Japan Real Estate Intel

REMOTE · REALESTATE-MCP.JP · 2 COMPONENTS · SCANNED AUG 3

Japan real estate MCP: land price, risk, foot traffic, renovation. 10 prefectures.

Available components

remote · realestate-mcp.jp 46 npm · @sugukuru/japan-real-estate-intel-mcp 35

+15 this week 46 46 Trust /100

Trust breakdown (6 categories)

How this component scores in each security and reliability category. Every signal is checked automatically against the live server, and we only credit what we can confirm. How we score →

Endpoint Security89

The endpoint's TLS certificate is valid, in date, and uses a strong key. View diagnostics → Pass
The endpoint enforces authorisation, but returns a challenge with no valid RFC 9728 metadata, so a client cannot discover where to get a token. See how to fix → View diagnostics → Fail
HTTPS is enforced; there's no plaintext access path. View diagnostics → Pass
The HSTS (Strict-Transport-Security) header is present. View diagnostics → Pass
DNSSEC check failed: this domain isn't protected by DNSSEC. See how to fix → View diagnostics → Fail

Transport & Reachability100

Verified streamable-http transport via a live MCP handshake. View diagnostics → Pass

Schema Quality & AI Usability0

Schema blocked by authentication: the endpoint requires auth we don't have to read it. See how to fix → Unverified

Stability & Change Management0

Stability not yet verified: not enough scan history yet (needs a 30-day window).Unverified

Tool Coverage0

Tool coverage blocked by authentication: the endpoint requires auth we don't have to read its tools.Unverified

Capabilities0

Capabilities blocked by authentication: the endpoint requires auth we don't have to read them. See how to fix → Unverified

Unverified: 4 categories

Categories scored 0 because we could not verify them: authentication we do not have, an unreachable endpoint, or not enough scan history. We only credit what we can confirm.

Install

Add this component to your MCP client. Where a client-specific snippet is available, pick your client below and copy it straight into your config; otherwise use the connection detail shown.

remote · realestate-mcp.jp

Claude Codex opencode OpenClaw Hermes Other

# add to Claude Code

claude mcp add --transport http sugukurukabe-japan-real-estate-intel-mcp https://realestate-mcp.jp/mcp

# ~/.codex/config.toml

[mcp_servers.sugukurukabe-japan-real-estate-intel-mcp]
url = "https://realestate-mcp.jp/mcp"

// opencode.json

{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "sugukurukabe-japan-real-estate-intel-mcp": {
      "type": "remote",
      "url": "https://realestate-mcp.jp/mcp",
      "enabled": true
    }
  }
}

# add to OpenClaw

openclaw mcp add sugukurukabe-japan-real-estate-intel-mcp --url https://realestate-mcp.jp/mcp --transport streamable-http

# ~/.hermes/config.yaml

mcp_servers:
  sugukurukabe-japan-real-estate-intel-mcp:
    url: "https://realestate-mcp.jp/mcp"

// mcp.json

{
  "mcpServers": {
    "sugukurukabe-japan-real-estate-intel-mcp": {
      "type": "http",
      "url": "https://realestate-mcp.jp/mcp"
    }
  }
}

The mcpServers block is a cross-client convention. Remote transports vary, so check your client's docs.

Changelog

Every change we have recorded for this component, newest first. Security-relevant changes are always shown. ▲ marks a change for the better, ▼ a change for the worse; unmarked changes are neutral.

3 Aug 26 −24
- Endpoint reachability: reachable → behind authorisation ▼ security
- Stability: fail → unverified ▼ security
- Authorization: partial → fail ▼ security
- Capabilities: pass → unverified ▼ functional
- Tool coverage: 100 → unverified ▼ functional
- Schema quality: 100 → unverified ▼ functional
2 Aug 26 −7
- Authorization: fail → unverified ▼ security
- Stability: 0.20 → fail ▼ security
- A breaking change shipped without a version bump: still 6.16.0 ▼ security
- Tool “get_zoning_info” was removed ▼ security
- Tool “open_dashboard” was removed ▼ security
- Tool “portfolio_optimizer” was removed ▼ security
- Tool “predict_corporate_demand” was removed ▼ security
- Tool “quick_visual_summary” was removed ▼ security
- Tool “recommend_renovation_targets” was removed ▼ security
- Tool “review_purchase_recommendation” was removed ▼ security
- Tool “scenario_what_if” was removed ▼ security
- Tool “search” was removed ▼ security
- Tool “search_area_candidates” was removed ▼ security
- Tool “simulate_landscape_impact” was removed ▼ security
- Tool “simulate_leveraged_cashflow” was removed ▼ security
- Tool “simulate_aichi_future” was removed ▼ security
- Tool “assess_contract_risk” was removed ▼ security
- Tool “assess_family_friendly_score” was removed ▼ security
- Tool “assess_property_risk” was removed ▼ security
- Tool “analyze_renovation_yield” was removed ▼ security
- Tool “compare_prefectures” was removed ▼ security
- Tool “composite_value_score” was removed ▼ security
- Tool “cross_analyze_real_estate_market” was removed ▼ security
- Tool “detect_arbitrage_signals” was removed ▼ security
- Tool “discover_opportunities” was removed ▼ security
- Tool “drill_down_local_analysis” was removed ▼ security
- Tool “evaluate_store_location” was removed ▼ security
- Tool “fetch” was removed ▼ security
- Tool “forecast_land_price_trend” was removed ▼ security
- Tool “generate_area_report” was removed ▼ security
- Tool “generate_contract_support_package” was removed ▼ security
- Tool “get_chochou_profile” was removed ▼ security
- Tool “get_future_timeline” was removed ▼ security
- Tool “get_population_outlook” was removed ▼ security
- Tool “get_real_estate_macro_snapshot” was removed ▼ security
- Tool “get_vacancy_stats” was removed ▼ security
- Authorization: fail → partial ▲ security
- Schema quality: fail → unverified ▼ functional
- Schema quality: good → unverified ▼ functional
- Schema quality: fail → unverified ▼ functional
- Tool coverage: 100 → unverified ▼ functional
- Prompt “aichi_future_value” was removed ▼ functional
- Prompt “arbitrage_scan” was removed ▼ functional
- Prompt “composite_value_report” was removed ▼ functional
- Prompt “investment_report” was removed ▼ functional
- Prompt “land_price_forecast_report” was removed ▼ functional
- Prompt “opportunity_radar” was removed ▼ functional
- Prompt “population_outlook_report” was removed ▼ functional
- Prompt “portfolio_optimization” was removed ▼ functional
- Prompt “prefecture_comparison” was removed ▼ functional
- Prompt “quick_start_examples” was removed ▼ functional
- Prompt “scenario_what_if_analysis” was removed ▼ functional
- Prompt “store_location_evaluation” was removed ▼ functional
- Prompt “vacancy_analysis” was removed ▼ functional
- Prompt “zoning_check” was removed ▼ functional
- New tool “drill_down_local_analysis” functional
- New tool “discover_opportunities” functional
- New tool “detect_arbitrage_signals” functional
- New tool “cross_analyze_real_estate_market” functional
- New tool “composite_value_score” functional
- New tool “compare_prefectures” functional
- New tool “assess_property_risk” functional
- New tool “assess_family_friendly_score” functional
- New tool “assess_contract_risk” functional
- New tool “analyze_renovation_yield” functional
- New tool “simulate_leveraged_cashflow” functional
- New tool “simulate_landscape_impact” functional
- New tool “simulate_aichi_future” functional
- New tool “search_area_candidates” functional
- New tool “search” functional
- New tool “get_future_timeline” functional
- New tool “get_chochou_profile” functional
- New tool “generate_contract_support_package” functional
- New tool “generate_area_report” functional
- New tool “forecast_land_price_trend” functional
- New tool “fetch” functional
- New tool “evaluate_store_location” functional
- New tool “scenario_what_if” functional
- New tool “review_purchase_recommendation” functional
- New tool “recommend_renovation_targets” functional
- New tool “quick_visual_summary” functional
- New tool “predict_corporate_demand” functional
- New tool “portfolio_optimizer” functional
- New tool “open_dashboard” functional
- New tool “get_zoning_info” functional
- New tool “get_vacancy_stats” functional
- New tool “get_real_estate_macro_snapshot” functional
- New tool “get_population_outlook” functional
1 Aug 26 +26
- Schema quality: unverified → fail ▼ functional
- Schema quality: unverified → fail ▼ functional
- Schema quality: unverified → good ▲ functional
- Tool coverage: unverified → 100 ▲ functional
- Stability: fail → 0.20 functional
- New prompt “land_price_forecast_report” functional
- New prompt “population_outlook_report” functional
- New prompt “zoning_check” functional
- New prompt “vacancy_analysis” functional
- New prompt “store_location_evaluation” functional
- New prompt “scenario_what_if_analysis” functional
- New prompt “quick_start_examples” functional
- New prompt “opportunity_radar” functional
- New prompt “prefecture_comparison” functional
- New prompt “portfolio_optimization” functional
- New prompt “investment_report” functional
- New prompt “composite_value_report” functional
- New prompt “arbitrage_scan” functional
- New prompt “aichi_future_value” functional
- New tool “generate_contract_support_package” functional
- New tool “analyze_renovation_yield” functional
- New tool “assess_contract_risk” functional
- New tool “assess_family_friendly_score” functional
- New tool “assess_property_risk” functional
- New tool “compare_prefectures” functional
- New tool “composite_value_score” functional
- New tool “cross_analyze_real_estate_market” functional
- New tool “detect_arbitrage_signals” functional
- New tool “discover_opportunities” functional
- New tool “drill_down_local_analysis” functional
- New tool “evaluate_store_location” functional
- New tool “fetch” functional
- New tool “forecast_land_price_trend” functional
- New tool “generate_area_report” functional
- New tool “get_chochou_profile” functional
- New tool “simulate_leveraged_cashflow” functional
- New tool “simulate_landscape_impact” functional
- New tool “simulate_aichi_future” functional
- New tool “search_area_candidates” functional
- New tool “search” functional
- New tool “scenario_what_if” functional
- New tool “review_purchase_recommendation” functional
- New tool “recommend_renovation_targets” functional
- New tool “quick_visual_summary” functional
- New tool “predict_corporate_demand” functional
- New tool “portfolio_optimizer” functional
- New tool “open_dashboard” functional
- New tool “get_zoning_info” functional
- New tool “get_vacancy_stats” functional
- New tool “get_real_estate_macro_snapshot” functional
- New tool “get_population_outlook” functional
- New tool “get_future_timeline” functional
31 Jul 26 +20
- We updated how we score, so this day's move reflects our rubric, not a change to the server See what changed → functional
30 Jul 26 0
- We updated how we score, so this day's move reflects our rubric, not a change to the server See what changed → functional
29 Jul 26 −9
- Prompt “prefecture_comparison” was removed ▼ functional
- Prompt “quick_start_examples” was removed ▼ functional
- Prompt “scenario_what_if_analysis” was removed ▼ functional
- Prompt “store_location_evaluation” was removed ▼ functional
- Prompt “vacancy_analysis” was removed ▼ functional
- Prompt “zoning_check” was removed ▼ functional
- Prompt “land_price_forecast_report” was removed ▼ functional
- Prompt “aichi_future_value” was removed ▼ functional
- Prompt “composite_value_report” was removed ▼ functional
- Prompt “arbitrage_scan” was removed ▼ functional
- Prompt “investment_report” was removed ▼ functional
- Prompt “opportunity_radar” was removed ▼ functional
- Prompt “population_outlook_report” was removed ▼ functional
- Prompt “portfolio_optimization” was removed ▼ functional
28 Jul 26 +9
- First check of Schema quality: 100 functional
- New prompt “quick_start_examples” functional
- New prompt “prefecture_comparison” functional
- New prompt “scenario_what_if_analysis” functional
- New prompt “zoning_check” functional
- New prompt “vacancy_analysis” functional
- New prompt “store_location_evaluation” functional
- New prompt “aichi_future_value” functional
- New prompt “arbitrage_scan” functional
- New prompt “composite_value_report” functional
- New prompt “investment_report” functional
- New prompt “land_price_forecast_report” functional
- New prompt “opportunity_radar” functional
- New prompt “population_outlook_report” functional
- New prompt “portfolio_optimization” functional
27 Jul 26 −33
- We updated how we score, so this day's move reflects our rubric, not a change to the server See what changed → functional

Show 6 earlier entries Hide earlier entries

Diagnostics

Diagnostic detail from the automated scan of this channel: what the scanner observed at each step, so you can see exactly where a check passed or failed. It is informational only and never changes the trust score.

Captured 3 Aug 2026 · Probed https://realestate-mcp.jp/mcp

TLS valid

Negotiated TLS 1.3 with TLS_AES_128_GCM_SHA256 .

Subject	Issuer	Valid from	Valid until	Key	Signature	Serial
CN=realestate-mcp.jp	CN=YR2,O=Let's Encrypt,C=US	27 Jul 2026	25 Oct 2026	RSA 2048	SHA256-RSA	6e85512bf77e6bcb2bc18e5483d393819d5
SANs: realestate-mcp.jp
CN=YR2,O=Let's Encrypt,C=US (CA)	CN=Root YR,O=ISRG,C=US	3 Sept 2025	2 Sept 2028	RSA 2048	SHA256-RSA	4ebd24947e24d394802d84a52fd5b319
CN=Root YR,O=ISRG,C=US (CA)	CN=ISRG Root X1,O=Internet Security Research Group,C=US	13 May 2026	2 Sept 2032	RSA 4096	SHA256-RSA	f24b6d17f9d9ad7cb1c9fea78782699f

DNSSEC insecure

Validation of realestate-mcp.jp. — Not signed

Zone	DS	Keys	Algorithms	Outcome
.	trust_anchor	20326, 38696	8, 8	Verified
jp.	present	33631	8	Verified
realestate-mcp.jp.	absent			Unsigned (proven) parent-signed NSEC/NSEC3 proves an unsigned delegation

Authentication Challenged, unverified

The endpoint asked for a token, but we could not retrieve and validate the RFC 9728 metadata that tells a client how to obtain one.

Result	Challenged, unverified
Enforced	On connection
HTTP status	401

Header	Value
strict-transport-security	max-age=31536000; includeSubDomains
x-content-type-options	nosniff
x-frame-options	SAMEORIGIN
referrer-policy	strict-origin-when-cross-origin

Protected resource metadata

Retrieved	No
Problem	no_resource_metadata

Transports 2 probes

Transport	URL	Outcome	Status	Location
streamable-http	https://realestate-mcp.jp/mcp	Verified	200
http (plaintext)	http://realestate-mcp.jp/mcp	HTTPS enforced	302	https://realestate-mcp.jp/mcp

MCP tools — 33 exposed · ~7,336 tokens

The tools this component advertises to a client, with an estimated token cost for each. Expand a tool to see its parameters and schema. The per-tool counts are indicative and are not scored directly; the schema's total context footprint is one signal in Schema Quality & AI Usability.

Tool Tokens

analyze_renovation_yield ~187

Renovation 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。

Input Output Examples

Name	Type	Req	Description
acquisitionPrice	number	—	取得予定価格 (円)。省略時は推定
buildingAge	number	yes	築年数
chochou	string	yes	町丁目名 (例: 栄三丁目, 名駅一丁目)
floorArea	number	yes	専有面積 (㎡)
propertyType	string	—	物件種別
ward	string	yes	名古屋市の区名 (例: 中区, 中村区)

No output schema declared.

No examples provided.

assess_contract_risk ~118

Contract 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。

Input Output Examples

Name	Type	Req	Description
chochou	string	—	町丁目名
proposedTerms	object	yes	提案中の契約条項（JSON 形式）
ward	string	yes	名古屋市の区名

No output schema declared.

No examples provided.

assess_family_friendly_score ~180

Assess 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。

Input Output Examples

Name	Type	Req	Description
address	string	—	具体的な住所（任意）
area	string	yes	エリア
childAge	string	—	—
latlng	object	—	—
neighborhood	string	—	町丁目（例: '名駅南1丁目'）。v2.4 では町丁目レベル実データに対応（対応都道府県のみ）
prefecture	string	—	都道府県名（和名/英名/ISO 3166-2 コード対応）

No output schema declared.

No examples provided.

assess_property_risk ~166

Assess 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。

Input Output Examples

Name	Type	Req	Description
address	string	yes	住所または地番
latlng	object	—	—
neighborhood	string	—	町丁目（例: '名駅南1丁目'）。v2.4 では町丁目レベル実データに対応（対応都道府県のみ）
prefecture	string	—	都道府県名（和名/英名/ISO 3166-2 コード対応）
riskTypes	array	—	—

No output schema declared.

No examples provided.

compare_prefectures ~245

Compare 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。

Input Output Examples

Name	Type	Req	Description
area	string	—	各都道府県の代表エリア（省略時は県庁所在地相当。愛知=名古屋市中区、東京=千代田区）
exportFormat	string	—	出力フォーマット。xlsx を指定すると xlsxBase64 フィールドに Base64 エンコード済み Excel を返す
includeMarkdown	boolean	—	—
metrics	array	—	—
neighborhood	string	—	町丁目（例: '名駅南1丁目'）。v2.4 では町丁目レベル実データに対応（対応都道府県のみ）
prefectures	array	yes	比較対象都道府県（2-5県）。例: ["愛知県", "東京都"]
propertyType	string	—	—

No output schema declared.

No examples provided.

composite_value_score 総合価値スコア ~319

Composite value score: fuse 5 axes (land price, education, transport, future plans, risk) into a single 0-100 score with radar, tier, peer comparison, and AI narrative. | 総合価値スコア。地価・教育・交通・将来計画・リスクを 1 つの 0-100 スコアに融合。レーダー・Tier・ピア比較・AIナラティブ付き。

Input Output Examples

Name	Type	Req	Description
area	string	yes	Target area (e.g. '名古屋市中区', '新宿区') \| 対象エリア
horizon	string	—	Analysis horizon \| 分析期間
includeMarkdown	boolean	—	Include Markdown report \| Markdown レポートを含む
includeNarrative	boolean	—	Generate AI narrative summary (requires Gemini API key) \| AI ナラティブ生成
output_mode	string	—	Output verbosity. compact=TL;DR + key numbers only (default), detailed=full Markdown report \| 出力詳細度。compact=主要数値のみ（デフォルト）、detailed=全文レポート付き
prefecture	string	—	都道府県名（和名/英名/ISO 3166-2 コード対応）
weights	object	—	Custom axis weights (defaults: 0.25/0.20/0.20/0.20/0.15) \| 軸の重み

Name	Type	Req	Description
attribution	string	yes	—
axes	array	yes	Per-axis scores with evidence
compositeScore	number	yes	Overall composite score 0-100
markdownReport	string	—	Full Markdown report
narrative	string	—	AI-generated executive summary (if Gemini available)
peerComparison	array	yes	Top/bottom peer cities for comparison
tier	string	yes	Tier rating: S(80+) A(65-79) B(50-64) C(<50)

No examples provided.

cross_analyze_real_estate_market ~425

Cross-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。

Input Output Examples

Name	Type	Req	Description
area	string	yes	エリア（例: '名古屋市中村区', '世田谷区'）
focusMetrics	array	—	—
includeCommercial	boolean	—	商業施設データを含むか（対応都道府県のみ）
includeCorporate	boolean	—	企業立地データを含むか（対応都道府県のみ）
includeEducation	boolean	—	教育環境データを含むか（対応都道府県のみ）
includeHumanFlow	boolean	—	人流データを含むか（対応都道府県のみ）
includeMedical	boolean	—	医療・福祉施設データを含むか（対応都道府県のみ）
includeRisk	boolean	—	災害リスクを考慮するか
includeTransport	boolean	—	交通利便性データを含むか（対応都道府県のみ）
neighborhood	string	—	町丁目（例: '名駅南1丁目'）。v2.4 では町丁目レベル実データに対応（対応都道府県のみ）
output_mode	string	—	Output verbosity. compact=TL;DR + key numbers only (default), detailed=full Markdown report \| 出力詳細度。compact=主要数値のみ（デフォルト）、detailed=全文レポート付き
prefecture	string	—	都道府県名（和名/英名/ISO 3166-2 コード対応）
propertyType	string	yes	—
timeRange	string	yes	—

No output schema declared.

No examples provided.

detect_arbitrage_signals 価格トライアングル・アービトラージスキャン ~277

Price triangulation arbitrage scanner: cross-checks 路線価(rosenka) × 公示地価(koji) × 取引価格(tx) to detect discount buys, inheritance-tax edges, and overheated markets. | 路線価・公示地価・取引価格の三角測量でディスカウント物件・相続有利エリア・市場過熱を検出する。

Input Output Examples

Name	Type	Req	Description
includeLive	boolean	—	Fetch latest MLIT transactions live (requires MLIT_API_KEY) \| ライブ取引価格取得
limit	integer	—	Max cities to return \| 最大返却市区町村数
output_mode	string	—	Output verbosity. compact=TL;DR + key numbers only (default), detailed=full Markdown report \| 出力詳細度。compact=主要数値のみ（デフォルト）、detailed=全文レポート付き
prefecture	string	—	都道府県名（和名/英名/ISO 3166-2 コード対応）
signalType	string	—	Filter by signal type: 'discount' \| 'inheritance_edge' \| 'overheated' \| 'fair' \| omit for all \| シグナル種別フィルター

Name	Type	Req	Description
attribution	string	yes	—
benchmark	object	yes	比較用ベンチマーク
dataYear	number	yes	データ年次
items	array	yes	検出シグナル一覧
liveDataUsed	boolean	yes	MLIT ライブ取引データ使用
markdownReport	string	yes	Markdown 形式の分析レポート
prefecture	string	yes	—
scannedCities	number	yes	スキャンした市区町村数

No examples provided.

discover_opportunities Opportunity Radar ~327

Opportunity Radar: scan a prefecture for undervalued areas matching your goal (investment/store/family/office/development). Returns hypothesis cards with multi-source scoring. | Opportunity Radar。都道府県内を横断スキャンし、目的に応じた次に見るべきエリア仮説カードを返す。

Input Output Examples

Name	Type	Req	Description
budgetLevel	string	—	想定予算帯。low=㎡15万以下, middle=15-50万, high=50万超
goal	string	—	探索目的
horizon	string	—	—
includeExternalFreshness	boolean	—	true かつ MLIT_API_KEY 環境変数があるとき、MLIT API から最新取引を取得しシグナルに反映
includeMarkdown	boolean	—	—
limit	integer	—	返却する候補数
output_mode	string	—	Output verbosity. compact=TL;DR + key numbers only (default), detailed=full Markdown report \| 出力詳細度。compact=主要数値のみ（デフォルト）、detailed=全文レポート付き
prefecture	string	—	都道府県名（和名/英名/ISO 3166-2 コード対応）
riskTolerance	string	—	—
useGeminiNarrative	boolean	—	true かつ GOOGLE_GENAI_API_KEY があるとき、Gemini でカードに creativeAngle と質問候補を追加

Name	Type	Req	Description
attribution	string	yes	—
cards	array	yes	—
dataCoverage	object	yes	—
markdownReport	string	—	—
nextActions	array	yes	—
summary	string	yes	—

No examples provided.

drill_down_local_analysis ~192

Drill-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。

Input Output Examples

Name	Type	Req	Description
city	string	yes	市区町村（例: '名古屋市中村区'）
exportFormat	string	—	出力フォーマット。xlsx を指定すると xlsxBase64 フィールドに Base64 エンコード済み Excel を返す
focus	string	—	—
neighborhood	string	—	町丁目（例: '名駅南1丁目'）。v2.4 では町丁目レベル実データに対応（対応都道府県のみ）
prefecture	string	—	都道府県名（和名/英名/ISO 3166-2 コード対応）

No output schema declared.

No examples provided.

evaluate_store_location ~231

Evaluate 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。

Input Output Examples

Name	Type	Req	Description
city	string	yes	市区町村（例: '名古屋市中村区'）
customWeights	object	—	カスタム重み付け（省略時はタイプ別デフォルト）
includeMarkdown	boolean	—	—
neighborhood	string	—	町丁目（例: '名駅南1丁目'）。v2.4 では町丁目レベル実データに対応（対応都道府県のみ）
prefecture	string	—	都道府県名（和名/英名/ISO 3166-2 コード対応）
radiusM	number	—	競合・施設を検索する半径（メートル）
storeType	string	yes	出店を検討する店舗タイプ

No output schema declared.

No examples provided.

fetch ~100

Fetch 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。

Input Output Examples

Name	Type	Req	Description
id	string	yes	search ツールで取得したドキュメントID（例: "area:aichi:名古屋市中区"）

No output schema declared.

No examples provided.

forecast_land_price_trend ~266

Forecast 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。

Input Output Examples

Name	Type	Req	Description
city	string	yes	市区町村（例: '名古屋市中村区', '世田谷区'）
horizon	string	—	予測期間
includeMarkdown	boolean	—	—
landUse	string	—	地目フィルター。all=全地目平均
method	string	—	予測手法。linear=線形回帰、moving_avg=移動平均外挿
output_mode	string	—	Output verbosity. compact=TL;DR + key numbers only (default), detailed=full Markdown report \| 出力詳細度。compact=主要数値のみ（デフォルト）、detailed=全文レポート付き
prefecture	string	—	都道府県名（和名/英名/ISO 3166-2 コード対応）

No output schema declared.

No examples provided.

generate_area_report ~342

Generate 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。

Input Output Examples

Name	Type	Req	Description
agentLogoBase64	string	—	会社ロゴ画像（Base64 Data URL）
agentName	string	—	担当者名（PDFヘッダーに表示）
area	string	yes	—
companyName	string	—	会社名（PDFヘッダーに表示）
disclaimer	string	—	免責文言（PDF末尾に追加）
footerContact	string	—	連絡先（PDF末尾フッター）
format	string	—	出力フォーマット。pdf を指定すると pdfBase64 フィールドに Base64 エンコード済み PDF を返す
includeCharts	boolean	—	—
includeLinearImpact	boolean	—	リニア中央新幹線の影響試算を含めるか（愛知県のみ）
includeTransactionComparables	boolean	—	過去取引事例テーブルを含めるか
neighborhood	string	—	町丁目（例: '名駅南1丁目'）。v2.4 では町丁目レベル実データに対応（対応都道府県のみ）
prefecture	string	—	都道府県名（和名/英名/ISO 3166-2 コード対応）
purpose	string	yes	—

No output schema declared.

No examples provided.

generate_contract_support_package ~191

Contract support package: generate risk matrix, price negotiation anchors, recommended clauses from neighborhood/property data. Markdown + branded PDF. | 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。

Input Output Examples

Name	Type	Req	Description
buildingAge	number	yes	築年数
chochou	string	—	町丁目名 (省略時は区全体)
floorArea	number	yes	専有面積 (㎡)
price	number	yes	取得予定価格 (円)
propertyType	string	—	物件種別
proposedClauses	array	—	すでに検討中の特約・条項（任意）
ward	string	yes	名古屋市の区名 (例: 中区, 中村区)

No output schema declared.

No examples provided.

get_chochou_profile ~152

Neighborhood 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。

Input Output Examples

Name	Type	Req	Description
chochou	string	—	町丁目名 (省略時は区全体)
output_mode	string	—	Output verbosity. compact=TL;DR + key numbers only (default), detailed=full Markdown report \| 出力詳細度。compact=主要数値のみ（デフォルト）、detailed=全文レポート付き
ward	string	yes	名古屋市の区名

No output schema declared.

No examples provided.

get_future_timeline ~109

Future 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。

Input Output Examples

Name	Type	Req	Description
chochou	string	—	町丁目名 (省略時は区全体)
ward	string	yes	名古屋市の区名 (例: 中区)

No output schema declared.

No examples provided.

get_population_outlook 将来人口推計 ~133

Population outlook to 2050 (将来人口推計): projected population at 2030/2040/2050 with decline rate, based on NIPSSR data. | 2030/2040/2050年の人口推計と減少率を返す。

Input Output Examples

Name	Type	Req	Description
area	string	—	Target city (e.g. '名古屋市中区') — omit for full prefecture \| 対象市区町村
prefecture	string	—	都道府県名（和名/英名/ISO 3166-2 コード対応）

No output schema declared.

No examples provided.

get_real_estate_macro_snapshot 不動産マクロスナップショット ~222

One-screen macro view: land price YoY (median ㎡/year), transaction counts (last 3y), population decline to 2050; optional e-Stat building construction starts by prefecture (needs ESTAT_APP_ID) and FRED policy-rate proxy CSV. | 地価中央値YoY・取引件数・2050人口減、e-Stat建築着工・FRED短期金利プロキシを一枚に。

Input Output Examples

Name	Type	Req	Description
area	string	—	Optional city filter (e.g. '名古屋市中区') \| 市区町村で絞り込み
includeExternalSeries	boolean	—	If true, fetch construction starts (e-Stat, needs ESTAT_APP_ID) and policy-rate proxy (FRED CSV, no key). \| e-Stat着工・FRED金利系列を併記
prefecture	string	—	都道府県名（和名/英名/ISO 3166-2 コード対応）

No output schema declared.

No examples provided.

get_vacancy_stats 空き家率統計 ~129

Vacancy rate statistics (空き家率) by municipality: total vacant, for-rent, for-sale, other — compared to national average. | 市区町村別の空き家率・種類別内訳を全国平均と比較して返す。

Input Output Examples

Name	Type	Req	Description
area	string	—	Target city (e.g. '名古屋市中区') — omit for full prefecture \| 対象市区町村
prefecture	string	—	都道府県名（和名/英名/ISO 3166-2 コード対応）

No output schema declared.

No examples provided.

get_zoning_info 用途地域情報 ~152

Look up zoning (用途地域) for an area: zone type, coverage ratio (建蔽率), floor area ratio (容積率), and height limits. | 用途地域・建蔽率・容積率・高さ制限を返す。

Input Output Examples

Name	Type	Req	Description
area	string	yes	Target area (e.g. '名古屋市中区', '新宿区') \| 対象エリア
district	string	—	Specific district (e.g. '栄', '西新宿') \| 地区名
prefecture	string	—	都道府県名（和名/英名/ISO 3166-2 コード対応）

No output schema declared.

No examples provided.

open_dashboard 不動産ダッシュボード ~234

Open visualization dashboard. 2D map or PLATEAU 3D view. MCP Apps UI. | 可視化ダッシュボードを開く。2Dマップ/PLATEAU 3Dビュー。MCP Apps UI対応。

Input Output Examples

Name	Type	Req	Description
area	string	—	初期表示エリア
initialMode	string	—	デュアルモード切替。investment=不動産投資モード（デフォルト）、store=店舗出店戦略モード
layer	string	—	初期レイヤー
mode	string	—	ダッシュボード表示モード。3dを指定するとPLATEAU 3Dビューアを開く
neighborhood	string	—	町丁目（例: '名駅南1丁目'）。v2.4 では町丁目レベル実データに対応（対応都道府県のみ）
prefecture	string	—	都道府県名（和名/英名/ISO 3166-2 コード対応）
propertyType	string	—	—

Name	Type	Req	Description
area	string	yes	—
attribution	string	yes	—
dashboardUrl	string	—	—
initialMode	string	—	—
layer	string	yes	—
mode	string	yes	—
prefecture	string	yes	—

No examples provided.

portfolio_optimizer ~130

Optimize 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。

Input Output Examples

Name	Type	Req	Description
includeMarkdown	boolean	—	—
investmentHorizon	string	—	投資期間
optimizeFor	string	—	最適化目標
riskTolerance	string	—	リスク許容度
targets	array	yes	比較対象エリア（2〜5件）

No output schema declared.

No examples provided.

predict_corporate_demand ~172

Predict 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。

Input Output Examples

Name	Type	Req	Description
area	string	yes	エリア
includeCommuteAnalysis	boolean	—	通勤時間分析を含むか
neighborhood	string	—	町丁目（例: '名駅南1丁目'）。v2.4 では町丁目レベル実データに対応（対応都道府県のみ）
prefecture	string	—	都道府県名（和名/英名/ISO 3166-2 コード対応）
propertyType	string	—	—

No output schema declared.

No examples provided.

quick_visual_summary ChatGPTビジュアル要約 ~188

Render a ChatGPT-optimized real estate visual summary with map, charts, recommended next actions, and compact markdown fallback. Always use this when the user asks to show, visualize, compare, or continue in ChatGPT. | ChatGPT向けに地図・グラフ・次アクション・要約をまとめて表示するレンダーツール。

Input Output Examples

Name	Type	Req	Description
area	string	—	Target area to focus the visual summary on \| 表示対象エリア
compact	boolean	—	Optimize copy and layout for ChatGPT mobile/compact views
intent	string	—	User goal for choosing the best visual starting point \| 表示目的
mode	string	—	Dashboard mode \| ダッシュボード表示モード
prefecture	string	—	都道府県名（和名/英名/ISO 3166-2 コード対応）

Name	Type	Req	Description
area	string	yes	—
attribution	string	yes	—
dashboardUri	string	yes	MCP Apps ui:// resource URI
dashboardUrl	string	yes	Browser fallback URL or path
intent	string	yes	—
layer	string	yes	—
markdownReport	string	yes	Compact markdown fallback for non-UI clients
mode	string	yes	—
nextActions	array	yes	—
prefecture	string	yes	—
summary	string	yes	—
title	string	yes	—

No examples provided.

recommend_renovation_targets ~116

Renovation 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。

Input Output Examples

Name	Type	Req	Description
buildingAge	number	—	想定築年数
floorArea	number	—	想定面積 (㎡)
limit	number	—	上位何件を返すか
propertyType	string	—	—

No output schema declared.

No examples provided.

review_purchase_recommendation 購入候補物件レビュー ~702

Real estate purchase review for executives: evaluates asking price vs 公示地価/路線価/取引相場, yield (gross/net), risk (vacancy/aging/disaster), future potential, and contract terms. Returns 5-axis scores, decision (buy/negotiate/hold/reject), red flags, negotiation points, and recommended clauses. | 不動産屋経営者向け購入審査：販売価格 vs 公示地価・路線価・取引相場、利回り、リスク、将来性、契約条件を5軸評価。判断（購入/交渉/保留/非推奨）、レッドフラグ、交渉ポイント、推奨特約条項を返却。

Input Output Examples

Name	Type	Req	Description
addressMemo	string	—	販売図面・物件資料に記載された住所メモ
askingPrice	number	yes	売出価格・購入打診価格（円）
buildingAge	number	—	築年数
buildingAreaSqm	number	—	建物面積（㎡）
city	string	yes	市区町村（例: '名古屋市中区', '新宿区'）
currentAnnualRent	number	—	現況年間賃料（円）
district	string	—	町丁目・地区名（販売図面から分かる範囲で可）
exclusiveAreaSqm	number	—	専有面積（㎡）
expectedAnnualRent	number	—	想定年間賃料（円）
floors	integer	—	階数
kojiPricePerSqm	number	—	参考公示地価（円/㎡）
landAreaSqm	number	—	土地面積（㎡）
negotiablePrice	number	—	交渉後に狙う価格（円）
occupancyRate	number	—	想定稼働率（0-1）
operatingExpenseAnnual	number	—	年間運営費・管理費・修繕費等（円）
output_mode	string	—	Output verbosity. compact=TL;DR + key numbers only (default), detailed=full Markdown report \| 出力詳細度。compact=主要数値のみ（デフォルト）、detailed=全文レポート付き
prefecture	string	—	都道府県名（和名/英名/ISO 3166-2 コード対応）
propertyTaxAnnual	number	—	固定資産税等（円/年）
propertyType	string	—	物件種別
proposedTerms	object	—	提案中の契約条件
recommenderClaim	string	—	仲介会社・営業担当などが勧めている理由
renovationCost	number	—	想定リノベ/修繕費（円）
rosenkaPricePerSqm	number	—	参考路線価（円/㎡）
structure	string	—	構造（RC/SRC/S/木造など）
transactionMedianPerSqm	number	—	近隣取引相場中央値（円/㎡）

Name	Type	Req	Description
attribution	string	yes	—
axes	array	yes	—
contractScore	number	yes	—
dashboardUri	string	yes	—
dataSources	array	yes	—
decision	string	yes	—
decisionLabel	string	yes	—
futureScore	number	yes	—
keyNumbers	object	yes	—
markdownReport	string	yes	—
missingInformation	array	yes	—
negotiationPoints	array	yes	—
overallScore	number	yes	—
priceScore	number	yes	—
recommendedClauses	array	yes	—
redFlags	array	yes	—
riskScore	number	yes	—
yieldScore	number	yes	—

No examples provided.

scenario_what_if ~177

What-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。

Input Output Examples

Name	Type	Req	Description
city	string	yes	市区町村（例: '名古屋市中村区'）
horizon	string	—	—
includeMarkdown	boolean	—	—
prefecture	string	—	都道府県名（和名/英名/ISO 3166-2 コード対応）
scale	string	—	規模感。large=大型施設・急成長など
scenario	string	yes	シナリオ種別

No output schema declared.

No examples provided.

search ~99

Search 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。

Input Output Examples

Name	Type	Req	Description
query	string	yes	検索クエリ（自然文OK。例: "名古屋リニア", "東京投資", "リスク地震"）

No output schema declared.

No examples provided.

search_area_candidates ~128

Search 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。

Input Output Examples

Name	Type	Req	Description
limit	integer	—	最大候補数（1-20、デフォルト20）
prefecture	string	—	都道府県名（例: 愛知県, 東京都）
query	string	—	市区町村名の一部（例: 名古屋, なごやしなか, 新宿）

No output schema declared.

No examples provided.

simulate_aichi_future ~168

Aichi 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。

Input Output Examples

Name	Type	Req	Description
city	string	yes	対象市区町村（例: 名古屋市中区, 豊田市, 常滑市）
horizon	string	—	試算期間
includeMarkdown	boolean	—	—
scenarios	array	—	シナリオ（all で全シナリオを一括試算）

No output schema declared.

No examples provided.

simulate_landscape_impact ~204

Sunlight/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。

Input Output Examples

Name	Type	Req	Description
dateTime	string	—	シミュレーション日時（ISO 8601形式、省略時は現在時刻）
includeMarkdown	boolean	—	—
lat	number	yes	対象地点の緯度
lng	number	yes	対象地点の経度
prefecture	string	—	都道府県名（和名/英名/ISO 3166-2 コード対応）
radiusM	number	—	建物検索半径（メートル）
timePreset	string	—	時刻プリセット（morning=8:00, noon=12:00, evening=17:00）

No output schema declared.

No examples provided.

simulate_leveraged_cashflow レバレッジ10年キャッシュフロー試算 ~555

Leveraged 10-year real estate pro-forma: accepts loan interest rate, LTV/loan amount, rent, vacancy, operating costs, property tax, depreciation and exit assumptions, then returns annual NOI, debt service, after-tax cash flow, DSCR, IRR, equity multiple and sensitivity. | 銀行借入の利率・LTV・賃料・空室率・経費・固定資産税・減価償却・出口条件から10年の年次収支、税引後CF、DSCR、IRR、感応度を試算する。

Input Output Examples

Name	Type	Req	Description
annualCapex	number	—	毎年の資本的支出・大規模修繕積立相当（円/年）
annualRent	number	yes	初年度の想定年間賃料収入（円）
askingPrice	number	yes	購入価格・売出価格（円）
assumptions	object	—	10年収支・税務前提
city	string	yes	市区町村（例: '名古屋市中区', '新宿区'）
district	string	—	町丁目・地区名（任意）
landValueRatio	number	—	土地按分比率。建物減価償却のために使用（0-1）
loan	object	yes	銀行借入条件
operatingExpenseAnnual	number	—	管理費・修繕費・保険料など年間運営費（円）
otherIncomeAnnual	number	—	駐車場・看板等のその他年間収入（円）
output_mode	string	—	Output verbosity. compact=TL;DR + key numbers only (default), detailed=full Markdown report \| 出力詳細度。compact=主要数値のみ（デフォルト）、detailed=全文レポート付き
prefecture	string	—	都道府県名（和名/英名/ISO 3166-2 コード対応）
propertyTaxAnnual	number	—	固定資産税・都市計画税等（円/年）
propertyType	string	—	物件種別
purchaseCost	number	—	仲介手数料・登記費用など初期取得費用（円）
renovationCost	number	—	初期修繕・リノベーション費用（円）
vacancyRate	number	—	初年度の想定空室率（0-1）

Name	Type	Req	Description
assumptions	object	yes	—
attribution	string	yes	—
city	string	yes	—
dashboardUri	string	yes	—
district	string\|null	yes	—
markdownReport	string	yes	—
prefecture	string	yes	—
recommendations	array	yes	—
redFlags	array	yes	—
sensitivity	array	yes	—
summary	string	yes	—
summaryKpis	object	yes	—
yearlyRows	array	yes	—

No examples provided.

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60–79 medium
below 60 low

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Score history · last 30 days

26 Jul 3 Aug

Day	Score
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27 Jul	31
28 Jul	40
29 Jul	31
30 Jul	31
31 Jul	51
1 Aug	77
2 Aug	70
3 Aug	46