# Tipranks Scraper (`mscraper/tipranks-scraper`) Actor TipRanks News Scraper is a specialized web scraping tool designed to provide valuable real-time data on stock prices, market trends, and financial metrics from TipRanks. The scraper exports the accumulated data to various formats like JSON, XML, CSV, or Excel. - **URL**: https://apify.com/mscraper/tipranks-scraper.md - **Developed by:** [mscraper](https://apify.com/mscraper) (community) - **Categories:** Other - **Stats:** 38 total users, 0 monthly users, 100.0% runs succeeded, 3 bookmarks - **User rating**: No ratings yet ## Pricing $9.00/month + usage To use this Actor, you pay a monthly rental fee to the developer. The rent is subtracted from your prepaid usage every month after the free trial period.You also pay for the Apify platform usage, which gets cheaper the higher Apify subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#rental-actors ## 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 ## TipRanks Quotes Scraper ### What does TipRanks Quotes Scraper do? TipRanks Quotes Scraper is a specialized web scraping tool designed to extract real-time stock quotes from [TipRanks](https://www.tipranks.com/). The scraper exports the accumulated data to various formats like JSON, XML, CSV, or Excel. ### Why scrape TipRanks Quotes? TipRanks Quotes provide valuable real-time data on stock prices, market trends, and financial metrics. This data can be used for a variety of purposes, including: - Real-time market analysis - Monitoring stock performance - Building financial models - Conducting research on stock trends If you're looking to gain insights from real-time stock quotes, TipRanks Quotes Scraper is the tool for you. ### How to scrape TipRanks Quotes? Using TipRanks Quotes Scraper is straightforward. Just add your proxy configuration options in the input field, and click start. The scraper will do the rest, pulling all the relevant data from the platform. ### Input TipRanks Quotes Scraper has the following input options. Click on the [input tab](https://apify.com/mscraper/tipranks-quotes-scraper/input-schema) for more information. ### Results ```json { "ticker": "META", "currency": "USD", "exchangeRate": 1.0, "marketName": "NASDAQ", "price": 488.14, "open": 489.0, "low": 476.15, "high": 501.145, "changeAmount": -9.6, "changePercent": -1.93, "volume": 24044658, "marketCap": 1238140928698, "isRealTime": true, "isMarketOpen": false, "prePostMarket": { "price": 486.0, "volume": 1806635, "changeAmount": -2.14, "changePercent": -0.44, "lastTradeDate": "2024-08-02T23:59:58Z" } } ```` ### Is it legal to scrape TipRanks? Note that personal data is protected by GDPR in the European Union and by other regulations around the world. You should not scrape personal data unless you have a legitimate reason to do so. If you're unsure whether your reason is legitimate, consult your lawyers. We also recommend that you read our blog post: is web scraping legal? ### Contact Please feel free to browse through the diverse array of web scrapers available on my Apify profile. If a custom solution or extra options are what you're seeking, don't hesitate to get in touch with me directly at hello@mscraper.com. # Actor input Schema ## `tickers` (type: `array`): List of stock tickers to scrape quotes for. ## `devLogs` (type: `boolean`): Enable detailed logging for debugging purposes. ## `proxy` (type: `object`): Proxy settings for the crawler. ## Actor input object example ```json { "tickers": [ "META", "AAPL" ], "devLogs": false, "proxy": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ], "apifyProxyCountry": "US" } } ``` # 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": [ "META", "AAPL" ], "proxy": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ], "apifyProxyCountry": "US" } }; // Run the Actor and wait for it to finish const run = await client.actor("mscraper/tipranks-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": [ "META", "AAPL", ], "proxy": { "useApifyProxy": True, "apifyProxyGroups": ["RESIDENTIAL"], "apifyProxyCountry": "US", }, } # Run the Actor and wait for it to finish run = client.actor("mscraper/tipranks-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": [ "META", "AAPL" ], "proxy": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ], "apifyProxyCountry": "US" } }' | apify call mscraper/tipranks-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=mscraper/tipranks-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Tipranks Scraper", "description": "TipRanks News Scraper is a specialized web scraping tool designed to provide valuable real-time data on stock prices, market trends, and financial metrics from TipRanks. The scraper exports the accumulated data to various formats like JSON, XML, CSV, or Excel.", "version": "0.0", "x-build-id": "k9xXwnbW2MBxXMJls" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/mscraper~tipranks-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-mscraper-tipranks-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/mscraper~tipranks-scraper/runs": { "post": { "operationId": "runs-sync-mscraper-tipranks-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/mscraper~tipranks-scraper/run-sync": { "post": { "operationId": "run-sync-mscraper-tipranks-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": "List of stock tickers to scrape quotes for.", "items": { "type": "string" } }, "devLogs": { "title": "Developer Logs", "type": "boolean", "description": "Enable detailed logging for debugging purposes.", "default": false }, "proxy": { "title": "Proxy Configuration", "type": "object", "description": "Proxy settings for the crawler." } } }, "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 } } } } } } } } } } ```