# StockTwits Scraper (`sheshinmcfly/stocktwits-scraper`) Actor Search StockTwits messages and trending symbols with real-time trader sentiment, price context at post time, author profiles, and AI-generated trend summaries. No login or API key needed -- get structured data ready for sentiment tracking, trend discovery, or social trading research. - **URL**: https://apify.com/sheshinmcfly/stocktwits-scraper.md - **Developed by:** [Sheshinmcfly](https://apify.com/sheshinmcfly) (community) - **Categories:** News, Lead generation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $1.00 / 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.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 Search StockTwits messages and trending symbols — real-time trader sentiment, price context at post time, author profiles, and AI-generated trend summaries. No login, no account, no API key. Track what retail traders are saying about any stock or crypto symbol, or discover what's trending right now with sentiment and volume shifts. ### How to use 1. Choose a **Data type**: messages (recent posts for specific symbols) or trending (the current top trending symbols). 2. For messages, add one or more **symbols** (e.g. `AAPL`, `TSLA`, `BTC.X`) and a **max results per symbol**. 3. Optionally filter messages by **sentiment** (Bullish or Bearish only). 4. Run. ### Use cases - **Sentiment tracking:** monitor bullish/bearish shifts on any stock or crypto symbol from real trader posts. - **Trend discovery:** find what's trending right now with sentiment and volume-change context. - **Social listening:** feed trader chatter into your own analytics or trading signals. - **Community research:** track influential traders (followers, post history) around specific tickers. ### Output example ```json { "recordType": "message", "id": 658968324, "querySymbol": "AAPL", "body": "$AAPL breaking out on volume", "createdAt": "2026-07-14T05:35:39Z", "sentiment": "Bullish", "priceAtPost": 317.88, "symbolsMentioned": ["AAPL"], "authorUsername": "trader123", "authorFollowers": 2620, "authorIdeasCount": 15248 } ```` ### Performance & cost Fast, structured results — no long waits for large jobs. ### Pricing This actor uses **pay-per-result** pricing — you are charged per record returned. See the pricing shown on the actor page. ### Keywords stocktwits scraper, stock sentiment data, trader sentiment api, stocktwits api, trending stocks scraper, social trading data, stock market sentiment, retail trader chatter ### Related actors - [FinViz Stock Screener](https://apify.com/sheshinmcfly/finviz-stock-screener) - [TradingView Screener](https://apify.com/sheshinmcfly/tradingview-screener) - [Polymarket Scraper](https://apify.com/sheshinmcfly/polymarket-scraper) ### Disclaimer This actor collects only publicly available data from StockTwits. Use the data in compliance with the applicable terms and with data-protection laws in your jurisdiction. This actor does not provide financial or investment advice. ### Changelog | Version | Date | Changes | |---|---|---| | 1.0 | 2026-07-14 | Initial release — messages with sentiment and trending symbols | # Actor input Schema ## `dataType` (type: `string`): What to scrape: messages (recent posts + sentiment for specific symbols) or trending (the current top trending symbols with sentiment/volume shifts). ## `symbols` (type: `array`): Stock or crypto ticker symbols to fetch messages for (e.g. "AAPL", "TSLA", "BTC.X"). Required when Data type is Messages. ## `maxResultsPerSymbol` (type: `integer`): Maximum number of messages to return per symbol. Only applies when Data type is Messages. ## `sentimentFilter` (type: `string`): Only return messages with this sentiment tag. Leave empty for all messages (most posts have no sentiment tag). Only applies when Data type is Messages. ## Actor input object example ```json { "dataType": "messages", "symbols": [ "AAPL", "TSLA" ], "maxResultsPerSymbol": 30 } ``` # Actor output Schema ## `dataset` (type: `string`): All extracted records. # 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 = { "symbols": [ "AAPL", "TSLA" ] }; // Run the Actor and wait for it to finish const run = await client.actor("sheshinmcfly/stocktwits-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 = { "symbols": [ "AAPL", "TSLA", ] } # Run the Actor and wait for it to finish run = client.actor("sheshinmcfly/stocktwits-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 '{ "symbols": [ "AAPL", "TSLA" ] }' | apify call sheshinmcfly/stocktwits-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=sheshinmcfly/stocktwits-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "StockTwits Scraper", "description": "Search StockTwits messages and trending symbols with real-time trader sentiment, price context at post time, author profiles, and AI-generated trend summaries. No login or API key needed -- get structured data ready for sentiment tracking, trend discovery, or social trading research.", "version": "1.0", "x-build-id": "yziw8dfpdklB2Lzx7" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/sheshinmcfly~stocktwits-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-sheshinmcfly-stocktwits-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/sheshinmcfly~stocktwits-scraper/runs": { "post": { "operationId": "runs-sync-sheshinmcfly-stocktwits-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/sheshinmcfly~stocktwits-scraper/run-sync": { "post": { "operationId": "run-sync-sheshinmcfly-stocktwits-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": [ "dataType" ], "properties": { "dataType": { "title": "Data type", "enum": [ "messages", "trending" ], "type": "string", "description": "What to scrape: messages (recent posts + sentiment for specific symbols) or trending (the current top trending symbols with sentiment/volume shifts).", "default": "messages" }, "symbols": { "title": "Symbols", "type": "array", "description": "Stock or crypto ticker symbols to fetch messages for (e.g. \"AAPL\", \"TSLA\", \"BTC.X\"). Required when Data type is Messages.", "items": { "type": "string" } }, "maxResultsPerSymbol": { "title": "Max results per symbol", "minimum": 1, "type": "integer", "description": "Maximum number of messages to return per symbol. Only applies when Data type is Messages.", "default": 30 }, "sentimentFilter": { "title": "Sentiment filter", "enum": [ "Bullish", "Bearish" ], "type": "string", "description": "Only return messages with this sentiment tag. Leave empty for all messages (most posts have no sentiment tag). Only applies when Data type is Messages." } } }, "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 } } } } } } } } } } ```