Federal Register Search Scraper

Search the Federal Register for rules, proposed rules, notices and presidential documents and export clean, flat records.

Get structured Federal Register data as JSON, CSV or Excel, or call it as a tool from Claude, Cursor, ChatGPT or any MCP client. Built on the official Federal Register API v1, so it does not break when the website changes. Pay only for the documents you receive.

What you get

One record per document with the fields people actually filter on: document number, title, type, abstract, links to the HTML page, the PDF and (where relevant) the public inspection PDF, publication date, agencies, a relevance excerpt, docket IDs, effective date, comment close date, the official citation, page length and page range, the action line, the dates line, regulation ID numbers (RINs), and CFR title/part references.

Every result is a flat record with stable field names, so it drops straight into a spreadsheet, a database or an AI agent's context.

Why use this instead of the website

• Combine search term, document type, agency, docket ID and publication date filters in one call
• Pagination handled for you, with automatic retries and polite rate limiting
• Results in JSON, CSV, Excel or via API, or piped into Zapier, Make, n8n and Google Sheets
• Works as an MCP tool, so AI agents can look up regulatory documents on demand
• No browser, no proxies, no personal data: fast runs and a tiny cost per result
• Monitoring made easy: set "Published after" to yesterday and schedule the Actor daily to catch new documents from an agency

Input

Field	Type	Default	Meaning
query	string		Free-text keywords searched across document titles and text
documentTypes	array	all	Any of RULE, PRORULE, NOTICE, PRESDOCU
agencies	array	all	Federal Register agency slugs, e.g. "food-and-drug-administration"
publishedAfter	date		Only documents published on or after YYYY-MM-DD
publishedBefore	date		Only documents published on or before YYYY-MM-DD
docketId	string		A single regulatory docket ID
order	string	newest first	Newest, oldest or relevance
maxResults	integer	100	Cap on documents saved. You are charged per document, so this caps your cost.

Example input:

{
  "query": "food safety",
  "documentTypes": ["RULE", "NOTICE"],
  "agencies": ["food-and-drug-administration"],
  "publishedAfter": "2026-01-01",
  "maxResults": 200
}

Output

Example result (shortened):

{
  "documentNumber": "2026-12345",
  "title": "Food Labeling; Requirements for Front-of-Package Nutrition Symbol",
  "type": "Rule",
  "abstract": "The Food and Drug Administration is issuing a final rule requiring...",
  "url": "https://www.federalregister.gov/documents/2026/06/01/2026-12345/food-labeling",
  "pdfUrl": "https://www.federalregister.gov/documents/2026/06/01/2026-12345.pdf",
  "publicationDate": "2026-06-01",
  "agencies": ["Food and Drug Administration"],
  "agencySlugs": ["food-and-drug-administration"],
  "docketIds": ["FDA-2021-N-0300"],
  "effectiveOn": "2027-01-01",
  "commentsCloseOn": null,
  "citation": "91 FR 12345",
  "pageLength": 42,
  "startPage": 12345,
  "endPage": 12387,
  "action": "Final rule.",
  "dates": "This rule is effective January 1, 2027.",
  "regulationIdNumbers": ["0910-AI99"],
  "cfrReferences": [{ "title": 21, "part": 101 }]
}

Field reference: documentNumber, title, type, abstract, url, pdfUrl, publicInspectionPdfUrl, publicationDate, agencies[], agencySlugs[], excerpts, docketIds[], effectiveOn, commentsCloseOn, citation, pageLength, startPage, endPage, action, dates, regulationIdNumbers[], cfrReferences[]{title,part}.

Pricing

Pay per event. You are charged $1.50 per 1,000 documents saved to the dataset, plus a fraction of a cent per run start. Nothing is charged for results you do not receive. Set "Max total charge per run" in the run options to cap spending on any run. When a run reaches your cap it stops cleanly and keeps everything it already saved.

Rough guide: 1,000 documents cost $1.50 and take about 30 seconds.

Use it from an AI agent (MCP)

This Actor is available as an MCP tool through the Apify MCP server. Add it to your client, then ask the agent for the data in plain language.

Claude Desktop, Claude Code or Cursor (mcp.json / claude_desktop_config.json):

{
  "mcpServers": {
    "apify": {
      "url": "https://mcp.apify.com/?actors=brightpath-data/federal-register-search",
      "headers": { "Authorization": "Bearer YOUR_APIFY_TOKEN" }
    }
  }
}

ChatGPT and other clients that support remote MCP servers: add https://mcp.apify.com/?actors=brightpath-data/federal-register-search as a connector with your Apify token.

Example prompt once connected: "Find final rules published this year by the FDA about food safety and list the title, effective date and citation for each."

Use it from code

curl -X POST "https://api.apify.com/v2/acts/brightpath-data~federal-register-search/run-sync-get-dataset-items?token=YOUR_APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"query":"food safety","documentTypes":["RULE"],"maxResults":100}'

Python:

from apify_client import ApifyClient
client = ApifyClient("YOUR_APIFY_TOKEN")
run = client.actor("brightpath-data/federal-register-search").call(run_input={"query": "food safety", "documentTypes": ["RULE"], "maxResults": 100})
items = client.dataset(run["defaultDatasetId"]).list_items().items

Limits and fair use

• Up to 2,000 documents per run. The Federal Register API does not reliably return results deeper than about 2,000 for a single query; narrow your search with dates, agencies or a docket ID to go deeper into a large result set.
• Requests are paced at roughly two per second to be polite to the source.
• Only the fields listed above are requested from the API to keep responses small; the full text of each document is not included, only its abstract and excerpts. Use the url or pdfUrl field to read the full document.

Data source and legal

Data comes from the Federal Register, the official daily publication of the U.S. government, through its official public API v1, which requires no key. The data is U.S. government public domain data. This Actor collects public, non-personal data only and does not bypass logins, paywalls or access controls. You are responsible for how you use the data.

Support

Found a problem or need a field added? Open an issue on the Actor's Issues tab. Fixes for broken runs are prioritized.