要スコアを算出。全10都道府県。
generate_area_reportGenerate comprehensive area report in Markdown/PDF with branding support. 10 prefectures. | エリアレポート生成。包括的な不動産分析をMarkdown/PDFで出力。ブランディング対応。全10都道府県。
compare_prefecturesCompare up to 5 prefectures: land price, population, risk, investment score ranking. Markdown output. | 都道府県比較。最大5都道府県を横断比較し、地価・人口・リスク・投資スコアをランキング。
drill_down_local_analysisDrill-down local analysis at block/neighborhood level including foot traffic, commercial, education. Markdown output. | 街区ドリルダウン分析。町丁目レベルの詳細分析。Markdown出力。
evaluate_store_locationEvaluate store location suitability considering foot traffic, transport, competitor distribution. 10 prefectures. | 店舗出店適地評価。人流・交通・競合店分布を考慮したスコアを算出。全10都道府県。
simulate_landscape_impactSunlight/shadow simulation using PLATEAU 3D buildings + SunCalc. | 日照・影シミュレーション。PLATEAU 3D建物データ+SunCalcで周辺建物の影響を分析。
assess_exterior_visualsAI visual exterior audit of a property using the Google Maps Street View Static API (https://developers.google.com/maps/documentation/streetview) and Google Gemini Vision (https://ai.google.dev/gemini-api/docs/vision) for image analysis. Falls back to a simulated audit if GOOGLE_MAPS_API_KEY/GOOGLE_…
analyze_commute_accessibilityTransit commute accessibility analyzer to regional station hubs, using the Google Maps Distance Matrix API (https://developers.google.com/maps/documentation/distance-matrix). Calculates travel times, routes, and overall score. | 交通通勤アクセシビリティ評価。Google Maps Distance Matrix APIで主要ターミナル駅への所要時間・経路・利便性スコア…
forecast_land_price_trendForecast land price trends using linear regression and moving average. Returns CAGR, confidence interval, investment signal (buy/hold/caution). 10 prefectures. | 地価トレンド予測。線形回帰・移動平均で将来地価を予測。CAGR・投資シグナルを返す。全10都道府県。
scenario_what_ifWhat-If scenario analysis: simulate impact of new stations, commercial facilities, population changes on land prices and investment scores. 10 prefectures. | シナリオWhat-If分析。新駅・大型商業施設・人口変動の地価影響を試算。全10都道府県。
portfolio_optimizerOptimize real estate investment portfolio across up to 5 areas. Returns expected return, risk score, Sharpe ratio. | 不動産投資ポートフォリオ最適化。最大5エリアのリターン・リスク・シャープレシオを算出。
simulate_aichi_futureAichi future value simulator: Linear Chuo Shinkansen, Centrair 2nd runway, Toyota EV investment, Expo legacy impact on land prices. Markdown report. | 愛知県将来価値シミュレーター。リニア・セントレア・トヨタ・万博レガシーの地価影響をMarkdownレポートで出力。
analyze_renovation_yieldRenovation yield analysis: calculate acquisition cost, renovation cost, expected rent, gross/net yield for Nagoya neighborhoods. Includes future plan upside. | リノベ利回り分析。名古屋市の町丁目×物件条件から取得価格・リノベ費用・利回りを算出。
get_future_timelineFuture timeline: upcoming redevelopment, infrastructure, and population projections for Nagoya wards/neighborhoods (2025-2050). | 未来タイムライン。名古屋市の区・町丁目に影響する将来計画を年次タイムラインで返す。
get_chochou_profileNeighborhood profile: current metrics (land price, population, households, ongoing plans) for Nagoya wards/neighborhoods. | 町丁目プロファイル。名古屋市の区・町丁目単位の現状指標を返す。
recommend_renovation_targetsRenovation yield ranking: scan all 16 Nagoya wards to rank neighborhoods by yield. | リノベ利回りランキング。名古屋市全16区の主要町丁目を横断スキャンし利回り上位をランキング。
generate_contract_support_packageContract support package: generate risk matrix, price negotiation anchors, recommended clauses from neighborhood/property data. Returns a downloadable Markdown report via resource_link. | 売買契約支援パッケージ。リスクマトリックス・価格交渉アンカー・推奨特約を生成。Markdownレポートをresource_linkとしてダウンロード可能。
assess_contract_riskContract risk assessment: analyze proposed clauses (financing contingency, inspection, future value terms) and return risk score with deal-breakers. | 契約リスク評価。提案中の契約条項を分析しリスクスコアとディールブレーカーを返す。
Disclosed vulnerabilities in this server's declared npm dependencies (via OSV). Whether each is reachable depends on the installed versions.
@modelcontextprotocol/sdk has cross-client data leak via shared server/transport instance reuse
Anthropic's MCP TypeScript SDK has a ReDoS vulnerability
Model Context Protocol (MCP) TypeScript SDK does not enable DNS rebinding protection by default
Prototype Pollution in sheetJS
SheetJS Regular Expression Denial of Service (ReDoS)
API_KEY~50 tool calls / month (UTC), applies to both the public https://realestate-mcp.jp connector (per MCP session) and self-hosted stdio (per client) — see TIER_MONTHLY_TOOL_CALLS. Pro/Enterprise unlock via license key, no relation to API_KEYARTIFACT_DB_PATHARTIFACT_DIRARTIFACT_TTL_HOURSBQ_DATASETDEFAULT_TIERGCP_PROJECTGOOGLE_GENAI_API_KEYGOOGLE_MAPS_API_KEYHOSTLICENSE_DB_PATHLICENSE_KEYLICENSE_PRIVATE_KEY_PEMLICENSE_SERVER_URLLOG_LEVELMCP_PUBLIC_URLMETRICS_KEYMLIT_API_KEYRun npm run data:fetch (requires MLIT_API_KEY / ESTAT_APP_ID for live sources) — recommend quarterly refresh for productionRATE_LIMIT_ENABLEDRATE_LIMIT_MAXRATE_LIMIT_WINDOW_MSSESSION_TIMEOUT_MSSTRIPE_SECRET_KEYSTRIPE_WEBHOOK_SECRETTIER_MONTHLY_TOOL_CALLS~50 tool calls / month (UTC), applies to both the public https://realestate-mcp.jp connector (per MCP session) and self-hosted stdio (per client) — see TIER_MONTHLY_TOOL_CALLS. Pro/Enterprise unlock via license key, no relation to API_KEYUSAGE_CLIENT_IDUSAGE_DB_PATHPORTSENTRY_DSNProduction dependencies are patched
0 critical, 5 high severity in production deps — @modelcontextprotocol/sdk@1.12.1 (high), @modelcontextprotocol/sdk@1.12.1 (high)
Run npm audit fix, or upgrade the affected packages to a non-vulnerable version.
Dependency freshness
1/20 production deps stale: topojson-client@2022-06-27 (4.2y)
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