MLIT Japan Real Estate Prices Scraper

MLIT Japan Real Estate Prices Scraper

Scrape official real estate transaction prices from Japan's MLIT, covering all 47 prefectures and any city or quarter back to 2005. Get actual sale prices, floor area, building age, layout, and zoning for each property in a clean, flat dataset. Export to CSV, JSON, Excel, or XML.

The MLIT's official land price database holds the true transaction prices for condos and houses across Japan, but its web interface makes comparing markets or tracking trends across quarters slow and manual. This actor reads the public API directly, so you get every sale record for a prefecture, city, and date range you specify, without clicking through a single map. All figures are the actual contracted prices the government collects, not asking prices or broker estimates.

Who uses it	What they scrape MLIT for
Real estate investors	Pull recent transaction prices for a whole ward to find undervalued neighborhoods before anyone else does.
Property appraisers	Download exact comparable sale records for a building type, age, and area to support a valuation report.
Data analysts and researchers	Build a time series of price per square meter across prefectures and quarters to model market cycles.
Development firms	Check land cost and transaction frequency in a district before assembling a site and setting a project budget.

What it does

This actor collects MLIT real estate transaction price records by prefecture, city, and quarter, and returns each sale as one structured row with all available field data.

• 🏢 Government source data: actual MLIT land transaction prices, the same data used by major banks and valuation firms in Japan.
• 🗾 Full 47-prefecture coverage: select any prefecture from Hokkaido to Okinawa, plus an optional 5-digit city code for district-level focus.
• 📅 Quarterly date range: filter by start and end period in YYYYN format (year plus quarter 1 through 4), with data available from 2005 onward.
• ⚙️ Max items control: set a hard cap from 1 to 1,000,000 transactions per run so you never exceed a budget.

Results export to CSV, JSON, Excel, or XML, or straight from the API.

What you can do with MLIT data

🏘 Screen a whole city for recent deals.

A buy-side analyst runs the actor for Osaka city from 2022 Q1 to 2023 Q4, exports a CSV, and filters for 60‑80 sq m units within 5 minutes of a station to shortlist target buildings.

📊 Build a quarterly price index.

A researcher feeds the actor with Tokyo's 23 wards quarter by quarter back to 2010, then plots the median price per square meter to publish a market report.

🏗️ Value a development site using land comps.

A developer pulls all vacant land transactions in a ward from the last four quarters, filters by zoning category, and calculates a residual land value before bidding.

🌐 Monitor multiple prefectures in one schedule.

An investor sets up an Apify schedule that runs the actor for Tokyo, Kanagawa, and Chiba every quarter when new MLIT data is released, appending the latest sales to a shared dataset.

Why choose this scraper

	What you get
Transaction price	The actual contracted sale price recorded by the government.
Floor area and layout	Property size in square meters and room configuration for accurate price-per-unit comparisons.
Building age and structure	Construction year and material, critical for depreciation and seismic risk models.
Nearest station and distance	Transport access details that explain a large part of price variation in Japan.

How it compares

Two other actors also pull from the MLIT API; here is how their listed capabilities compare for pricing, filtering granularity, and throughput.

Feature	ParseForge	MLIT Japan Real Estate Transaction Prices	Japan Real Estate Transaction Prices (MLIT Official)
Download actual transaction prices	Yes, per-property contracted sale price.	Yes	Yes
Filter by exact quarter (YYYYN)	Yes, from and to period with quarter granularity.	Not listed	Not listed
Filter down to a specific city code	Yes, optional 5-digit city code input.	Not listed	Not listed
Cap max records to control cost	Yes, user-set max from 1 to 1M per run.	Not listed	Not listed
English and Japanese data output	Yes, bilingual fields included.	Yes	Yes

Configure the run

Drive the actor with a prefecture code, an optional city code, and a start-to-end quarter range, and the filters run on the API side so only matching transactions reach your dataset. The Input tab lists every parameter.

A first run with the defaults:

{
  "from": "20231",
  "to": "20234",
  "maxItems": 10
}

A larger pull:

{
  "from": "20231",
  "to": "20234",
  "maxItems": 200
}

Pricing

Pay-per-result: $0.0085 per result collected. You pay only for the results written to your dataset.

Results collected	Approximate cost
100 results	$0.85
1,000 results	$8.50
10,000 results	$85.00

New Apify accounts start with $5 in free credit.

Free users

Free-plan runs return up to 10 results as a preview. Upgrade your Apify plan to collect up to 1,000,000 results per run.

Run it

1. Create a free Apify account with $5 in credit.
2. Open the MLIT Japan Real Estate Prices Scraper.
3. Set your inputs and any filters, then click Start.
4. Export the results as CSV, Excel, JSON, or XML from the Dataset tab.

Run it programmatically through the Apify API (run-sync-get-dataset-items) or the ApifyClient for JavaScript and Python.

Use with AI agents (MCP)

Give an AI agent live access to MLIT through the Model Context Protocol. Add the Actor to Claude, Cursor, or any MCP client:

claude mcp add --transport http apify "https://mcp.apify.com?tools=parseforge/mlit-japan-real-estate-prices-scraper"

Then prompt it in plain language to run the scraper and read back the results.

Troubleshooting

Why am I getting no results?

Check that your from and to periods are in the correct YYYYN format and that the end period is not before the start. Also verify that the prefecture code is a valid two-digit string. If you used a 5-digit city code, try removing it in case no transactions match that specific city in the quarter range.

The actor runs but returns far fewer records than I expected.

The maxItems field caps the number of transactions. If you set it to a low value like 10, the actor stops early. Raise it up to 1,000,000 and re-run.

I see an error about the period format.

Use exactly YYYYN with no delimiters, for example 20221 for Q1 2022. Values like 2022-1 or 2022Q1 will fail.

The output has Japanese column names and I need only English.

The dataset includes both ja and en field names. When exporting to CSV or Excel, you can deselect the Japanese columns or use a post-processing script that keeps only the English keys.

Can I scrape multiple prefectures in a single run?

The actor takes one prefecture code per run. To collect multiple prefectures, create an Apify task for each one and either run them sequentially or put them in a shared schedule.

The actor timed out before it reached my maxItems limit.

Very wide queries with a high maxItems value can be slow. Try narrowing the city code or date range, or break the job into smaller chunks. The Apify actor timeout is 300 seconds by default.

FAQ

Question	Answer
Is this the official MLIT dataset?	Yes, the actor reads the same public API that powers the MLIT's own land information map, so every row is the actual contracted price reported to the government.
How far back does the data go?	The MLIT API provides records from 2005 onwards, and you control the exact start and end quarter in the input.
Do I need an API key or an MLIT account?	No. The actor queries the open government endpoint directly, so you do not register anything or manage tokens.
What is a prefecture code and where do I find it?	The input provides a dropdown with all 47 codes, from 01 for Hokkaido to 47 for Okinawa. The default is 13 for Tokyo.
How do I specify a city or ward?	Enter the optional 5-digit MLIT city code in the cityCode field. Leave it blank to get all cities inside the prefecture.
What does the quarter format YYYYN mean?	YYYY is the year, N is the quarter number 1 through 4. For example, 20231 means January to March 2023, and 20234 means October to December 2023.
Can I get results in Japanese?	Yes. The raw response fields include the original Japanese labels alongside English translations, and you can select your preferred output format when you export.
Is there a limit on how many records I can pull?	You set the maximum transactions per run, from 1 up to 1,000,000. The API itself does not impose a rate limit on this actor.
Does this actor update automatically when new quarterly data is released?	The actor runs on-demand or on an Apify schedule you configure. The MLIT typically posts new quarter data a few months after the quarter ends, so you can time your schedule to match.
Can I get the price per tsubo instead of per square meter?	The raw data reports area in square meters. You can add a computed column in Excel or in a post-processing step to convert to tsubo (1 sq m equals about 0.3025 tsubo).
Does this include commercial or industrial land, or only residential?	The MLIT API returns transactions across all land-use categories. You can filter by zoning or property type in your dataset after the run.
What export formats are supported?	The actor stores results in Apify's default dataset, which you can export to CSV, JSON, Excel, XML, or a direct API endpoint.

Related actors

Browse the full ParseForge collection for more scrapers.

🆘 Need help? Email parseforge@protonmail.com with your run ID, your input, and what you expected.

⚠️ Disclaimer. This Actor is unofficial and is not affiliated with, endorsed by, or sponsored by Ministry of Land, Infrastructure, Transport and Tourism. It collects only publicly available data. You are responsible for using the collected data in compliance with the source's terms of service and applicable data-protection laws, including GDPR, CCPA, and PIPL. Do not use it to collect personal data unlawfully.