# SEC EDGAR Scraper (`trendlab/sec-edgar-scraper`) Actor Get SEC EDGAR data for any US public company: filings, financial statements (XBRL), and insider trades. Clean, AI-ready JSON. No API key needed. - **URL**: https://apify.com/trendlab/sec-edgar-scraper.md - **Developed by:** [Cheoljae Lee](https://apify.com/trendlab) (community) - **Categories:** Developer tools, AI - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $5.00 / 1,000 company processeds This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. 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 Scraper Get **SEC EDGAR data for any US public company** — filings, financial statements (XBRL), company profiles, and insider transactions — as clean, AI-ready JSON. Powered by SEC's official data APIs: reliable, always up to date, and no API key required. ### What does SEC EDGAR Scraper do? Pass any **stock ticker** (AAPL, MSFT, TSLA) or **CIK number** and get back: - 🏢 **Company profile** — name, CIK, tickers, exchanges, SIC industry code, state of incorporation, fiscal year end, address - 📄 **Filings list** — every recent filing with form type, dates, and a direct link to the document. Filter by form type (10-K, 10-Q, 8-K, S-1, DEF 14A…) and date - 💵 **Financial statements (XBRL)** — revenue, net income, assets, liabilities, equity, EPS and any other US-GAAP concept, with the latest value plus history - 👤 **Insider transactions** — Forms 3/4/5 (insider buys and sells) with links to each filing - 🤖 **AI-ready JSON** — normalized output built for LLM pipelines, financial dashboards, and AI agents via the Apify MCP server ### Why scrape SEC EDGAR? Financial analysts, fintech builders, quant researchers, compliance teams, and AI agents use this Actor to: - Track **company fundamentals** across a watchlist without manual EDGAR searches - Monitor **new filings** (8-K events, 10-K/10-Q reports) programmatically - Pull **structured XBRL financials** without parsing raw filing documents - Watch **insider trading activity** (Form 4) across companies - Feed **regulatory & financial data** into models, RAG systems, and AI agents ### Input example ```json { "companies": ["AAPL", "TSLA", "320193"], "dataTypes": ["profile", "filings", "financials", "insiderTransactions"], "formTypes": ["10-K", "10-Q", "8-K"], "maxFilings": 50, "financialConcepts": ["Revenues", "NetIncomeLoss", "Assets", "Liabilities", "StockholdersEquity"] } ```` ### Output example (abridged) ```json { "query": "AAPL", "cik": "0000320193", "name": "Apple Inc.", "profile": { "exchanges": ["Nasdaq"], "sicDescription": "Electronic Computers", "stateOfIncorporation": "CA" }, "filings": [ { "form": "10-Q", "filingDate": "2026-05-01", "url": "https://www.sec.gov/Archives/edgar/data/320193/.../aapl-20260328.htm" } ], "financials": { "Revenues": { "xbrlTag": "RevenueFromContractWithCustomerExcludingAssessedTax", "unit": "USD", "latest": { "value": 111184000000, "end": "2026-03-28", "fiscalYear": 2026, "fiscalPeriod": "Q2" } } }, "insiderTransactions": [ { "form": "4", "filingDate": "2026-06-17", "url": "https://www.sec.gov/Archives/edgar/data/320193/..." } ] } ``` ### Financial concepts (XBRL tags) Companies report financials under standardized US-GAAP tags. Common ones: `Revenues`, `NetIncomeLoss`, `Assets`, `Liabilities`, `StockholdersEquity`, `CashAndCashEquivalentsAtCarryingValue`, `EarningsPerShareBasic`. Tag availability varies by company and era — this Actor automatically resolves common revenue variants so you always get the most recent value. ### How much does it cost? Pay per company processed — a small fee per record. Analyzing 100 companies costs well under $1. No subscription. ### FAQ **Is this legal / affiliated with the SEC?** This Actor uses SEC's official public data APIs (data.sec.gov) and is not affiliated with or endorsed by the SEC. All data is public. We follow SEC's fair-access policy (declared User-Agent, rate limits). **Do I need an API key?** No. SEC EDGAR data is free and public. **Can AI agents use this?** Yes — it works with the Apify MCP server, so Claude, ChatGPT, and other agents can call it and pay per use. **Which companies are covered?** All ~10,000+ US public companies that file with the SEC. Pass a ticker or CIK. ### Support Need a new data type (full Form 4 transaction parsing, fund holdings, full-text filing search)? Open an issue in the **Issues tab** — actively maintained, issues answered within one business day. # Actor input Schema ## `companies` (type: `array`): List of stock tickers (e.g. AAPL, MSFT) or CIK numbers (e.g. 320193). Each is resolved and processed separately. ## `dataTypes` (type: `array`): Which datasets to return for each company. ## `formTypes` (type: `array`): Only include filings of these form types (e.g. 10-K, 10-Q, 8-K, S-1, DEF 14A). Leave empty for all forms. ## `maxFilings` (type: `integer`): Maximum number of recent filings to return per company (most recent first). ## `financialConcepts` (type: `array`): US-GAAP concepts to extract when 'Financial statements' is selected. Common: Revenues, NetIncomeLoss, Assets, Liabilities, StockholdersEquity, CashAndCashEquivalentsAtCarryingValue, EarningsPerShareBasic. ## `filingsSince` (type: `string`): Only include filings on or after this date (YYYY-MM-DD). Leave empty for no lower bound. ## `contactEmail` (type: `string`): SEC requires a contact email in the request User-Agent for its fair-access policy. Your own email is recommended; a default is used if left blank. ## Actor input object example ```json { "companies": [ "AAPL", "MSFT" ], "dataTypes": [ "profile", "filings", "financials" ], "formTypes": [ "10-K", "10-Q", "8-K" ], "maxFilings": 50, "financialConcepts": [ "Revenues", "NetIncomeLoss", "Assets", "Liabilities", "StockholdersEquity" ] } ``` # 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 = { "companies": [ "AAPL", "MSFT" ], "formTypes": [ "10-K", "10-Q", "8-K" ] }; // Run the Actor and wait for it to finish const run = await client.actor("trendlab/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 '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "companies": [ "AAPL", "MSFT", ], "formTypes": [ "10-K", "10-Q", "8-K", ], } # Run the Actor and wait for it to finish run = client.actor("trendlab/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 '{ "companies": [ "AAPL", "MSFT" ], "formTypes": [ "10-K", "10-Q", "8-K" ] }' | apify call trendlab/sec-edgar-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=trendlab/sec-edgar-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "SEC EDGAR Scraper", "description": "Get SEC EDGAR data for any US public company: filings, financial statements (XBRL), and insider trades. Clean, AI-ready JSON. No API key needed.", "version": "0.1", "x-build-id": "JmPutgLlKNSrEpdUZ" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/trendlab~sec-edgar-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-trendlab-sec-edgar-scraper", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/trendlab~sec-edgar-scraper/runs": { "post": { "operationId": "runs-sync-trendlab-sec-edgar-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/trendlab~sec-edgar-scraper/run-sync": { "post": { "operationId": "run-sync-trendlab-sec-edgar-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "required": [ "companies" ], "properties": { "companies": { "title": "Companies (tickers or CIK numbers)", "minItems": 1, "type": "array", "description": "List of stock tickers (e.g. AAPL, MSFT) or CIK numbers (e.g. 320193). Each is resolved and processed separately.", "items": { "type": "string" } }, "dataTypes": { "title": "Data to extract", "uniqueItems": true, "type": "array", "description": "Which datasets to return for each company.", "items": { "type": "string", "enum": [ "profile", "filings", "financials", "insiderTransactions" ], "enumTitles": [ "Company profile", "Filings list", "Financial statements (XBRL)", "Insider transactions (Form 4)" ] }, "default": [ "profile", "filings", "financials" ] }, "formTypes": { "title": "Filing form types (filter)", "type": "array", "description": "Only include filings of these form types (e.g. 10-K, 10-Q, 8-K, S-1, DEF 14A). Leave empty for all forms.", "items": { "type": "string" } }, "maxFilings": { "title": "Max filings per company", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Maximum number of recent filings to return per company (most recent first).", "default": 50 }, "financialConcepts": { "title": "Financial concepts (XBRL tags)", "type": "array", "description": "US-GAAP concepts to extract when 'Financial statements' is selected. Common: Revenues, NetIncomeLoss, Assets, Liabilities, StockholdersEquity, CashAndCashEquivalentsAtCarryingValue, EarningsPerShareBasic.", "default": [ "Revenues", "NetIncomeLoss", "Assets", "Liabilities", "StockholdersEquity" ], "items": { "type": "string" } }, "filingsSince": { "title": "Filings since (date)", "type": "string", "description": "Only include filings on or after this date (YYYY-MM-DD). Leave empty for no lower bound." }, "contactEmail": { "title": "Contact email (for SEC User-Agent)", "type": "string", "description": "SEC requires a contact email in the request User-Agent for its fair-access policy. Your own email is recommended; a default is used if left blank." } } }, "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 } } } } } } } } } } ```