# SEC Schedule 13D Activist Ownership Scraper (`automation-lab/sec-schedule-13d-ownership-scraper`) Actor 📈 Extract SEC Schedule 13D and 13D/A activist ownership filings, reporting persons, shares, percentages, CUSIPs, Item 4 purpose, and canonical links. - **URL**: https://apify.com/automation-lab/sec-schedule-13d-ownership-scraper.md - **Developed by:** [Stas Persiianenko](https://apify.com/automation-lab) (community) - **Categories:** Other - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing Pay per event This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. 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 Schedule 13D Activist Ownership Scraper Turn public SEC EDGAR Schedule 13D and 13D/A filings into structured activist-ownership records. Monitor new 5% ownership disclosures, identify reporting persons, compare amendments, and feed canonical filing links into research or compliance workflows. The Actor uses SEC public archives directly over HTTP. It needs no browser, proxy, login, or paid data provider. ### What does this SEC Schedule 13D scraper do? It scans quarterly EDGAR master indexes or accepts specific SEC filing URLs. For each matching filing it resolves the accession index and primary document, then normalizes filing and ownership details. Use it for one-off research, recurring activist screens, amendment tracking, or financial-data enrichment. ### Who is it for? - 📈 Event-driven funds monitoring activist positions. - 🧭 Activist-investing researchers building target timelines. - 🛡️ Compliance teams reviewing beneficial-ownership disclosures. - 🗄️ Financial-data teams maintaining EDGAR pipelines. - 📰 Journalists investigating ownership and control changes. ### Why use this Actor? Schedule 13D documents vary across XHTML, XML, and legacy filing layouts. This Actor handles discovery, canonical URL resolution, bounded retries, polite request pacing, and normalized export. Results can be downloaded as JSON, CSV, Excel, XML, or RSS through Apify datasets. ### What data can you extract? | Field | Meaning | |---|---| | `issuerName` | Company or issuer named in the filing | | `issuerCik` | SEC Central Index Key | | `filingType` | `SC 13D` or `SC 13D/A` | | `filingDate` | Filing date from EDGAR | | `accessionNumber` | Stable SEC accession identifier | | `amendment` | Whether the filing is an amendment | | `reportingPersons` | Names of reporting persons | | `securityClass` | Class of securities | | `cusip` | CUSIP shown in the filing | | `sharesBeneficiallyOwned` | Aggregate beneficial shares | | `percentOfClass` | Reported ownership percentage | | `sourceOfFunds` | Schedule 13D source-of-funds code | | `purposeOfTransaction` | Normalized Item 4 narrative | | `filingIndexUrl` | Canonical accession directory | | `documentUrl` | Primary SEC document | | `scrapedAt` | Extraction timestamp | ### How to scrape SEC Schedule 13D filings 1. Open the Actor input page. 2. Keep the prefilled quarter or add quarters such as `2025/QTR4`. 3. Set a small `maxItems` for your first run. 4. Optionally paste specific SEC Archives filing URLs. 5. Keep a descriptive SEC-compliant User-Agent. 6. Start the Actor. 7. Export the default dataset in your preferred format. ### Input ```json { "quarters": ["2026/QTR2"], "maxItems": 100, "requestDelayMillis": 150, "userAgent": "Your Organization contact@example.com" } ```` `filingUrls` accepts SEC accession or primary-document URLs. `quarters` uses `YYYY/QTRN` values and scans only `SC 13D` and `SC 13D/A` rows. `maxItems` caps saved filing records across all inputs. `requestDelayMillis` supports SEC fair-access pacing and cannot effectively go below 120 ms. ### Output example ```json { "issuerName": "Example Issuer, Inc.", "issuerCik": "1234567", "filingType": "SC 13D/A", "filingDate": "2026-05-04", "accessionNumber": "0000000000-26-000001", "amendment": true, "reportingPersons": ["Example Investor LLC"], "securityClass": "Common Stock", "cusip": "123456789", "sharesBeneficiallyOwned": "5,547,360", "percentOfClass": "16.6 %", "sourceOfFunds": "WC", "filingIndexUrl": "https://www.sec.gov/Archives/edgar/data/.../", "documentUrl": "https://www.sec.gov/Archives/edgar/data/.../primary_doc.xml" } ``` Values are preserved as filing text where numeric formatting may carry meaning. ### How much does it cost to scrape Schedule 13D filings? The Actor uses pay-per-event pricing. A small one-time start charge covers run initialization. Each successfully saved filing is charged as one `item` event. Tier discounts reduce the per-filing rate for larger Apify plans. You can set `maxItems` to establish a hard output bound before running. ### Tips for reliable monitoring - Scan only newly completed quarters in scheduled runs. - Store accession numbers as stable deduplication keys. - Use `filingType` and `amendment` to separate initial positions from updates. - Compare `percentOfClass` and `sharesBeneficiallyOwned` across amendments. - Retain SEC URLs for auditability. - Use a real organization and contact address in `userAgent`. - Avoid unnecessary repeated historical scans. ### Integrations Connect datasets to Google Sheets for analyst review. Send new records to Slack or email through Apify integrations. Load CSV exports into Snowflake, BigQuery, or PostgreSQL. Trigger the Actor daily from Apify Schedules and deduplicate by accession number. Use webhooks to launch enrichment when a new activist filing appears. ### API usage Run the Actor from JavaScript, Python, or cURL with the examples below. Replace the token placeholder with your Apify API token and keep production limits explicit. ### JavaScript API example ```javascript import { ApifyClient } from 'apify-client'; const client = new ApifyClient({ token: process.env.APIFY_TOKEN }); const run = await client.actor('automation-lab/sec-schedule-13d-ownership-scraper').call({ quarters: ['2026/QTR2'], maxItems: 100, }); const { items } = await client.dataset(run.defaultDatasetId).listItems(); console.log(items); ``` ### Python API example ```python from apify_client import ApifyClient client = ApifyClient('YOUR_APIFY_TOKEN') run = client.actor('automation-lab/sec-schedule-13d-ownership-scraper').call(run_input={ 'quarters': ['2026/QTR2'], 'maxItems': 100, }) items = client.dataset(run['defaultDatasetId']).list_items().items print(items) ``` ### cURL API example ```bash curl -X POST 'https://api.apify.com/v2/acts/automation-lab~sec-schedule-13d-ownership-scraper/runs?token=YOUR_APIFY_TOKEN' \ -H 'Content-Type: application/json' \ -d '{"quarters":["2026/QTR2"],"maxItems":100}' ``` Poll the returned run ID, then download records from its default dataset. ### MCP and AI workflows Use the Actor through Apify MCP: `https://mcp.apify.com?tools=automation-lab/sec-schedule-13d-ownership-scraper` Add the server in Claude Code: ```bash claude mcp add apify-sec-13d --transport http 'https://mcp.apify.com?tools=automation-lab/sec-schedule-13d-ownership-scraper' ``` Claude Desktop JSON configuration: ```json { "mcpServers": { "apify-sec-13d": { "url": "https://mcp.apify.com?tools=automation-lab/sec-schedule-13d-ownership-scraper" } } } ``` Example prompts showing MCP usage: Example Claude Code prompt: > Use the Apify MCP tool to run the SEC Schedule 13D scraper for 2026/QTR2, return 100 filings, and summarize amendments above 10% ownership. Example Claude Desktop prompt: > Through MCP, extract these SEC filing URLs and compare beneficial ownership by accession number. MCP makes the structured dataset available to agentic research without custom scraping code. ### Fair access and legality SEC EDGAR filings are public United States government records. Users remain responsible for lawful use, retention, redistribution, and investment or compliance decisions. The Actor sends a descriptive User-Agent, limits request frequency, retries transient responses with backoff, and uses no identity-hiding proxy by default. Do not use the output as the sole basis for legal or investment advice. ### Limitations Historical Schedule 13D layouts are not fully uniform. Some filings include exhibits or combined submissions rather than a standalone primary file. Optional normalized fields may be absent when a filing does not state them in a recognizable layout. Quarterly indexes include accepted filings, not real-time intraday alerts. SEC maintenance or fair-access responses can temporarily delay requests. ### Troubleshooting **Why did a filing produce no record?** Check that the URL belongs to `www.sec.gov/Archives/edgar/data/` and represents a Schedule 13D filing. The log names skipped malformed filings. **Why are some ownership fields missing?** Older or exhibit-heavy filings may use a nonstandard layout. Canonical document URLs remain available for review. **Why did SEC return 403 or 429?** Use a descriptive User-Agent with a contact address, keep request pacing enabled, and retry later instead of increasing concurrency. **Why are there fewer results than `maxItems`?** The selected quarter may contain fewer matching forms, or malformed filings may have been skipped. ### Related SEC scrapers Explore other Automation Lab actors for adjacent filings: - [SEC Form D Scraper](https://apify.com/automation-lab/sec-form-d-scraper) for private offering notices. - [SEC filing actors](https://apify.com/automation-lab) for complementary EDGAR workflows. Schedule 13D records are distinct from Form D fundraising and Form 4 insider transactions. ### FAQ **Does this include Schedule 13G?** No. The Actor intentionally targets activist-style Schedule 13D and 13D/A forms. **Can I scrape a specific filing?** Yes. Add its SEC Archives URL to `filingUrls` and set `quarters` to an empty list. **Can I monitor multiple quarters?** Yes. Add multiple `YYYY/QTRN` strings and use `maxItems` to bound output. **Does it require a proxy?** No. Public SEC endpoints are accessed directly with fair-access headers and pacing. **What is the deduplication key?** Use `accessionNumber`, which uniquely identifies an SEC submission. **Can I schedule daily runs?** Yes. Use Apify Schedules, export the dataset, and compare accession numbers against your previous run. ### Support When reporting an extraction problem, include the accession number, filing URL, expected field, and Actor run ID. That evidence makes layout-specific fixes faster while preserving reproducibility. # Actor input Schema ## `filingUrls` (type: `array`): Optional SEC Archives filing or primary-document URLs to extract. ## `quarters` (type: `array`): Quarterly master indexes to scan, formatted YYYY/QTRN. Schedule 13D and 13D/A only. ## `maxItems` (type: `integer`): Maximum Schedule 13D filing records to save. ## `userAgent` (type: `string`): Descriptive organization/contact User-Agent sent to SEC.gov. ## `requestDelayMillis` (type: `integer`): Polite delay between SEC filing requests. Minimum effective delay is 120 ms. ## Actor input object example ```json { "filingUrls": [ { "url": "https://www.sec.gov/Archives/edgar/data/22701/000121390026050832/xslSCHEDULE_13D_X02/primary_doc.xml" } ], "quarters": [ "2026/QTR2" ], "maxItems": 10, "userAgent": "Automation Lab SEC research actor support@automation-lab.ai", "requestDelayMillis": 150 } ``` # Actor output Schema ## `overview` (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 = { "filingUrls": [ { "url": "https://www.sec.gov/Archives/edgar/data/22701/000121390026050832/xslSCHEDULE_13D_X02/primary_doc.xml" } ], "quarters": [ "2026/QTR2" ], "maxItems": 10 }; // Run the Actor and wait for it to finish const run = await client.actor("automation-lab/sec-schedule-13d-ownership-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 = { "filingUrls": [{ "url": "https://www.sec.gov/Archives/edgar/data/22701/000121390026050832/xslSCHEDULE_13D_X02/primary_doc.xml" }], "quarters": ["2026/QTR2"], "maxItems": 10, } # Run the Actor and wait for it to finish run = client.actor("automation-lab/sec-schedule-13d-ownership-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 '{ "filingUrls": [ { "url": "https://www.sec.gov/Archives/edgar/data/22701/000121390026050832/xslSCHEDULE_13D_X02/primary_doc.xml" } ], "quarters": [ "2026/QTR2" ], "maxItems": 10 }' | apify call automation-lab/sec-schedule-13d-ownership-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=automation-lab/sec-schedule-13d-ownership-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "SEC Schedule 13D Activist Ownership Scraper", "description": "📈 Extract SEC Schedule 13D and 13D/A activist ownership filings, reporting persons, shares, percentages, CUSIPs, Item 4 purpose, and canonical links.", "version": "0.1", "x-build-id": "1cNL906fDj2aHK2ph" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/automation-lab~sec-schedule-13d-ownership-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-automation-lab-sec-schedule-13d-ownership-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/automation-lab~sec-schedule-13d-ownership-scraper/runs": { "post": { "operationId": "runs-sync-automation-lab-sec-schedule-13d-ownership-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/automation-lab~sec-schedule-13d-ownership-scraper/run-sync": { "post": { "operationId": "run-sync-automation-lab-sec-schedule-13d-ownership-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", "properties": { "filingUrls": { "title": "📄 SEC filing URLs", "type": "array", "description": "Optional SEC Archives filing or primary-document URLs to extract.", "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } }, "quarters": { "title": "📅 EDGAR quarters", "type": "array", "description": "Quarterly master indexes to scan, formatted YYYY/QTRN. Schedule 13D and 13D/A only.", "default": [ "2026/QTR2" ], "items": { "type": "string" } }, "maxItems": { "title": "Maximum filings", "minimum": 1, "maximum": 5000, "type": "integer", "description": "Maximum Schedule 13D filing records to save.", "default": 10 }, "userAgent": { "title": "SEC-compliant User-Agent", "type": "string", "description": "Descriptive organization/contact User-Agent sent to SEC.gov.", "default": "Automation Lab SEC research actor support@automation-lab.ai" }, "requestDelayMillis": { "title": "Delay between filing requests (ms)", "minimum": 120, "maximum": 5000, "type": "integer", "description": "Polite delay between SEC filing requests. Minimum effective delay is 120 ms.", "default": 150 } } }, "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 } } } } } } } } } } ```