# SEC EDGAR Full-Text Search Scraper (`ninhothedev/sec-fulltext-search-scraper`) Actor $0.5/1K 🔥 Fast SEC EDGAR full-text search scraper! Find filings by keyword — company, form, date & link. No key. JSON, CSV, Excel or API in seconds. Search 10-K, 8-K & more for investment intel & due diligence ⚡ - **URL**: https://apify.com/ninhothedev/sec-fulltext-search-scraper.md - **Developed by:** [ninhothedev](https://apify.com/ninhothedev) (community) - **Categories:** Developer tools, Automation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.50 / 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/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.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/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 Full-Text Search Scraper Search the **entire SEC EDGAR full-text filings index by keyword** and get back clean, structured results: company name, CIK, form type, filing date, and a **direct link to the filing document** — with **no API key** required. Perfect for **filings research, investment intelligence, compliance monitoring, and due diligence**. Point it at a phrase like `"artificial intelligence"`, `"going concern"`, `"material weakness"`, or a competitor's product name, optionally narrow by form type (`10-K`, `8-K`, `10-Q`, …) and date range, and export every matching filing to JSON, CSV, or Excel. --- ### Why this scraper - **No API key, no login.** The SEC provides open full-text search; this actor is ready the moment you run it. - **Direct filing URLs.** Every result includes the exact `https://www.sec.gov/Archives/...` document link, built from the accession number and CIK. - **Multi-query.** Run a whole list of keywords in one job — great for watchlists and topic monitoring. - **Filter by form and date.** Focus on annual reports, current reports, proxy statements, or a specific window. - **Cheap & fast.** Datacenter-friendly, one item per filing, tiny memory footprint. > Built responsibly: the actor sends a descriptive `User-Agent` with a contact email on every request, as required by the SEC fair-access policy. --- ### Input | Field | Type | Description | |-------|------|-------------| | `mode` | select | `search` — run keyword queries against the EDGAR full-text index. | | `queries` | array | Keywords/phrases to search. Wrap in double quotes for exact-phrase match. Prefilled: `["artificial intelligence", "cybersecurity risk"]`. | | `forms` | string | Optional. Restrict to form types, comma-separated (e.g. `10-K` or `8-K,10-Q`). | | `startDate` | string | Optional. Only filings on/after this date (`YYYY-MM-DD`). | | `endDate` | string | Optional. Only filings on/before this date (`YYYY-MM-DD`). | | `maxItems` | integer | Max total filings across all queries. Default `100`, max `1000`. | #### Example input ```json { "mode": "search", "queries": ["artificial intelligence", "supply chain risk"], "forms": "10-K", "startDate": "2024-01-01", "endDate": "2024-12-31", "maxItems": 200 } ```` *** ### Output One dataset item per matching filing. All fields are nullable. ```json { "query": "artificial intelligence", "accession": "0001161697-21-000289", "document": "form_10-k.htm", "company": "Artificial Intelligence Technology Solutions Inc. (AITX) (CIK 0001498148)", "ciks": ["0001498148"], "form": "10-K", "file_date": "2021-06-01", "file_type": "10-K", "file_description": "FORM 10-K ANNUAL REPORT FOR 02-28-2021", "sics": ["3714"], "states": ["NV"], "filing_url": "https://www.sec.gov/Archives/edgar/data/1498148/000116169721000289/form_10-k.htm", "source": "sec", "scraped_at": "2026-07-20T00:00:00+00:00" } ``` | Field | Description | |-------|-------------| | `query` | The search term that produced this hit. | | `accession` | Filing accession number (`_id` before the `:`). | | `document` | Primary document filename (`_id` after the `:`). | | `company` | Company display name incl. ticker and CIK. | | `ciks` | List of associated CIK identifiers. | | `form` | SEC form type (e.g. `10-K`, `8-K`). | | `file_date` | Filing date, ISO `YYYY-MM-DD`. | | `file_type` | Document type label. | | `file_description` | Human-readable filing description. | | `sics` | Standard Industrial Classification codes. | | `states` | Business location state(s). | | `filing_url` | Direct URL to the filing document on SEC.gov. | | `source` | Always `sec`. | | `scraped_at` | UTC timestamp when the record was scraped. | *** ### Pricing Roughly **$0.5 per 1,000 filings** — pay only for what you pull. Datacenter proxies are fine; no residential proxy needed. *** ### Use cases - **Filings research** — find every company discussing a topic, technology, or risk factor. - **Investment intelligence** — surface disclosures across an entire sector or theme. - **Compliance** — monitor for keywords (restatements, going concern, cyber incidents) across new filings. - **Due diligence** — pull a target's filings and cross-reference language against peers. *** ### Related actors - [SEC EDGAR Scraper](https://apify.com/ninhothedev/sec-edgar-scraper) - [CourtListener Scraper](https://apify.com/ninhothedev/courtlistener-scraper) - [GLEIF LEI Scraper](https://apify.com/ninhothedev/gleif-scraper) - [FDIC Banks Scraper](https://apify.com/ninhothedev/fdic-banks-scraper) *** ### Keywords SEC EDGAR scraper, full-text search, SEC filings API, 10-K scraper, 8-K scraper, 10-Q, financial filings research, investment intelligence, compliance monitoring, due diligence, company disclosures, CIK, accession number, regulatory data, no API key. *** ### FAQ **Do I need an SEC API key?** No. SEC full-text search is open. The actor sends a compliant contact `User-Agent` automatically. **How far back does full-text search go?** SEC full-text search covers filings from 2001 onward. **Can I search exact phrases?** Yes — wrap the phrase in double quotes, e.g. `"material weakness"`. **How many results per query?** The index returns up to 100 hits per page and the actor paginates; use `maxItems` to cap the total. # Actor input Schema ## `mode` (type: `string`): What to scrape. Currently 'search' runs keyword queries against the SEC EDGAR full-text search index and returns one item per matching filing. ## `queries` (type: `array`): Keywords or phrases to search across SEC filings. Wrap a phrase in double quotes for an exact-phrase match (e.g. "artificial intelligence"). Each query is searched independently. ## `forms` (type: `string`): Restrict results to one or more SEC form types, comma-separated (e.g. '10-K' or '8-K' or '10-K,10-Q'). Leave empty to search all forms. ## `startDate` (type: `string`): Only include filings dated on or after this date, format YYYY-MM-DD (e.g. 2024-01-01). Leave empty for no lower bound. ## `endDate` (type: `string`): Only include filings dated on or before this date, format YYYY-MM-DD (e.g. 2024-12-31). Leave empty for no upper bound. ## `maxItems` (type: `integer`): Maximum total number of filings to return across all queries. Default 100, maximum 1000. ## Actor input object example ```json { "mode": "search", "queries": [ "artificial intelligence", "cybersecurity risk" ], "forms": "10-K", "startDate": "2024-01-01", "endDate": "2024-12-31", "maxItems": 100 } ``` # 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 = { "queries": [ "artificial intelligence", "cybersecurity risk" ] }; // Run the Actor and wait for it to finish const run = await client.actor("ninhothedev/sec-fulltext-search-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 = { "queries": [ "artificial intelligence", "cybersecurity risk", ] } # Run the Actor and wait for it to finish run = client.actor("ninhothedev/sec-fulltext-search-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 '{ "queries": [ "artificial intelligence", "cybersecurity risk" ] }' | apify call ninhothedev/sec-fulltext-search-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=ninhothedev/sec-fulltext-search-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "SEC EDGAR Full-Text Search Scraper", "description": "$0.5/1K 🔥 Fast SEC EDGAR full-text search scraper! Find filings by keyword — company, form, date & link. No key. JSON, CSV, Excel or API in seconds. Search 10-K, 8-K & more for investment intel & due diligence ⚡", "version": "0.1", "x-build-id": "kcLTnQ6v0PUGtu9Sy" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/ninhothedev~sec-fulltext-search-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-ninhothedev-sec-fulltext-search-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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/ninhothedev~sec-fulltext-search-scraper/runs": { "post": { "operationId": "runs-sync-ninhothedev-sec-fulltext-search-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/ninhothedev~sec-fulltext-search-scraper/run-sync": { "post": { "operationId": "run-sync-ninhothedev-sec-fulltext-search-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": [ "mode", "queries" ], "properties": { "mode": { "title": "Mode", "enum": [ "search" ], "type": "string", "description": "What to scrape. Currently 'search' runs keyword queries against the SEC EDGAR full-text search index and returns one item per matching filing.", "default": "search" }, "queries": { "title": "Search queries", "type": "array", "description": "Keywords or phrases to search across SEC filings. Wrap a phrase in double quotes for an exact-phrase match (e.g. \"artificial intelligence\"). Each query is searched independently.", "default": [ "artificial intelligence", "cybersecurity risk" ], "items": { "type": "string" } }, "forms": { "title": "Form types (optional)", "type": "string", "description": "Restrict results to one or more SEC form types, comma-separated (e.g. '10-K' or '8-K' or '10-K,10-Q'). Leave empty to search all forms." }, "startDate": { "title": "Start date (optional)", "type": "string", "description": "Only include filings dated on or after this date, format YYYY-MM-DD (e.g. 2024-01-01). Leave empty for no lower bound." }, "endDate": { "title": "End date (optional)", "type": "string", "description": "Only include filings dated on or before this date, format YYYY-MM-DD (e.g. 2024-12-31). Leave empty for no upper bound." }, "maxItems": { "title": "Max items", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Maximum total number of filings to return across all queries. Default 100, maximum 1000.", "default": 100 } } }, "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 } } } } } } } } } } ```