# Stock Market Fundamentals Scraper (`scrapemint/stock-market-fundamentals-scraper`) Actor Revenue, net income, EPS, assets, cash flow and other financial-statement line items per stock ticker, straight from official SEC filings (XBRL). Keyless JSON, no browser and no proxy. - **URL**: https://apify.com/scrapemint/stock-market-fundamentals-scraper.md - **Developed by:** [Ken M](https://apify.com/scrapemint) (community) - **Categories:** Business, News - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## 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 ## Stock Market Fundamentals Scraper Financial-statement line items for any public company, straight from official **SEC filings**: revenue, net income, EPS, total assets, shareholders equity, operating cash flow, capital expenditures and more. No login, no API key, no proxy. It reads the SEC's keyless XBRL data, so the numbers are the same ones companies file, returned as clean JSON. ### What you get One row per metric per reporting period: ```json { "symbol": "AAPL", "cik": 320193, "concept": "NetIncomeLoss", "label": "Net income", "unit": "USD", "value": 29578000000, "fiscalYear": 2026, "fiscalPeriod": "Q2", "periodEnd": "2026-03-28", "form": "10-Q", "filed": "2026-05-01", "accession": "0000320193-26-000061" } ```` By default you get a curated set of common income-statement, balance-sheet and cash-flow items. Set `includeAllConcepts` to pull every concept a company reports (hundreds), or pass `metrics` to pick specific XBRL tags. ### Input | Field | Description | | --- | --- | | `tickers` | Symbols to fetch, e.g. `["AAPL","MSFT"]` (required) | | `metrics` | Optional list of XBRL concepts, e.g. `["Revenues","NetIncomeLoss"]` | | `includeAllConcepts` | Return every reported concept (overrides `metrics`) | | `forms` | Filing forms to include (default `["10-K","10-Q"]`) | | `minYear` | Only periods ending in this year or later | | `latestOnly` | Only the most recent value per metric | ### Example ```json { "tickers": ["AAPL"], "metrics": ["Revenues", "NetIncomeLoss", "EarningsPerShareDiluted"], "minYear": 2022 } ``` ### Who it's for Analysts and quants building models, fintech apps and dashboards showing fundamentals, screeners, and researchers who want clean financials without paying for a data terminal. Completes the stock-market data set with the **Stock Market Earnings Calendar** (when companies report) and **Stock Market Price History** (the chart). ### Pricing Pay per fundamentals row. The first 15 rows of every run are free so you can validate the output before you pay. # Actor input Schema ## `tickers` (type: `array`): Stock symbols to fetch, e.g. \["AAPL", "MSFT"]. ## `metrics` (type: `array`): Limit to specific XBRL concept names (e.g. \["Revenues","NetIncomeLoss"]). Leave empty to return the curated set of common financial-statement line items. ## `includeAllConcepts` (type: `boolean`): Return every us-gaap concept the company reports (hundreds), not just the curated set. Overrides Metrics. ## `forms` (type: `array`): Only include data points from these filing forms. ## `minYear` (type: `integer`): Only include data points whose period ends in this year or later. Leave empty for full history. ## `latestOnly` (type: `boolean`): Return only the most recent data point for each metric instead of full history. ## `maxRowsPerTicker` (type: `integer`): Cap fundamentals rows returned per ticker. ## `maxRowsTotal` (type: `integer`): Stop after this many rows across all tickers. ## Actor input object example ```json { "tickers": [ "AAPL", "MSFT" ], "metrics": [ "Revenues", "NetIncomeLoss", "EarningsPerShareDiluted" ], "includeAllConcepts": false, "forms": [ "10-K", "10-Q" ], "minYear": 2020, "latestOnly": false, "maxRowsPerTicker": 5000, "maxRowsTotal": 50000 } ``` # 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" ], "metrics": [] }; // Run the Actor and wait for it to finish const run = await client.actor("scrapemint/stock-market-fundamentals-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 = { "tickers": ["AAPL"], "metrics": [], } # Run the Actor and wait for it to finish run = client.actor("scrapemint/stock-market-fundamentals-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 '{ "tickers": [ "AAPL" ], "metrics": [] }' | apify call scrapemint/stock-market-fundamentals-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scrapemint/stock-market-fundamentals-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Stock Market Fundamentals Scraper", "description": "Revenue, net income, EPS, assets, cash flow and other financial-statement line items per stock ticker, straight from official SEC filings (XBRL). Keyless JSON, no browser and no proxy.", "version": "0.1", "x-build-id": "cCkteCZZGKo4YkTu3" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scrapemint~stock-market-fundamentals-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scrapemint-stock-market-fundamentals-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/scrapemint~stock-market-fundamentals-scraper/runs": { "post": { "operationId": "runs-sync-scrapemint-stock-market-fundamentals-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/scrapemint~stock-market-fundamentals-scraper/run-sync": { "post": { "operationId": "run-sync-scrapemint-stock-market-fundamentals-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": [ "tickers" ], "properties": { "tickers": { "title": "Tickers", "type": "array", "description": "Stock symbols to fetch, e.g. [\"AAPL\", \"MSFT\"].", "items": { "type": "string" } }, "metrics": { "title": "Metrics (optional)", "type": "array", "description": "Limit to specific XBRL concept names (e.g. [\"Revenues\",\"NetIncomeLoss\"]). Leave empty to return the curated set of common financial-statement line items.", "items": { "type": "string" } }, "includeAllConcepts": { "title": "Include all concepts", "type": "boolean", "description": "Return every us-gaap concept the company reports (hundreds), not just the curated set. Overrides Metrics.", "default": false }, "forms": { "title": "Filing forms", "type": "array", "description": "Only include data points from these filing forms.", "default": [ "10-K", "10-Q" ], "items": { "type": "string" } }, "minYear": { "title": "Minimum year", "type": "integer", "description": "Only include data points whose period ends in this year or later. Leave empty for full history." }, "latestOnly": { "title": "Latest value only", "type": "boolean", "description": "Return only the most recent data point for each metric instead of full history.", "default": false }, "maxRowsPerTicker": { "title": "Max rows per ticker", "minimum": 1, "type": "integer", "description": "Cap fundamentals rows returned per ticker.", "default": 5000 }, "maxRowsTotal": { "title": "Max rows total", "minimum": 1, "type": "integer", "description": "Stop after this many rows across all tickers.", "default": 50000 } } }, "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 } } } } } } } } } } ```