# SEC EDGAR Intel: Filings, Financials & Full-Text Search (`obsidian937/sec-edgar-intel`) Actor Turn SEC EDGAR into structured data. Track any US public company's filings (10-K, 8-K, 13F and more), pull clean XBRL financials as a time series, or run full-text search across every filing. Official SEC public data, no API key, no proxy. Delta mode for recurring filing and keyword monitoring. - **URL**: https://apify.com/obsidian937/sec-edgar-intel.md - **Developed by:** [Obsidian IT Consulting SRL](https://apify.com/obsidian937) (community) - **Categories:** Developer tools, Lead generation, News - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $3.00 / 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 Intel: Filings, Financials & Full-Text Search Turn the U.S. Securities and Exchange Commission's EDGAR system into clean, structured data you can drop into a spreadsheet, database, or model. Track any public company's filings, pull audited XBRL financials as a time series, or search the full text of every filing for a keyword or phrase. Built on the official SEC public data endpoints. No API key. No proxy. No login. ### Three modes #### 1. Filings (per company) Give it tickers or CIK numbers and get every recent filing back as structured rows: form type, filing date, report date, accession number, and direct links to the primary document. Filter by form (10-K, 10-Q, 8-K, S-1, 13F-HR, Form 4, and so on). Use it to monitor a portfolio, watch competitors, or feed a compliance pipeline. Turn on **delta mode** and a scheduled run emits only filings that appeared since the last run, so a schedule plus webhook becomes a real-time filing alert. #### 2. Financials (XBRL facts) Pull headline numbers straight from the structured XBRL data companies file: revenue, net income, operating income, assets, liabilities, equity, cash, EPS, and any other US-GAAP concept you name. Each row is one reported value for one period, so you get a ready-made time series. Set **annual only** to drop quarterly noise and keep 10-K / 20-F figures. #### 3. Full-text search Search the full text of filings from roughly the last ten years. Quote a phrase for an exact match ("going concern", "artificial intelligence", "material weakness"), narrow by form and date range, and get back the matching filings with company, form, date, and a link to the document. Great for thematic research and competitive intelligence. Delta mode turns it into a recurring keyword watch. ### Example input Monitor Apple and Microsoft 8-K filings, only new ones each run: ```json { "mode": "filings", "companies": ["AAPL", "MSFT"], "forms": ["8-K"], "deltaMode": true } ```` Pull annual revenue and net income for NVIDIA: ```json { "mode": "financials", "companies": ["NVDA"], "concepts": ["Revenues", "NetIncomeLoss"], "annualOnly": true } ``` Find every recent filing that mentions "stock split": ```json { "mode": "search", "searchQuery": "\"stock split\"", "forms": ["8-K"], "startdt": "2026-01-01" } ``` ### Output One row per record. Filings carry `form`, `filingDate`, `accessionNumber`, `documentUrl`. Financial facts carry `concept`, `value`, `unit`, `fiscalYear`, `fiscalPeriod`, `form`, `filed`. Search hits carry `company`, `ticker`, `form`, `fileDate`, `documentUrl`. ### A note on fair access SEC asks that automated clients send a descriptive User-Agent with a contact and stay under 10 requests per second. This actor does both automatically; you can set your own contact in the input. ### Part of the B2B data suite Pair this with our other structured-source actors for sales, research, and competitive intelligence: - **GitHub Intel** (repos, developer leads, stargazer lists) - **Hacker News Intel** (Who's Hiring jobs, Show HN launches, keyword monitor) - **Y Combinator Companies Scraper** - **IndieHackers Product Scraper** - **BetaList Startup Scraper** # Actor input Schema ## `mode` (type: `string`): What to extract: company filings, XBRL financials, or a full-text search across filings. ## `companies` (type: `array`): Ticker symbols (e.g. "AAPL", "MSFT") or raw CIK numbers (e.g. "320193"). Used by filings and financials modes. ## `forms` (type: `array`): Filter to specific filing forms, e.g. "10-K", "10-Q", "8-K", "S-1", "13F-HR", "4". Empty = all forms. Used by filings and search modes. ## `concepts` (type: `array`): US-GAAP concept tags to pull, e.g. "Revenues", "NetIncomeLoss", "Assets". Empty = a sensible default set of headline financials. Used by financials mode. ## `taxonomy` (type: `string`): XBRL taxonomy for the concepts (financials mode). Almost always us-gaap. ## `annualOnly` (type: `boolean`): Keep only annual-report facts (10-K / 20-F), dropping quarterly noise (financials mode). ## `searchQuery` (type: `string`): Full-text query across filings. Quote a phrase for exact match, e.g. '"artificial intelligence"' or '"going concern"' (search mode). ## `startdt` (type: `string`): Earliest filing date, e.g. "2026-01-01" (search mode). ## `enddt` (type: `string`): Latest filing date, e.g. "2026-06-30" (search mode). ## `deltaMode` (type: `boolean`): Only emit filings new since the previous run (per-account state). Turns the actor into a recurring filing or keyword monitor. Pair with a schedule + webhook for alerts. Used by filings and search modes. ## `userAgent` (type: `string`): SEC requires a descriptive User-Agent carrying a contact, e.g. "Acme Research jane@acme.com". Optional: a working default is used if left empty. ## `maxItems` (type: `integer`): Cap on records to return across all companies. Full-text search is capped at 1000 by the SEC API. ## Actor input object example ```json { "mode": "filings", "companies": [ "AAPL" ], "forms": [], "concepts": [], "taxonomy": "us-gaap", "annualOnly": false, "searchQuery": "", "startdt": "", "enddt": "", "deltaMode": false, "userAgent": "", "maxItems": 200 } ``` # 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 = {}; // Run the Actor and wait for it to finish const run = await client.actor("obsidian937/sec-edgar-intel").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 = {} # Run the Actor and wait for it to finish run = client.actor("obsidian937/sec-edgar-intel").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 '{}' | apify call obsidian937/sec-edgar-intel --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=obsidian937/sec-edgar-intel", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "SEC EDGAR Intel: Filings, Financials & Full-Text Search", "description": "Turn SEC EDGAR into structured data. Track any US public company's filings (10-K, 8-K, 13F and more), pull clean XBRL financials as a time series, or run full-text search across every filing. Official SEC public data, no API key, no proxy. Delta mode for recurring filing and keyword monitoring.", "version": "1.0", "x-build-id": "S852Q16JFhqaeQ7Sc" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/obsidian937~sec-edgar-intel/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-obsidian937-sec-edgar-intel", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/obsidian937~sec-edgar-intel/runs": { "post": { "operationId": "runs-sync-obsidian937-sec-edgar-intel", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/obsidian937~sec-edgar-intel/run-sync": { "post": { "operationId": "run-sync-obsidian937-sec-edgar-intel", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "mode": { "title": "Mode", "enum": [ "filings", "financials", "search" ], "type": "string", "description": "What to extract: company filings, XBRL financials, or a full-text search across filings.", "default": "filings" }, "companies": { "title": "Companies (tickers or CIKs)", "type": "array", "description": "Ticker symbols (e.g. \"AAPL\", \"MSFT\") or raw CIK numbers (e.g. \"320193\"). Used by filings and financials modes.", "default": [ "AAPL" ], "items": { "type": "string" } }, "forms": { "title": "Form types", "type": "array", "description": "Filter to specific filing forms, e.g. \"10-K\", \"10-Q\", \"8-K\", \"S-1\", \"13F-HR\", \"4\". Empty = all forms. Used by filings and search modes.", "default": [], "items": { "type": "string" } }, "concepts": { "title": "XBRL concepts", "type": "array", "description": "US-GAAP concept tags to pull, e.g. \"Revenues\", \"NetIncomeLoss\", \"Assets\". Empty = a sensible default set of headline financials. Used by financials mode.", "default": [], "items": { "type": "string" } }, "taxonomy": { "title": "Taxonomy", "enum": [ "us-gaap", "ifrs-full", "dei" ], "type": "string", "description": "XBRL taxonomy for the concepts (financials mode). Almost always us-gaap.", "default": "us-gaap" }, "annualOnly": { "title": "Annual figures only", "type": "boolean", "description": "Keep only annual-report facts (10-K / 20-F), dropping quarterly noise (financials mode).", "default": false }, "searchQuery": { "title": "Search query", "type": "string", "description": "Full-text query across filings. Quote a phrase for exact match, e.g. '\"artificial intelligence\"' or '\"going concern\"' (search mode).", "default": "" }, "startdt": { "title": "Start date", "type": "string", "description": "Earliest filing date, e.g. \"2026-01-01\" (search mode).", "default": "" }, "enddt": { "title": "End date", "type": "string", "description": "Latest filing date, e.g. \"2026-06-30\" (search mode).", "default": "" }, "deltaMode": { "title": "Delta / monitor mode", "type": "boolean", "description": "Only emit filings new since the previous run (per-account state). Turns the actor into a recurring filing or keyword monitor. Pair with a schedule + webhook for alerts. Used by filings and search modes.", "default": false }, "userAgent": { "title": "User-Agent (contact)", "type": "string", "description": "SEC requires a descriptive User-Agent carrying a contact, e.g. \"Acme Research jane@acme.com\". Optional: a working default is used if left empty.", "default": "" }, "maxItems": { "title": "Max items", "type": "integer", "description": "Cap on records to return across all companies. Full-text search is capped at 1000 by the SEC API.", "default": 200 } } }, "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 } } } } } } } } } } ```