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Turning Japanese press releases (PR TIMES) into an LLM-ready dataset in 5 minutes

A developer built an Apify Actor that scrapes PR TIMES, Japan's largest press-release distribution platform, into LLM-ready JSON records containing title, company, timestamp, category, cleaned body text, images and source URL. The tool accepts keyword, company-ID and date-based inputs, can skip full-body fetching for roughly 5× cheaper runs, and is exposed as a tool through Apify's MCP server for assistants like Claude and Cursor. The developer says the Actor only accesses public pages at low concurrency and warns users to summarize and index the copyrighted releases rather than republish them.

by read2 min views1 publishedSep 16, 2026

If you build anything that needs to understand the Japanese market — competitor monitoring, PR analytics, a RAG assistant for a sales team — you quickly run into a gap: most of the good structured news data is in English, and the Japanese sources that matter are not in your usual scraping toolkit.

PR TIMES is the one to know. It is Japan's largest press-release distribution platform: more than 100,000 companies publish there, from Toyota-scale corporations to two-person startups, and journalists in Japan treat it as a primary source. Whatever a Japanese company wants the world to know — a funding round, a new store, a product launch, a partnership — shows up on PR TIMES first, in a consistent format, with a category and a timestamp.

This post shows how to turn that stream into clean JSON you can feed to an LLM, without writing a scraper yourself.

Each release becomes one record:

{
  "title": "【虎ノ門ヒルズ×PR TIMES】一次情報で街の活性化を図る、新コラボ始動",
  "company": "株式会社PR TIMES",
  "companyId": 112,
  "publishedAt": "2026-09-06T23:00:00.000Z",
  "category": "イベント",
  "description": "…",
  "bodyText": "9月7日開始、200面以上に毎日掲出…",
  "bodyLength": 4567,
  "images": ["https://prcdn.freetls.fastly.net/release_image/112/1698/….png"],
  "url": "https://prtimes.jp/main/html/rd/p/000001698.000000112.html"
}

bodyText is the full body with navigation, scripts and boilerplate removed and paragraphs joined by newlines, so it embeds well and summarizes well. category comes from the site's own JSON-LD (articleSection), which is handy for filtering: 商品サービス (products), 資金調達 (funding), イベント (events), 人事 (HR) and so on.

The Actor accepts three kinds of input, and you can mix them:

生成AI, SaaS, EC…) — returns the latest ~40 releases per keyword. Good for "what is happening in my niche this week".https://prtimes.jp/main/html/searchrlp/company_id/XXXX. This paginates through the company's publishedAfter to only fetch what's new. Set fetchBody: false if you only need titles, dates and URLs — it's about 5× cheaper and much faster.

On Apify (PR TIMES Press Release Scraper) the free plan is enough to try it. The pricing is pay-per-event: you pay a fraction of a cent per release, nothing per month.

From code it's a normal Apify Actor call:

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('<your-username>/prtimes-press-release-scraper').call({
  companyIds: ['112'],
  publishedAfter: '2026-09-01',
  maxItems: 200,
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items.length, 'releases');

And if you use an MCP-capable assistant (Claude, Cursor, etc.), Apify's MCP server exposes the Actor as a tool, so you can literally ask "summarize what our three competitors announced this month" and get an answer grounded in the releases.

The Actor only touches public pages, at low concurrency, and keeps the content attributed to its source URL. Press releases exist to be spread, but they are still copyrighted by their publishers — summarize, analyze and index; don't republish them wholesale.

I'm building a small set of Japan-specific data tools (PR TIMES, Qiita/Zenn tech articles, government statistics) for people who need Japanese data in LLM pipelines. If there's a Japanese source you wish existed as a clean API, tell me in the comments.

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