# Federal Register Scraper - US Rules & Regulations (`scrapesage/federal-register-scraper`) Actor

Search the US Federal Register - final rules, proposed rules, notices and presidential documents: title, abstract, agencies, publication and effective dates, comment deadlines, CFR references, docket IDs and PDF links. Filter by type, agency and date. No API key, no browser.

- **URL**: https://apify.com/scrapesage/federal-register-scraper.md
- **Developed by:** [Scrape Sage](https://apify.com/scrapesage) (community)
- **Categories:** News, Agents, Integrations
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.55 / 1,000 document scrapeds

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## Federal Register Scraper - US Rules & Regulations

Search the **US Federal Register** and get clean rows for every document: **final rules**, **proposed
rules**, **notices** and **presidential documents** - with **title**, **abstract**, **agencies**,
**publication and effective dates**, **public comment deadlines**, **CFR references**, **docket IDs**,
**citation** and **PDF links**. Filter by document type, agency and date. Built on the official API -
no key, no browser.

### What you get per document

| Field | Meaning |
|---|---|
| `documentNumber` / `title` / `citation` | FR document number, title and Federal Register citation |
| `documentType` / `documentTypeLabel` | RULE, PRORULE, NOTICE or PRESDOCU (with a readable label) |
| `abstract` / `action` | Summary and the regulatory action |
| `agencies` / `agencyCount` | Issuing agencies |
| `publicationDate` / `effectiveOn` / `commentsCloseOn` | Key dates, incl. the public-comment deadline |
| `cfrReferences` / `docketIds` / `regulationIdNumbers` | Code of Federal Regulations parts, dockets, RINs |
| `significant` / `president` / `signingDate` | Significance flag; president & signing date (presidential docs) |
| `htmlUrl` / `pdfUrl` | Links to the official document |

### Input

```json
{ "searchQueries": ["artificial intelligence"], "documentTypes": ["RULE"], "dateFrom": "2024-01-01" }
```

- **Search terms** - full-text search, one per line. **Document numbers** - exact lookups.
- **Filters** - document **type**, **agency slugs** (e.g. `environmental-protection-agency`), and a
  **publication date range**.
- **Import from a file** - paste a list, or link a public `.txt`/`.csv`, a Google Sheet/Drive link, or an
  Apify key-value-store record. **Output fields** trim every record.

Leave everything empty and the run returns a small free sample so you can see the shape first.

### Reliability

Reads the official [Federal Register API](https://www.federalregister.gov/developers/api/v1) - public,
keyless, no anti-bot, page-paginated for deep result sets. A search that returns nothing bills **$0**.

### Honest limits

- **Metadata, not the full rule text.** You get the document record, abstract and links; follow
  `htmlUrl`/`pdfUrl` for the full text.
- **`commentsCloseOn` is present only for documents with an open comment period** (mostly proposed
  rules) - an honest null otherwise.
- **`cfrReferences` / `president` / `signingDate` populate only where applicable** by document type -
  presidential fields on presidential documents, CFR parts on rules.

### Pricing

**$0.001 per document** on the FREE tier (tiered pricing lowers it with volume). Only documents actually
saved are billed; an empty search costs nothing.

### Output views

- **Documents** - title, type, agencies, publication date, comment deadline, citation and link.

### Use with AI assistants (MCP)

Available through the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp) - an agent
can monitor new rules from an agency, track a rulemaking's comment deadline, or pull every AI-related
regulation in a date range in one call.

### Agent-ready: autonomous payments (x402 & Skyfire)

This actor is **agent-ready** - AI agents can discover it, run it, and **pay for it autonomously**, with no Apify account and no human in the loop. It uses [pay-per-event](https://docs.apify.com/platform/actors/publishing/monetize/pay-per-event) pricing and [limited permissions](https://docs.apify.com/platform/actors/development/permissions), so it qualifies for Apify's agentic-payment standards:

- **[x402](https://docs.apify.com/platform/integrations/x402)** - an open, HTTP-native payment protocol. Agents pay per run in USDC on the Base network directly through the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp) - no account, no API key.
- **[Skyfire](https://docs.apify.com/platform/integrations/skyfire)** - agent-to-service payments for fully autonomous AI-agent workflows.

Building an AI agent, MCP tool, or autonomous data pipeline? This scraper is ready to plug in and pay as it goes.

# Actor input Schema

## `searchQueries` (type: `array`):

Terms to search the Federal Register full text, one per line - e.g. <code>artificial intelligence</code>, <code>clean water</code>. <b>Leave empty and the run returns a small free sample.</b>

## `documentNumbers` (type: `array`):

Specific Federal Register document numbers to fetch exactly, one per line - e.g. <code>2024-00001</code>.

## `documentTypes` (type: `array`):

Keep only the selected document types. Leave empty for all.

## `agencies` (type: `array`):

Keep only documents from these agency slugs - e.g. <code>environmental-protection-agency</code>, <code>securities-and-exchange-commission</code>, <code>food-and-drug-administration</code>. Leave empty for all agencies.

## `dateFrom` (type: `string`):

Only documents published on or after this date (YYYY-MM-DD). Leave empty for no lower bound.

## `dateTo` (type: `string`):

Only documents published on or before this date (YYYY-MM-DD). Leave empty for no upper bound.

## `maxItemsPerQuery` (type: `integer`):

How many documents to collect for each search term.

## `maxItems` (type: `integer`):

Overall cap across all searches. You are only charged for documents actually saved.

## `searchQueriesFromFile` (type: `string`):

Bulk-load search terms. Either <b>paste the whole list</b> (one per line), or give <b>a single link</b> to a public <code>.txt</code>/<code>.csv</code>, a Google Sheet/Drive link, or an Apify key-value-store record. A file that cannot be read says so and charges nothing.

## `outputFields` (type: `array`):

Pick the fields you want and every record is trimmed to exactly those - handy for lean CSV/Sheets exports.

## Actor input object example

```json
{
  "searchQueries": [
    "artificial intelligence"
  ],
  "maxItemsPerQuery": 100,
  "maxItems": 2000
}
```

# Actor output Schema

## `results` (type: `string`):

Each scraped record - a Federal Register document with agencies, dates, CFR references and links - as a JSON item in the default dataset.

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "searchQueries": [
        "artificial intelligence"
    ],
    "searchQueriesFromFile": ""
};

// Run the Actor and wait for it to finish
const run = await client.actor("scrapesage/federal-register-scraper").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "searchQueries": ["artificial intelligence"],
    "searchQueriesFromFile": "",
}

# Run the Actor and wait for it to finish
run = client.actor("scrapesage/federal-register-scraper").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "searchQueries": [
    "artificial intelligence"
  ],
  "searchQueriesFromFile": ""
}' |
apify call scrapesage/federal-register-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,scrapesage/federal-register-scraper"
        }
    }
}

```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/CDyJaJood7PVE3UbY/builds/8TUwnnymk7jhHQWOx/openapi.json