# Motley Fool Earnings Call Transcripts Scraper (`jungle_synthesizer/motley-fool-earnings-transcripts-scraper`) Actor Scrape earnings call transcripts from Motley Fool's free archive. Extracts full transcript text (prepared remarks + Q\&A), call participants, company ticker, fiscal quarter, published date, and article metadata. Archive spans 2007 to present with ~1,000-1,500 new transcripts per earnings quarter. - **URL**: https://apify.com/jungle\_synthesizer/motley-fool-earnings-transcripts-scraper.md - **Developed by:** [BowTiedRaccoon](https://apify.com/jungle_synthesizer) (community) - **Categories:** Business, Automation, Other - **Stats:** 4 total users, 3 monthly users, 100.0% runs succeeded, NaN 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. 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 ## Motley Fool Earnings Call Transcripts Scraper Scrape earnings call transcripts from [Motley Fool's free archive](https://www.fool.com/earnings-call-transcripts/). Extracts full transcript text (prepared remarks + Q&A), call participants, company ticker, fiscal quarter, published date, and article metadata. Archive spans 2007 to present with ~1,000–1,500 new transcripts per earnings quarter. ### What it does The actor operates in two modes: **Direct URL mode** — provide specific transcript URLs and get results immediately. No sitemap walking, no date filtering. **Discovery mode** — walk Motley Fool's monthly XML sitemaps for a configured year range (`startYear`–`endYear`), filter to transcript URLs, and extract each one. Supports optional ticker filtering. For each transcript the actor extracts: - Company name, ticker symbol, and exchange (e.g., `NASDAQ`) - Fiscal quarter label (e.g., `Q1 2026`) - Date of the earnings call - Article publication date (ISO 8601) - Author / transcript editor name - Headline from structured data - List of call participants with their roles - Full transcript text - Prepared remarks (pre-Q&A portion) - Q&A section (from first analyst question onward) - AI-generated summary (when present) ### Use cases - Build earnings sentiment analysis pipelines - Train LLMs on executive communication and financial language - Track company-specific commentary across quarters - Monitor guidance language and forward-looking statements - Research competitor disclosures by ticker ### Input | Field | Type | Description | |-------|------|-------------| | `startUrls` | String list | Specific transcript URLs to scrape. When provided, bypasses sitemap discovery entirely. | | `startYear` | Integer | Earliest publication year for discovery mode. Default: current year. | | `endYear` | Integer | Latest publication year for discovery mode (inclusive). Default: current year. | | `tickerFilter` | String | Only return transcripts matching this ticker symbol (e.g., `AAPL`). Case-insensitive. Leave blank for all tickers. | | `maxItems` | Integer | Maximum number of transcripts to return. `0` = no limit. | #### Direct URL example ```json { "startUrls": [ "https://www.fool.com/earnings/call-transcripts/2026/05/09/maravai-mrvi-q1-2026-earnings-transcript/", "https://www.fool.com/earnings/call-transcripts/2026/04/30/twilio-twlo-q1-2026-earnings-transcript/" ], "maxItems": 5 } ```` #### Discovery mode example (all transcripts from Q1 2026) ```json { "startYear": 2026, "endYear": 2026, "maxItems": 100 } ``` #### Ticker filter example ```json { "startYear": 2020, "endYear": 2026, "tickerFilter": "AAPL", "maxItems": 0 } ``` ### Output Each dataset record has these fields: | Field | Description | |-------|-------------| | `article_url` | Full URL of the Motley Fool transcript article | | `article_slug` | URL slug, e.g. `maravai-mrvi-q1-2026-earnings-transcript` | | `company_name` | Company name extracted from slug, e.g. `Maravai` | | `ticker` | Stock ticker symbol, e.g. `MRVI` | | `exchange` | Stock exchange, e.g. `NASDAQ` | | `fiscal_quarter` | Fiscal quarter label, e.g. `Q1 2026` | | `call_date` | Date of the earnings conference call, e.g. `May 7, 2026` | | `published_date` | Article publication date (ISO 8601), e.g. `2026-05-09T20:15:31.000Z` | | `author` | Transcript editor or contributor name | | `headline` | Article headline from structured data | | `canonical_url` | Canonical URL from the article | | `summary` | AI-generated summary paragraph (when present) | | `call_participants` | List of participants in `Role — Name` format | | `transcript_full` | Full conference call transcript text | | `prepared_remarks` | Text of the prepared remarks portion (before Q\&A) | | `qa_section` | Text of the Q\&A portion (from first analyst question onward) | #### Sample record ```json { "article_url": "https://www.fool.com/earnings/call-transcripts/2026/05/09/maravai-mrvi-q1-2026-earnings-transcript/", "article_slug": "maravai-mrvi-q1-2026-earnings-transcript", "company_name": "Maravai", "ticker": "MRVI", "exchange": "NASDAQ", "fiscal_quarter": "Q1 2026", "call_date": "May 7, 2026", "published_date": "2026-05-09T20:15:31.000Z", "author": "Motley Fool Transcribing", "call_participants": [ "Chief Executive Officer — Trey Martin", "Chief Financial Officer — Kevin Herde", "Analyst — Derik De Bruin" ], "prepared_remarks": "...", "qa_section": "...", "transcript_full": "..." } ``` ### Performance - No proxy required — Motley Fool's transcript pages are publicly accessible - Default concurrency: 3 parallel requests (conservative for Cloudflare CDN) - Archive size: ~80k–120k transcripts historically; ~1,000–1,500 new per earnings season - Sitemap for a single month contains 1,000–1,500 entries (processed in-memory) ### Pricing Pay-per-result pricing: **$0.10 per start + $0.001 per transcript**. - 100 transcripts: ~$0.20 - 1,000 transcripts: ~$1.10 - Full quarterly archive (~1,500 transcripts): ~$1.60 ### Notes - Only transcript articles are scraped — `/earnings/call-transcripts/` URL path - The `tickerFilter` applies only in discovery mode; in direct URL mode, all provided URLs are fetched - Transcripts with no Q\&A section (rare) have `qa_section` as an empty string and `prepared_remarks` as the full text - The actor does not follow pagination links on listing pages; it uses sitemaps for scalable discovery # Actor input Schema ## `sp_intended_usage` (type: `string`): Please describe how you plan to use the data extracted by this crawler. ## `sp_improvement_suggestions` (type: `string`): Provide any feedback or suggestions for improvements. ## `sp_contact` (type: `string`): Provide your email address so we can get in touch with you. ## `startUrls` (type: `array`): Optional: provide specific transcript URLs to scrape directly (bypasses sitemap discovery). Each URL must be a fool.com/earnings/call-transcripts/... article URL. ## `startYear` (type: `integer`): Earliest publication year to scrape (e.g. 2024). Defaults to current year. Ignored when startUrls is provided. ## `endYear` (type: `integer`): Latest publication year to scrape (inclusive). Defaults to current year. Ignored when startUrls is provided. ## `tickerFilter` (type: `string`): Optional: only return transcripts matching this ticker symbol (case-insensitive, e.g. AAPL). Leave blank to return all tickers. ## `maxItems` (type: `integer`): Maximum number of transcripts to return. 0 = no limit. ## Actor input object example ```json { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "startUrls": [], "startYear": 2026, "endYear": 2026, "tickerFilter": "", "maxItems": 10 } ``` # Actor output Schema ## `results` (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 = { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "startUrls": [], "startYear": 2026, "endYear": 2026, "tickerFilter": "", "maxItems": 10 }; // Run the Actor and wait for it to finish const run = await client.actor("jungle_synthesizer/motley-fool-earnings-transcripts-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 = { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "startUrls": [], "startYear": 2026, "endYear": 2026, "tickerFilter": "", "maxItems": 10, } # Run the Actor and wait for it to finish run = client.actor("jungle_synthesizer/motley-fool-earnings-transcripts-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 '{ "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "startUrls": [], "startYear": 2026, "endYear": 2026, "tickerFilter": "", "maxItems": 10 }' | apify call jungle_synthesizer/motley-fool-earnings-transcripts-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=jungle_synthesizer/motley-fool-earnings-transcripts-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Motley Fool Earnings Call Transcripts Scraper", "description": "Scrape earnings call transcripts from Motley Fool's free archive. Extracts full transcript text (prepared remarks + Q&A), call participants, company ticker, fiscal quarter, published date, and article metadata. Archive spans 2007 to present with ~1,000-1,500 new transcripts per earnings quarter.", "version": "0.1", "x-build-id": "NkeMlpB0wGw9kzBG7" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/jungle_synthesizer~motley-fool-earnings-transcripts-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-jungle_synthesizer-motley-fool-earnings-transcripts-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/jungle_synthesizer~motley-fool-earnings-transcripts-scraper/runs": { "post": { "operationId": "runs-sync-jungle_synthesizer-motley-fool-earnings-transcripts-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/jungle_synthesizer~motley-fool-earnings-transcripts-scraper/run-sync": { "post": { "operationId": "run-sync-jungle_synthesizer-motley-fool-earnings-transcripts-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "sp_intended_usage": { "title": "What is the intended usage of this data?", "minLength": 1, "type": "string", "description": "Please describe how you plan to use the data extracted by this crawler." }, "sp_improvement_suggestions": { "title": "How can we improve this crawler for you?", "minLength": 1, "type": "string", "description": "Provide any feedback or suggestions for improvements." }, "sp_contact": { "title": "Contact Email", "minLength": 1, "type": "string", "description": "Provide your email address so we can get in touch with you." }, "startUrls": { "title": "Start URLs", "type": "array", "description": "Optional: provide specific transcript URLs to scrape directly (bypasses sitemap discovery). Each URL must be a fool.com/earnings/call-transcripts/... article URL.", "default": [], "items": { "type": "string" } }, "startYear": { "title": "Start Year", "type": "integer", "description": "Earliest publication year to scrape (e.g. 2024). Defaults to current year. Ignored when startUrls is provided.", "default": 2026 }, "endYear": { "title": "End Year", "type": "integer", "description": "Latest publication year to scrape (inclusive). Defaults to current year. Ignored when startUrls is provided.", "default": 2026 }, "tickerFilter": { "title": "Ticker Filter", "type": "string", "description": "Optional: only return transcripts matching this ticker symbol (case-insensitive, e.g. AAPL). Leave blank to return all tickers.", "default": "" }, "maxItems": { "title": "Max Items", "type": "integer", "description": "Maximum number of transcripts to return. 0 = no limit.", "default": 0 } } }, "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 } } } } } } } } } } ```