# SEC EDGAR Scraper - Filings, Forms & Companies (`goat255/sec-edgar-scraper`) Actor

Search the full text of company filings or pull any company's filing history by ticker. One clean row per filing with the company, form type, filing date, period and direct links to the document.

- **URL**: https://apify.com/goat255/sec-edgar-scraper.md
- **Developed by:** [Goutam Soni](https://apify.com/goat255) (community)
- **Categories:** Automation, Lead generation, Business
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$1.10 / 1,000 filing scrapeds

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#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

## SEC EDGAR Scraper

Search the full text of company filings, or pull any company's filing history by ticker. One clean row per filing. No login and no API key.

### What it does

- **Full text search** across filed documents going back years, so you can find every company that mentions a phrase.
- **Company filing history** by ticker or CIK number, filtered to the forms you care about.
- **Form filter** for 10-K, 10-Q, 8-K, S-1, DEF 14A, Form 4 and anything else.
- **Date range** on both modes.
- **Direct document links** on every row, both to the filed document itself and to its index page, so you can go straight to the source.
- **Company details** attached to each filing: ticker, CIK, industry code, location and state of incorporation.

Common uses: monitoring a company or a competitor's disclosures, finding every filing that mentions a technology or a risk, building a filings dataset, and financial and legal research.

### Input

Both modes are optional and can be combined in one run.

| Field | Type | Description |
|---|---|---|
| `searchQuery` | string | Text to find in filed documents. Use double quotes for an exact phrase. |
| `tickers` | array | Companies whose history you want, by ticker or CIK. |
| `formTypes` | array | Only these forms. Leave empty for all. |
| `dateFrom` / `dateTo` | string | Date range, `YYYY-MM-DD`. |
| `maxResults` | integer | Cap for the search. Default 200, up to 20000. |
| `maxFilingsPerCompany` | integer | Cap per company. Default 100. |
| `contactEmail` | string | Optional. See the note below. |
| `proxyConfiguration` | object | Optional. Enable to spread requests across IPs. |

#### Example input

```json
{
  "searchQuery": "\"machine learning\"",
  "formTypes": ["10-K"],
  "dateFrom": "2026-01-01",
  "maxResults": 1000
}
```

### Output

Each item is one filing.

```json
{
  "accessionNumber": "0000000000-26-000001",
  "form": "10-K",
  "type": "filing",
  "company": "Example Corporation",
  "ticker": "EXMPL",
  "cik": "0000000001",
  "sic": "3571",
  "location": "Springfield, IL",
  "stateOfIncorporation": "DE",
  "filingDate": "2026-05-01",
  "periodEnding": "2026-03-28",
  "primaryDocument": "exmpl-20260328.htm",
  "fileType": "10-K",
  "items": [],
  "documentUrl": "https://www.sec.gov/Archives/edgar/data/1/000000000026000001/exmpl-20260328.htm",
  "filingUrl": "https://www.sec.gov/Archives/edgar/data/1/000000000026000001/0000000000-26-000001-index.htm"
}
```

Rows from the company history mode also carry `size` and `isXBRL`.

### Notes

- No login and no API key. Enter a search phrase or a ticker and run.
- A single search returns up to 10000 filings. To go past that, split the run by date range.
- Results are deduplicated, so a filing reached by both a search and a company history is delivered once and charged once.
- Tickers that do not match a company are reported and skipped rather than returned as empty rows.
- The filings service asks callers to identify themselves. Setting `contactEmail` is optional but recommended for very large runs.

To improve our actors we collect anonymized usage telemetry (run stats and input patterns). No personal account data is collected.

# Actor input Schema

## `searchQuery` (type: `string`):

Search the text of filed documents. Wrap a phrase in double quotes to match it exactly.

## `tickers` (type: `array`):

Companies whose filing history you want. Accepts stock tickers or CIK numbers.

## `formTypes` (type: `array`):

Only return these forms, for example 10-K, 10-Q, 8-K, S-1, DEF 14A, 4. Leave empty for all forms.

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

Only filings on or after this date, format YYYY-MM-DD.

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

Only filings on or before this date, format YYYY-MM-DD.

## `maxResults` (type: `integer`):

Cap for the full text search. Default 200, up to 20000.

## `maxFilingsPerCompany` (type: `integer`):

Cap per company in the filing history mode.

## `contactEmail` (type: `string`):

Optional. The filings service asks callers to identify themselves. Adding your email is polite and reduces the chance of being slowed down on very large runs.

## `proxyConfiguration` (type: `object`):

Optional. Enable to spread requests across IP addresses.

## Actor input object example

```json
{
  "searchQuery": "\"supply chain risk\"",
  "tickers": [
    "AAPL",
    "0000320193"
  ],
  "formTypes": [
    "10-K",
    "8-K"
  ],
  "dateFrom": "2026-01-01",
  "dateTo": "2026-07-01",
  "maxResults": 200,
  "maxFilingsPerCompany": 100,
  "contactEmail": "you@example.com"
}
```

# Actor output Schema

## `filings` (type: `string`):

No description

# 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 = {
    "searchQuery": "\"machine learning\""
};

// Run the Actor and wait for it to finish
const run = await client.actor("goat255/sec-edgar-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 = { "searchQuery": "\"machine learning\"" }

# Run the Actor and wait for it to finish
run = client.actor("goat255/sec-edgar-scraper").call(run_input=run_input)

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

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

```

## CLI example

```bash
echo '{
  "searchQuery": "\\"machine learning\\""
}' |
apify call goat255/sec-edgar-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=goat255/sec-edgar-scraper",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/wqL80dUjx2qsArXL0/builds/Si43oWa0mTiSmyzE1/openapi.json