# SEC EDGAR Financials, Filings & Company Data Scraper (`foxlabs/sec-edgar-financials`) Actor
Rich US public-company intelligence from the official SEC EDGAR API: full firmographics, multi-year XBRL financial statements (income, balance sheet, cash flow), computed margins & growth, plus recent filings (10-K/10-Q/8-K, insider). Input tickers or CIKs. Free, structured JSON.
- **URL**: https://apify.com/foxlabs/sec-edgar-financials.md
- **Developed by:** [Berkan Kaplan](https://apify.com/foxlabs) (community)
- **Categories:** Lead generation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet
## Pricing
from $5.00 / 1,000 results
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 a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases.
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.
In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md):
```bash
npm install apify-client
```
In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md):
```bash
pip install apify-client
```
In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md):
````bash
# MacOS / Linux
curl -fsSL https://apify.com/install-cli.sh | bash
# Windows
irm https://apify.com/install-cli.ps1 | iex
```bash
In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md).
If your project is in a different language, use 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 Financials, Filings & Company Data Scraper pulls **rich US public-company intelligence from the official [SEC EDGAR](https://www.sec.gov/edgar) system** — complete firmographics, multi-year XBRL financial statements, computed metrics, and the latest filings — for any ticker or CIK. Get clean, structured JSON for **investment research, financial analysis, fundamentals databases, and B2B lead enrichment**.
No API key, no login, no proxies. Because it runs on Apify you get scheduling, an API, webhooks, and one-click export to JSON, CSV, or Excel.
### What does SEC EDGAR Scraper do?
Give it a list of stock tickers (e.g. `AAPL`, `MSFT`, `NVDA`) or CIK numbers, and for each company it returns a single rich record containing:
- **Firmographics** — legal name, tickers, exchanges, SIC industry, EIN, state of incorporation, fiscal year end, former names, address.
- **Full financial statements** — income statement (revenue, gross profit, operating & net income, EPS, R&D), balance sheet (assets, liabilities, equity, cash), and cash flow, as **multi-year annual + multi-quarter** series, parsed from XBRL.
- **Computed metrics** — gross / operating / net margins, revenue growth (YoY), debt-to-equity, and return on equity, all calculated from the same fiscal year.
- **Recent filings** — 10-K, 10-Q, 8-K and more (optionally insider Form 3/4/5), each with a direct link.
### Why use this SEC EDGAR Scraper?
- **Richest output on the market** — most EDGAR actors return just a filings list or a single metric. This one merges firmographics + full financials + computed ratios + filings in one clean record.
- **Build a fundamentals database** — pull hundreds of tickers on a schedule and keep your own up-to-date financial dataset.
- **Enrich B2B / investor data** — attach real revenue, profitability and filing activity to your CRM or watchlist.
- **Free, authoritative source** — straight from SEC's official XBRL API, public domain.
### How to use SEC EDGAR Scraper
1. Click **Try for free**.
2. Enter one or more **tickers** (or CIK numbers).
3. Optionally adjust how many **annual years** / **quarters** / **filings** to include.
4. Click **Start**, then download the dataset or wire it into your pipeline.
### Input
| Field | Description |
|---|---|
| Stock tickers | Tickers to look up (resolved to CIK automatically) |
| CIK numbers | Alternative/additional SEC CIKs |
| Include financial statements | Fetch XBRL financials + computed metrics (default on) |
| Annual years / Quarters | Depth of financial history per metric |
| Include recent filings | Add the filings list with links |
| Max filings | Cap on filings per company |
| Include insider filings | Include Form 3/4/5 (off by default) |
### Output
A simplified record (download as JSON, CSV, Excel, or HTML):
```json
{
"cik": "0001045810",
"name": "NVIDIA CORP",
"tickers": ["NVDA"],
"exchanges": ["Nasdaq"],
"sicDescription": "Semiconductors & Related Devices",
"stateOfIncorporation": "DE",
"computedMetrics": {
"grossMarginPct": 71.1, "operatingMarginPct": 60.4,
"netMarginPct": 55.6, "revenueGrowthYoYPct": 65.5, "returnOnEquityPct": 76.3
},
"financials": {
"revenue": {
"annual": [
{ "fiscalYear": 2026, "end": "2026-01-25", "value": 215900000000 },
{ "fiscalYear": 2025, "end": "2025-01-26", "value": 130500000000 }
],
"quarterly": [ { "period": "CY2025Q4", "end": "2026-01-25", "value": 39300000000 } ]
}
},
"recentFilings": [
{ "form": "10-K", "filingDate": "2026-02-26", "url": "https://www.sec.gov/Archives/edgar/data/..." }
]
}
````
### Data table
| Field | Description |
|---|---|
| cik / name / tickers / exchanges | Company identity |
| sic / sicDescription | Industry classification |
| ein / stateOfIncorporation / fiscalYearEnd / formerNames / address | Firmographics |
| financials.\* | 13 metrics, each with `annual` and `quarterly` series (income, balance sheet, cash flow, EPS, shares) |
| computedMetrics | Margins, revenue growth, debt-to-equity, ROE |
| recentFilings | Form type, dates, and direct document links |
### How much does it cost to scrape SEC EDGAR?
The actor uses SEC's free public API, so runs are cheap — cost scales with the number of companies you request (each company is a couple of API calls). Use the depth options to keep output lean. The free tier is enough to evaluate it and run small scheduled jobs.
### Tips & advanced options
- **Keep your dataset fresh** — schedule a daily/weekly run over your ticker list.
- **Lean output** — lower the annual/quarter counts, or turn off filings, if you only need headline financials.
- **Insider activity** — turn on insider filings to capture Form 4 transactions.
- **Tag fallbacks** — financials combine multiple XBRL tags, so companies that changed reporting tags over the years still return complete history.
### FAQ, disclaimers & support
- **Is this legal?** It only retrieves publicly available data from the U.S. Securities and Exchange Commission's official EDGAR system, which is in the **public domain**. This actor and its author are **not affiliated with or endorsed by the SEC**.
- **Accuracy:** financials are parsed directly from companies' XBRL filings. Always verify against the source filing for critical decisions; restatements and non-standard reporting can occur.
- **Rate limits:** the actor respects SEC's fair-access policy with a descriptive User-Agent and request throttling.
- **Support & custom work:** need another field, statement, or source? Open an issue on the Issues tab — feedback and custom-solution requests are welcome.
***
### More foXLabs data tools
This Actor is part of the **[foXLabs data platform](https://data.foxlabs.com.tr/)** — a suite of public-data scrapers for company intelligence, procurement, financial and AI-search visibility data. Browse the full Actor suite and free how-to guides at **[data.foxlabs.com.tr](https://data.foxlabs.com.tr/)**.
# Actor input Schema
## `tickers` (type: `array`):
Stock ticker symbols to look up (e.g. AAPL, MSFT, NVDA). Resolved to SEC CIK automatically.
## `ciks` (type: `array`):
SEC Central Index Keys, as an alternative or addition to tickers (e.g. 0000320193 or 320193).
## `includeFinancials` (type: `boolean`):
Fetch structured XBRL financials (income statement, balance sheet, cash flow) + computed metrics.
## `maxAnnualYears` (type: `integer`):
How many fiscal years of annual (10-K) financials to include per metric.
## `maxQuarters` (type: `integer`):
How many recent quarters of financials to include per metric.
## `includeFilings` (type: `boolean`):
Add the list of recent SEC filings (10-K, 10-Q, 8-K, etc.) with direct links.
## `maxFilings` (type: `integer`):
Maximum number of recent filings to include per company.
## `includeInsiderFilings` (type: `boolean`):
Include insider transaction forms in the filings list. Off by default (they dominate the feed).
## Actor input object example
```json
{
"tickers": [
"AAPL",
"MSFT"
],
"ciks": [],
"includeFinancials": true,
"maxAnnualYears": 5,
"maxQuarters": 8,
"includeFilings": true,
"maxFilings": 20,
"includeInsiderFilings": false
}
```
# Actor output Schema
## `dataset` (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 '' with your token
const client = new ApifyClient({
token: '',
});
// Prepare Actor input
const input = {
"tickers": [
"AAPL",
"MSFT"
]
};
// Run the Actor and wait for it to finish
const run = await client.actor("foxlabs/sec-edgar-financials").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 '' with your token.
client = ApifyClient("")
# Prepare the Actor input
run_input = { "tickers": [
"AAPL",
"MSFT",
] }
# Run the Actor and wait for it to finish
run = client.actor("foxlabs/sec-edgar-financials").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 '{
"tickers": [
"AAPL",
"MSFT"
]
}' |
apify call foxlabs/sec-edgar-financials --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=foxlabs/sec-edgar-financials",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "SEC EDGAR Financials, Filings & Company Data Scraper",
"description": "Rich US public-company intelligence from the official SEC EDGAR API: full firmographics, multi-year XBRL financial statements (income, balance sheet, cash flow), computed margins & growth, plus recent filings (10-K/10-Q/8-K, insider). Input tickers or CIKs. Free, structured JSON.",
"version": "0.1",
"x-build-id": "wMacedzJA31EHvPFd"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/foxlabs~sec-edgar-financials/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-foxlabs-sec-edgar-financials",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/foxlabs~sec-edgar-financials/runs": {
"post": {
"operationId": "runs-sync-foxlabs-sec-edgar-financials",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/foxlabs~sec-edgar-financials/run-sync": {
"post": {
"operationId": "run-sync-foxlabs-sec-edgar-financials",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
}
},
"components": {
"schemas": {
"inputSchema": {
"type": "object",
"properties": {
"tickers": {
"title": "Stock tickers",
"type": "array",
"description": "Stock ticker symbols to look up (e.g. AAPL, MSFT, NVDA). Resolved to SEC CIK automatically.",
"default": [],
"items": {
"type": "string"
}
},
"ciks": {
"title": "CIK numbers (optional)",
"type": "array",
"description": "SEC Central Index Keys, as an alternative or addition to tickers (e.g. 0000320193 or 320193).",
"default": [],
"items": {
"type": "string"
}
},
"includeFinancials": {
"title": "Include financial statements",
"type": "boolean",
"description": "Fetch structured XBRL financials (income statement, balance sheet, cash flow) + computed metrics.",
"default": true
},
"maxAnnualYears": {
"title": "Annual years",
"minimum": 1,
"maximum": 15,
"type": "integer",
"description": "How many fiscal years of annual (10-K) financials to include per metric.",
"default": 5
},
"maxQuarters": {
"title": "Quarters",
"minimum": 0,
"maximum": 40,
"type": "integer",
"description": "How many recent quarters of financials to include per metric.",
"default": 8
},
"includeFilings": {
"title": "Include recent filings",
"type": "boolean",
"description": "Add the list of recent SEC filings (10-K, 10-Q, 8-K, etc.) with direct links.",
"default": true
},
"maxFilings": {
"title": "Max filings",
"minimum": 1,
"maximum": 1000,
"type": "integer",
"description": "Maximum number of recent filings to include per company.",
"default": 20
},
"includeInsiderFilings": {
"title": "Include insider filings (Form 3/4/5)",
"type": "boolean",
"description": "Include insider transaction forms in the filings list. Off by default (they dominate the feed).",
"default": false
}
}
},
"runsResponseSchema": {
"type": "object",
"properties": {
"data": {
"type": "object",
"properties": {
"id": {
"type": "string"
},
"actId": {
"type": "string"
},
"userId": {
"type": "string"
},
"startedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"finishedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"status": {
"type": "string",
"example": "READY"
},
"meta": {
"type": "object",
"properties": {
"origin": {
"type": "string",
"example": "API"
},
"userAgent": {
"type": "string"
}
}
},
"stats": {
"type": "object",
"properties": {
"inputBodyLen": {
"type": "integer",
"example": 2000
},
"rebootCount": {
"type": "integer",
"example": 0
},
"restartCount": {
"type": "integer",
"example": 0
},
"resurrectCount": {
"type": "integer",
"example": 0
},
"computeUnits": {
"type": "integer",
"example": 0
}
}
},
"options": {
"type": "object",
"properties": {
"build": {
"type": "string",
"example": "latest"
},
"timeoutSecs": {
"type": "integer",
"example": 300
},
"memoryMbytes": {
"type": "integer",
"example": 1024
},
"diskMbytes": {
"type": "integer",
"example": 2048
}
}
},
"buildId": {
"type": "string"
},
"defaultKeyValueStoreId": {
"type": "string"
},
"defaultDatasetId": {
"type": "string"
},
"defaultRequestQueueId": {
"type": "string"
},
"buildNumber": {
"type": "string",
"example": "1.0.0"
},
"containerUrl": {
"type": "string"
},
"usage": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "integer",
"example": 1
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
},
"usageTotalUsd": {
"type": "number",
"example": 0.00005
},
"usageUsd": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "number",
"example": 0.00005
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
}
}
}
}
}
}
}
}
```