FT Scraper | Financial Times Articles, Authors and Topics (2026)

From SilentFlow. Creators of Facebook Search Scraper and Pinterest Scraper, with 600,000+ combined lifetime runs.

Turn the Financial Times into a table: every FT article about a company, a person or a theme, with its headline, summary, authors, main topic, topic tags, word count, access level, publication and update dates and image, plus the full text when the article is free to read. Our test run for the keyword nvidia returned 20 complete articles in 14 seconds, with no FT account and no subscription.

Why choose this actor?

Reading FT.com tab after tab to see what it wrote about your company this week? Copying headlines into a spreadsheet by hand? Using a tool that only works once you already have the list of article links?

• 20 fields filled on every article, not 13. In our run for nvidia, each of the 20 rows carried the same 20 data fields: id, link, headline, summary, content type, category, main topic with its FT link, every topic tag, word count, access level, free-to-read flag, publication and update dates, image link with its size, language and source. Authors and the image caption came on 15 of the 20 rows, the comment count and full text where FT shows them. The output example of the most used FT actor on the Store has 13 keys, two of them empty.
• 1,000 articles from one keyword, not 12 headlines. Type Nvidia, private credit or Christine Lagarde and get the matching FT articles, newest first or most relevant first. In our test, the keyword oil returned 1,000 different articles in 29 seconds with listing fields only. The most used FT actor on the Store takes article links, and finds new articles only through FT's front-page feed, which held 12 headlines when we checked on 23 October 2026. Here you can paste article links too.
• Follow a topic, a section or a journalist. Paste an ft.com topic, company, section or author page and the actor reads it page after page, newest first, and stops at your date window. In our test, https://www.ft.com/artificial-intelligence with dateFrom set to 14 days gave 30 articles in 22 seconds, all published inside the window.

Try your first 20 articles

Paste this input in the JSON tab of the Input page and press Start. It looks for nvidia on FT and opens each article, until it has 20 different articles. In our test it took 14 seconds.

{
  "searchQueries": ["nvidia"],
  "maxItems": 20,
  "sort": "date",
  "includeDetails": true
}

Raise maxItems to 100 or more for a full coverage report. It runs on the Apify Free plan. Each article becomes one row of your dataset: open the Output tab to see the table with headlines, authors, topics and dates, or export the rows as JSON, CSV or Excel.

Copy to your AI assistant

Paste this block into Claude, ChatGPT or Cursor to give it the full picture of this scraper:

You have access to the FT Scraper on Apify: silentflow/ft-scraper

It returns Financial Times (ft.com) articles as structured rows, without any FT account. One row per article;
an article found through several keywords or links is returned once.

Input schema (no field is required):
- searchQueries (array of strings): keywords such as "nvidia", "private credit", "Christine Lagarde".
  Up to 1,000 articles per keyword. If FT search is busy, the matching FT topic page is read instead.
- startUrls (array of {url}): any ft.com page. Article (https://www.ft.com/content/{uuid}), topic or company
  (https://www.ft.com/nvidia), section (https://www.ft.com/technology), author page, stream page
  (https://www.ft.com/stream/{uuid}) or search page (https://www.ft.com/search?q=oil&sort=date).
- maxItems (integer, default 100, 20 in the form): max articles for the whole run.
- sort (string, "date" or "relevance", default "date"): order of keyword results.
- dateFrom (string): keep articles published on or after this day. "2026-10-01" or a span like "7 days".
- dateTo (string): keep articles published on or before this day. "2026-10-31" or a span like "1 day".
- includeDetails (boolean, default true): open each article for authors, topics, word count, comment count,
  access level, update date and full text of free articles. false = listing fields only, much faster.
- debugMode (boolean, default false).

Output per article (25 fields, null when absent):
- id (string, FT article uuid), url (string, https://www.ft.com/content/{id}), title (string)
- description (string, the standfirst), content (string, full text, free-to-read articles only)
- contentType (string: article, opinion, podcast, video), category (string), categoryUrl (string)
- mainTopic (string), mainTopicUrl (string), topics (array of strings, main topic first)
- authors (array of strings)
- wordCount (integer), commentsCount (integer)
- accessLevel (string: free, registered, subscriber, premium), isAccessibleForFree (boolean)
- publishedAt, modifiedAt (strings, RFC 3339 UTC)
- imageUrl (string), imageCaption (string), imageWidth, imageHeight (integers)
- language (string, e.g. en-GB), source (string, "Financial Times"), scrapedAt (string, RFC 3339 UTC)

Use apify-client for Python or JavaScript: client.actor("silentflow/ft-scraper").call(run_input=...).

How to scrape Financial Times articles

Three inputs, from the simplest to the most complete. Each one runs as is.

Get the latest FT articles about Nvidia

{
  "searchQueries": ["nvidia"],
  "maxItems": 50
}

The prefilled search, newest first. Each row is one FT article with its authors, main topic, topic tags, word count and access level, ready to sort by date or by topic.

Pull a month of FT coverage on private credit

{
  "searchQueries": ["private credit"],
  "dateFrom": "2026-09-01",
  "dateTo": "2026-09-30",
  "maxItems": 200
}

A date window turns a keyword into a monthly report. In our test with listing fields only, every row came back dated between 3 and 28 September 2026. Leave the dates empty to get every article FT has for the keyword.

Follow two FT topics and a few articles you already have

{
  "startUrls": [
    { "url": "https://www.ft.com/artificial-intelligence" },
    { "url": "https://www.ft.com/technology" },
    { "url": "https://www.ft.com/content/75153d9f-ce43-4f59-97a8-903a5f4a68e1" }
  ],
  "dateFrom": "14 days",
  "maxItems": 100
}

Topic and section pages are read page after page, newest first, and the run stops at the first article older than dateFrom. Article links are always read in full: this one is free to read, so its row carries the whole text.

Input parameters

Parameter	Type	Default	What it does
searchQueries	array of strings	prefilled ["nvidia"]	Keywords to look for on FT, one per line. Up to 1,000 articles per keyword.
startUrls	array of {url}	empty	ft.com links: articles, topics, companies, sections, authors, stream or search pages.
maxItems	integer	100 (20 in the form)	Max articles for the whole run, across all keywords and links.
sort	date or relevance	date	Order of keyword results: newest first, or best match first.
dateFrom	date or span	empty	Keep articles published on or after this day.
dateTo	date or span	empty	Keep articles published on or before this day.
includeDetails	boolean	true	Open each article for authors, topics, counts, access level and free text.
debugMode	boolean	false	Detailed log, for troubleshooting only.

No field is required. The form comes prefilled with a keyword that returns rows; an input with neither a keyword nor a link stops at once and says why.

Accepted links. Article pages (https://www.ft.com/content/66933e51-e06d-475c-aed2-f808f9443dea, with or without https:// or www.), topic and company pages (https://www.ft.com/nvidia, https://www.ft.com/us-interest-rates), section pages (https://www.ft.com/technology, https://www.ft.com/markets), stream and author pages (https://www.ft.com/stream/{uuid}) and FT search pages (https://www.ft.com/search?q=oil&sort=relevance, whose keyword, sort and dates are kept). Links to other websites, or to FT pages that list no article, are skipped with a message in the log.

Accepted dates. A day such as 2026-10-01, a full timestamp such as 2026-10-01T08:00:00Z (its UTC day is kept), today, yesterday, or a span back from now such as 7 days, 2 weeks, 3 months or 1 year. The form's date picker writes these for you. Spans make scheduled runs easy: a daily run with dateFrom set to 1 day always reads the last day.

What data can you extract from the Financial Times?

Every row has 25 fields, in the same order, with null when FT shows nothing for a field.

Group	Fields
Identity	id (FT article uuid), url (permanent link), title
Content	description (standfirst), content (full text of free-to-read articles), contentType, category, categoryUrl, mainTopic, mainTopicUrl, topics
Author	authors
Measures and access	wordCount, commentsCount, accessLevel, isAccessibleForFree
Time	publishedAt, modifiedAt
Media	imageUrl, imageCaption, imageWidth, imageHeight
Meta	language, source, scrapedAt

A few facts that help you use the data:

• id is FT's own article uuid and never changes; url is the permanent https://www.ft.com/content/{id} link, without tracking parameters. Both are safe keys for deduplication across runs.
• publishedAt, modifiedAt and scrapedAt are RFC 3339 timestamps in UTC (2026-10-21T06:33:49Z).
• accessLevel tells who can read the article on FT: free (anyone), registered (a free FT account), subscriber or premium. isAccessibleForFree is the same answer as a true or false flag.
• topics lists the main topic first, then every topic FT tags the article with. mainTopicUrl is the FT page of that topic, which you can paste back as a link to follow it.
• contentType comes from the listing: article, opinion, podcast or video.
• imageUrl points to FT's image service; imageWidth and imageHeight are the size of the original picture.

Output example

A complete row from our test run for nvidia (a subscriber article, so content is null):

{
  "id": "023caf76-40df-485d-8a28-0ff62aa7ec6f",
  "url": "https://www.ft.com/content/023caf76-40df-485d-8a28-0ff62aa7ec6f",
  "title": "Australian data centre group falls 44% on profit warning",
  "description": "NextDC plunge adds to sector woes as Nvidia holds talks over injecting capital into Firmus after failed IPO",
  "content": null,
  "contentType": "article",
  "category": "Data centres",
  "categoryUrl": "https://www.ft.com/data-centres",
  "mainTopic": "Data centres",
  "mainTopicUrl": "https://www.ft.com/stream/4619d295-5eca-4381-8087-cb0ecfb5eac3",
  "topics": ["Data centres", "Melbourne", "Nvidia", "Australia", "Artificial intelligence", "Technology"],
  "authors": ["Nic Fildes"],
  "wordCount": 541,
  "commentsCount": 31,
  "accessLevel": "subscriber",
  "isAccessibleForFree": false,
  "publishedAt": "2026-10-21T06:33:49Z",
  "modifiedAt": "2026-10-21T06:33:49Z",
  "imageUrl": "https://images.ft.com/v3/image/raw/https%3A%2F%2Fd1e00ek4ebabms.cloudfront.net%2Fproduction%2Fcfc387e3-991e-4ffa-b015-87d906405bf1.jpg?source=next-barrier-page&fit=scale-down&quality=highest&width=700&dpr=1",
  "imageCaption": "The M3 data centre in Footscray, Melbourne",
  "imageWidth": 2000,
  "imageHeight": 1125,
  "language": "en-GB",
  "source": "Financial Times",
  "scrapedAt": "2026-10-23T12:30:13Z"
}

On a free-to-read article, content holds the whole text with paragraphs separated by blank lines, and accessLevel is free.

Advanced usage

Five recipes for needs the examples above do not show. Each input runs as is.

Watch your company every morning

{
  "searchQueries": ["Unilever"],
  "dateFrom": "1 day",
  "maxItems": 50
}

Save this input as a task and schedule it daily in Apify Schedules. Each run returns only what FT published since yesterday, so your Slack channel, sheet or CRM gets the new coverage and nothing else.

Build a fast headline feed without opening articles

{
  "startUrls": [
    { "url": "https://www.ft.com/markets" },
    { "url": "https://www.ft.com/companies" }
  ],
  "includeDetails": false,
  "maxItems": 300
}

With includeDetails off, each row comes from the listing alone: headline, summary, category, date, image and caption. In our test, a 200-article run with listing fields only took 10 seconds. Turn it back on when you need authors, topics and counts.

Collect a journalist's articles

{
  "startUrls": [
    { "url": "https://www.ft.com/stream/54698fe3-773b-4f3d-8c5d-96bc5114c2cb" }
  ],
  "maxItems": 100
}

Every FT author has a stream page; open an author's name on any FT article to find it. The run reads it newest first, which is a clean way to track a reporter on your beat or to build a byline dataset.

Get the best matches of a theme, whatever their age

{
  "searchQueries": ["central bank digital currency", "stablecoin regulation"],
  "sort": "relevance",
  "maxItems": 200
}

Relevance sort brings FT's best matches first instead of the latest ones. Several keywords share the same maxItems, and an article found by both keywords is returned once.

Enrich a list of FT links you already have

{
  "startUrls": [
    { "url": "https://www.ft.com/content/66933e51-e06d-475c-aed2-f808f9443dea" },
    { "url": "https://www.ft.com/content/06209f51-de7c-4de0-8e66-5c621a960b87" },
    { "url": "https://www.ft.com/content/9aa4549e-26f4-4963-94eb-50cf0fc0b8f9" }
  ]
}

Paste links from a newsletter, a research note or an old spreadsheet and get each article back with its authors, topics, word count, comment count, access level and dates. Export the dataset as CSV and join it to your sheet on url or id.

FAQ

What is the Financial Times? The Financial Times (FT, ft.com) is a London-based business and economics newspaper, read worldwide for its coverage of companies, markets, central banks and politics. Most of its articles are for subscribers; some are free to read, and some need a free FT account.

What does this actor return exactly? One row per FT article, with 25 fields: identity, content, authors, measures, access level, dates, image and language. See the table in "What data can you extract".

Do I get the full text of every article? You get the full text of articles FT makes free to read. For subscriber and premium articles you get everything FT shows to a visitor who is not signed in: headline, summary, topics, word count, dates and image, plus authors and comment count on most of them. The paywalled body is never returned: content is null on those rows and accessLevel tells you why.

Do I need an FT account or subscription? No. The actor reads public FT pages without signing in. No FT account, no subscription, no login details to provide.

How do keyword searches work? A keyword returns the FT articles that match it, newest first or most relevant first, up to 1,000 per keyword. When FT search is busy, the actor reads the FT topic page that matches your keyword (for nvidia, the Nvidia topic page) and says so in the log, so the run still delivers articles.

How fresh is the data? Live. Every run reads FT at that moment, so an article published a minute ago can appear. Nothing is cached between runs.

How many articles can I get? maxItems caps the run, 100 by default. A keyword gives up to 1,000 articles (FT's own limit for one search); a topic or section page is read up to 100 pages deep, newest first. Several keywords and links add up, with duplicates removed.

Can I combine keywords, links and dates? Yes. Keywords and links run in the same input and share maxItems; the date window applies to all of them. For example searchQueries: ["oil"] with dateFrom: "2026-10-01" and sort: "date" returns this month's FT oil coverage, newest first.

Why do some rows have no authors or no comment count? FT does not show authors on some premium articles, editorials and podcast transcripts, and comments are closed on many pieces. In our nvidia run, 15 of 20 rows had authors. Fields FT does not show are null, never invented.

Are the links permanent? Yes. url and mainTopicUrl are permanent FT links and id never changes. Image links point to FT's image service; keep your own copy of a picture if you archive it.

Is it legal to scrape the Financial Times? The actor collects data FT shows publicly to any visitor and does not get around FT's paywall or sign-in. Article text is copyrighted by the FT: use the data for research, monitoring and analysis, and check FT's terms before republishing anything.

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🔎 SEO

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Support

Need something this scraper doesn't do yet? We ship features fast.

• Feature requests go straight to our backlog
• Enterprise needs? We do custom integrations and high-volume plans
• Pricing questions? Check the Monetization tab on the actor page

Response time: usually under 24 hours.

Legal compliance

This Actor extracts publicly available data from ft.com. It does not bypass any login, paywall or CAPTCHA, and it never returns the body of a subscriber-only article. Users are responsible for complying with the Financial Times terms of service, copyright law and applicable data protection laws (GDPR, CCPA, and PIPL where relevant). The output contains the names of journalists as published in FT bylines; handle them as personal data where those laws apply. The data returned is informational; verify accuracy for regulated use cases.

Built by SilentFlow for analysts, researchers and data teams who read the Financial Times for a living.