# TipRanks Analyst, Insider & Smart Score Scraper (`xtracto/tipranks-stock-signals`) Actor Get TipRanks data for any stock: the 1-10 Smart Score, analyst consensus with buy/hold/sell counts and price targets plus computed upside, individual analyst ratings and firms, recent insider trades with SEC filing links, and blogger + news sentiment. No account or API key needed. - **URL**: https://apify.com/xtracto/tipranks-stock-signals.md - **Developed by:** [Farhan Febrian Nauval](https://apify.com/xtracto) (community) - **Categories:** Lead generation, News, Integrations - **Stats:** 2 total users, 1 monthly users, 83.3% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $2.00 / 1,000 results This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. 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 ## TipRanks Analyst, Insider & Smart Score Scraper Get analyst ratings, price targets, insider trades, and the Smart Score for any stock from TipRanks — one clean row per ticker, ready for spreadsheets, databases, or your own models. No account, no login, no API key. ### Why use this actor - **No account or API key required** — just enter ticker symbols and run. - **The full TipRanks signal set in one row per stock:** the 1–10 Smart Score with its underlying factors, the Wall Street analyst consensus (buy/hold/sell counts), the average price target with computed upside, every individual analyst's latest rating and firm, recent insider trades, and blogger + news sentiment. - **Real insider trades with direct SEC filing links** — name, title, shares, dollar value, and the exact EDGAR Form 4 URL for each transaction. - **Named analysts, not just numbers** — each analyst's name, firm, star rating, track record, latest action (upgrade / downgrade / reiterate), and old vs. new price target. - **Stable JSON output** suitable for pipelines, dashboards, and quantitative screening. Export to JSON, CSV, or Excel. - **Automatic retries**, runs on Apify's schedule, and scales to a whole watchlist in one run. ### How it works 1. You provide a list of stock ticker symbols (for example `AAPL`, `TSLA`, `NVDA`). 2. For each ticker, the actor pulls the complete TipRanks signal set for that stock. 3. It organizes everything into one tidy record per ticker — Smart Score, analyst consensus, price target with upside, per-analyst ratings, insider transactions, and sentiment. 4. Optionally, it adds a news-sentiment block (media buzz and bullish/bearish split) for each stock. 5. Results are saved to your dataset, ready to export or feed into another tool. You don't manage any scrapers, browsers, or blocks — just enter tickers and read the results. ### Input ```json { "tickers": ["AAPL", "TSLA", "NVDA"], "includeNewsSentiment": true, "wallStreetOnly": false, "maxItems": 100, "maxConcurrency": 4 } ```` | Field | Type | Description | | --- | --- | --- | | `tickers` | array of strings | Stock ticker symbols to look up. One dataset row per ticker. Unknown tickers produce an error row so nothing fails silently. | | `includeNewsSentiment` | boolean | Add a news-sentiment block (media buzz, bullish/bearish split, weekly article counts) per ticker. Default `true`. | | `wallStreetOnly` | boolean | Limit the `analysts` list to professional Wall Street analysts and exclude financial bloggers. Default `false`. | | `maxItems` | integer | Maximum number of tickers to process (0 = all). Default `100`. | | `maxConcurrency` | integer | How many tickers to fetch in parallel. Default `4`. | | `proxyConfiguration` | object | Optional. Not required; a Residential proxy is offered as insurance for large batches. | ### Output One row per ticker. Real sample for `AAPL` (long arrays truncated): ```json { "_input": "AAPL", "_source": "S1-api", "_scrapedAt": "2026-07-11T09:20:04Z", "recordType": "STOCK", "ticker": "AAPL", "companyName": "Apple", "companyFullName": "Apple", "marketCap": 4602870851543, "smartScore": { "score": 9, "subFactors": { "returnOnEquity": 146.6892, "twelveMonthsMomentum": 0.5036, "simpleMovingAverage": 1.0, "assetGrowth": 12.0305, "volatilityLevelRating": 2 } }, "consensus": { "rating": 4, "ratingLabel": "Moderate Buy", "buyCount": 18, "holdCount": 11, "sellCount": 1, "totalAnalysts": 30, "consensusRate": 30, "date": "10/7/26" }, "priceTarget": { "priceTarget": 330.71, "high": 400.0, "low": 253.0, "currency": "USD", "latestPrice": 316.22, "upside": 0.0458 }, "analysts": [ { "name": "Samik Chatterjee", "firm": "J.P. Morgan", "expertTypeLabel": "Analyst", "isAiModel": false, "stars": 5.0, "stockSuccessRate": 0.936, "stockAverageReturn": 0.209, "currentRatingLabel": "Buy", "latestAction": 5, "latestActionLabel": "Reiterated", "priceTarget": 345.0, "oldPriceTarget": 325.0, "ratingDate": "2026-07-07T00:00:00" } // … 105 more ], "insiderTransactions": [ { "name": "Ben Borders", "officerTitle": "CAO", "isOfficer": true, "action": 3, "actionLabel": "Buy (non-open-market)", "transTypeLabel": "Grant/Award/Other Acquisition", "operation": "Grant/Award/Other Acquisition", "numberOfShares": 116, "estimatedSharesValue": 34384.72, "date": "3w", "rDate": "2026-06-17T00:00:00", "secLink": "http://sec.gov/Archives/edgar/data/2100523/000114036126025620/xslF345X03/form4.xml" } // … 39 more ], "insiderSignal": { "confidenceScore": 3, "confidenceLabel": "Very Positive", "last3MonthsSum": -86740722.31, "numOfInsiders": 108136, "monthlyBuckets": [ /* 12 monthly buy/sell buckets */ ] }, "bloggerSentiment": { "bullish": "74", "bearish": "14", "neutral": "12", "bullishCount": 47, "bearishCount": 8, "score": 1, "avg": 0.6542 }, "newsSentiment": { "buzz": { "articlesInLastWeek": 176, "weeklyAverage": 218.75, "buzz": 0.8089 }, "sentiment": { "bullishPercent": 0.7746, "bearishPercent": 0.2254 }, "sectorAverageBullishPercent": 0.8421, "score": 0.6674 } } ``` | Field | Type | Description | | --- | --- | --- | | `ticker` / `companyName` | string | The stock symbol and company name. | | `marketCap` | number | Market capitalization in the stock's currency. | | `smartScore.score` | integer | TipRanks Smart Score, 1 (bearish) to 10 (bullish). | | `smartScore.subFactors` | object | The underlying factors (return on equity, momentum, moving average, asset growth, volatility rating, etc.). | | `consensus.rating` / `ratingLabel` | int / string | Analyst consensus, 1–5, e.g. 4 = "Moderate Buy". | | `consensus.buyCount` / `holdCount` / `sellCount` | integer | Number of analysts on each side of the latest consensus. | | `consensus.consensusRate` | integer | Number of analysts behind the consensus. | | `priceTarget.priceTarget` / `high` / `low` | number | Average, highest, and lowest 12-month price targets. | | `priceTarget.latestPrice` | number | Most recent share price. | | `priceTarget.upside` | number | Computed upside to the average target (e.g. `0.0458` = +4.58%). | | `analysts[]` | array | Each covering analyst: name, firm, type, star rating, track record, current rating, latest action, and old vs. new price target. | | `insiderTransactions[]` | array | Recent insider trades: name, title, buy/sell action, shares, dollar value, dates, and a direct SEC filing link. | | `insiderSignal` | object | Insider confidence signal, net insider dollars over the last 3 months, and 12 monthly buy/sell buckets. | | `bloggerSentiment` | object | Financial-blogger bullish / bearish / neutral split. | | `newsSentiment` | object | Media buzz, bullish/bearish news split, and sector benchmark (when enabled). | ### Notes / limits - **One row per ticker** — everything for a stock arrives in a single record. Pass a whole watchlist to cover many stocks in one run. - **Insider transactions are a recent window** (roughly the last ~40 trades per stock), not the company's full lifetime history. - **Some analysts are AI models** — for those, the `name` is intentionally empty and the firm reads like "TipRanks – Anthropic"; the `isAiModel` flag marks them. - **Unknown or delisted tickers** produce a clear error row (`_error: "not_found"`) instead of being dropped. - **Not every stock has every signal** — micro-caps may have no analyst coverage or no insider confidence score; those fields come back empty rather than guessed. - A proxy is not required. For very large batches, enable a Residential proxy in the input for extra reliability. ### Other actors Part of a finance data collection — pair this with the DexScreener pairs actor and other market-data scrapers in the same family. # Actor input Schema ## `tickers` (type: `array`): Stock ticker symbols to look up on TipRanks, e.g. \["AAPL", "TSLA", "NVDA"]. One dataset row is produced per ticker, with Smart Score, analyst consensus, price target, per-analyst ratings, insider transactions and sentiment. Unknown tickers produce an error row. ## `includeNewsSentiment` (type: `boolean`): If checked, each ticker is enriched with a news-sentiment block (media buzz, bullish/bearish split, weekly article counts, sector benchmark). Adds one extra request per ticker. ## `wallStreetOnly` (type: `boolean`): If checked, the 'analysts' list is limited to professional Wall Street analysts and excludes financial bloggers. ## `maxItems` (type: `integer`): Maximum number of tickers to process from the list (0 = no cap). One row is produced per ticker. ## `maxConcurrency` (type: `integer`): Number of tickers fetched in parallel. Keep modest to stay polite to the source. ## `proxyConfiguration` (type: `object`): Optional. TipRanks is readable without a proxy; a Residential proxy is offered as insurance if you run large batches. Defaults to no proxy. ## Actor input object example ```json { "tickers": [ "AAPL", "TSLA", "NVDA" ], "includeNewsSentiment": true, "wallStreetOnly": false, "maxItems": 100, "maxConcurrency": 4, "proxyConfiguration": { "useApifyProxy": false } } ``` # 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", "TSLA", "NVDA" ], "maxItems": 100 }; // Run the Actor and wait for it to finish const run = await client.actor("xtracto/tipranks-stock-signals").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", "TSLA", "NVDA", ], "maxItems": 100, } # Run the Actor and wait for it to finish run = client.actor("xtracto/tipranks-stock-signals").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", "TSLA", "NVDA" ], "maxItems": 100 }' | apify call xtracto/tipranks-stock-signals --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=xtracto/tipranks-stock-signals", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "TipRanks Analyst, Insider & Smart Score Scraper", "description": "Get TipRanks data for any stock: the 1-10 Smart Score, analyst consensus with buy/hold/sell counts and price targets plus computed upside, individual analyst ratings and firms, recent insider trades with SEC filing links, and blogger + news sentiment. No account or API key needed.", "version": "0.1", "x-build-id": "UmgtHdWQamgcZlgEE" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/xtracto~tipranks-stock-signals/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-xtracto-tipranks-stock-signals", "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/xtracto~tipranks-stock-signals/runs": { "post": { "operationId": "runs-sync-xtracto-tipranks-stock-signals", "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/xtracto~tipranks-stock-signals/run-sync": { "post": { "operationId": "run-sync-xtracto-tipranks-stock-signals", "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": "Stock tickers", "type": "array", "description": "Stock ticker symbols to look up on TipRanks, e.g. [\"AAPL\", \"TSLA\", \"NVDA\"]. One dataset row is produced per ticker, with Smart Score, analyst consensus, price target, per-analyst ratings, insider transactions and sentiment. Unknown tickers produce an error row.", "items": { "type": "string" } }, "includeNewsSentiment": { "title": "Include news sentiment", "type": "boolean", "description": "If checked, each ticker is enriched with a news-sentiment block (media buzz, bullish/bearish split, weekly article counts, sector benchmark). Adds one extra request per ticker.", "default": true }, "wallStreetOnly": { "title": "Wall Street analysts only", "type": "boolean", "description": "If checked, the 'analysts' list is limited to professional Wall Street analysts and excludes financial bloggers.", "default": false }, "maxItems": { "title": "Max tickers (0 = all)", "minimum": 0, "type": "integer", "description": "Maximum number of tickers to process from the list (0 = no cap). One row is produced per ticker.", "default": 100 }, "maxConcurrency": { "title": "Max concurrent requests", "minimum": 1, "maximum": 10, "type": "integer", "description": "Number of tickers fetched in parallel. Keep modest to stay polite to the source.", "default": 4 }, "proxyConfiguration": { "title": "Proxy", "type": "object", "description": "Optional. TipRanks is readable without a proxy; a Residential proxy is offered as insurance if you run large batches. Defaults to no proxy.", "default": { "useApifyProxy": false } } } }, "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 } } } } } } } } } } ```