SEC EDGAR Filings Scraper

SEC EDGAR Scraper: search every SEC filing by phrase, ticker or CIK

Give it a phrase and it runs the SEC's own full-text search across every indexed filing. Give it tickers or CIKs instead and it pulls those companies' filing histories. Each row carries the form type, the company, the CIK, the filing date, the accession number and a link straight to the document.

One thing to know before you budget a run: full-text search returns a row per matching document, not per filing. A 10-K whose exhibits all mention your phrase comes back as several rows, and each one is charged.

🔍 What SEC EDGAR Scraper does

In search mode it asks EDGAR's full-text index for your phrase and pages through the hits. Your words go in as one quoted phrase, so artificial intelligence finds that pair of words together, not documents that happen to contain both somewhere. There are no boolean operators and no wildcards.

In company mode you hand it tickers, CIKs or a mix of the two, and it reads each company's recent filing history from the SEC's submissions feed. These rows are fuller: the ticker, the report date and the document description are all populated, because that feed carries them and the full-text index usually does not.

Both modes take the same form filter and the same date window, and both stop at the same run total. What you get is filing metadata plus filingUrl, which points at the document itself rather than a landing page, so you can hand it straight to whatever reads it next.

📥 What you give it

{
  "mode": "search",
  "query": "artificial intelligence",
  "forms": "10-K,8-K",
  "startDate": "2024-01-01",
  "maxItems": 500
}

{
  "mode": "company",
  "tickers": ["AAPL", "TSLA", "0000320193"],
  "forms": "10-K",
  "maxItems": 200
}

maxItems is a budget for the run, shared by every ticker in the list. Four tickers at maxItems: 100 does not give you 100 each. The first company can spend the whole budget before the fourth is reached, so put the ones you care about first.

📤 What you get back

A real row from a recent run:

{
  "ok": true,
  "form": "20-F",
  "companyName": "Xiao-I Corp",
  "cik": "0001935172",
  "ticker": "AIXI",
  "filingDate": "2023-04-28",
  "reportDate": "2022-12-31",
  "accessionNumber": "0001213900-23-033683",
  "primaryDocument": "f20f2022ex4-19_xiaoicorp.htm",
  "description": "ENGLISH TRANSLATION OF AI CLOUD PLATFORM SERVICE CONTRACT BETWEEN SHANGHAI XIAO-I ROBOT TECHNOLOGY CO., LTD. AND CUSTOMER F DATED JUNE 27, 2022",
  "filingUrl": "https://www.sec.gov/Archives/edgar/data/1935172/000121390023033683/f20f2022ex4-19_xiaoicorp.htm"
}

🧾 Reading the output

Two kinds of row land in your dataset, and ok tells them apart.

The overview table in the Apify console shows the filing columns only, so a diagnostic row looks blank there. Switch to the JSON or All fields view to read it.

▶️ How to run it

1. Open SEC EDGAR Scraper and click Try for free. 2. Leave Mode on full-text search and type a phrase into Search query, or switch to company filings and fill in Tickers or CIKs. 3. Set Max filings. Start around 50 to see the row shape. 4. Narrow it with Form types and the two date fields if you want, then click Start. 5. Download the dataset as JSON, CSV or Excel, or read it from the Apify API.

💰 How much does it cost?

$2.00 per 1,000 filings. Flat on every Apify plan, no volume tiers.

You pay per row delivered. Duplicate documents are dropped before they are counted, diagnostic rows are not charged, and a search that matches nothing is not charged.

💡 What people use it for

• Finding every company that used a phrase in its filings, then reading the documents that came back.
• Pulling one company's 10-K and 8-K history for a model that needs the source text, not a summary.
• Watching a form type on a schedule, using the date fields so each run only picks up what is new.
• Building a CIK list for an internal database, since the CIK survives ticker changes and renames.

🚧 What it does not do

• Metadata and a link, never the text. The filing itself is not downloaded or parsed here.
• Full-text search stops at 10,000 results per query. That is the SEC's ceiling. Narrow a common

phrase with a form filter or a date range instead of trying to page past it.

• Search rows are thin. ticker, reportDate and description are frequently null, because

the SEC's full-text index does not carry them. Use company mode when you need full records.

• One row per matching document. A filing with several matching exhibits produces several rows.
• company mode reads the recent filings block the SEC publishes per company. A start date

further back than that block reaches returns fewer rows without saying so.

• Dates are taken as given. An impossible date is not rejected, it just matches nothing.
• The query is one exact phrase. Quotes of your own, AND, OR and wildcards are not

interpreted.

• A ticker that has been reused resolves to whichever company holds it today. Use a CIK to be

certain.

🧭 Which company data scraper do you need?

❓ Questions people ask

Do I need an SEC account or key? No. EDGAR is a public government system and this reads it directly.

Why did four tickers give me fewer rows than I expected? maxItems is one budget for the whole run. Raise it, or run the companies separately.

Why is ticker empty on my search results? The SEC's full-text index often does not publish it. Take the cik from the row and run company mode on that.

Can I search for two phrases at once? Not in one run. The query goes in as a single quoted phrase. Run them separately and join on accessionNumber.

Can I schedule it? Yes. Set startDate to the day you last ran it, and each run picks up what has been filed since.

Is this legal? EDGAR is published by the SEC for public use, and these are documents companies are required by law to file. Apify's write-up on scraping and the law is a good starting point, and we are not lawyers.

🆘 If something breaks

Open the Issues tab on the actor page. Send the run ID and the input you used. The errorCode on the diagnostic row usually names the problem on its own.