# Quora Scraper (`jungle_synthesizer/quora-scraper`) Actor Scrape Quora questions and answers by keyword search or direct question URLs. Extracts question title, answer text, author info, upvote counts, and engagement metrics. Supports bulk extraction with configurable result limits. - **URL**: https://apify.com/jungle\_synthesizer/quora-scraper.md - **Developed by:** [BowTiedRaccoon](https://apify.com/jungle_synthesizer) (community) - **Categories:** Social media, Developer tools - **Stats:** 2 total users, 1 monthly users, 33.3% 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. 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.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 ## Quora Scraper Scrape Quora questions and answers by providing direct question URLs or keyword search terms. Extracts answer text, author info, upvote counts, and engagement metrics from public Quora pages. ### Features - Scrape questions and answers by **keyword search** or **direct URL** - Extracts question title, answer text, author credentials, and upvotes - Handles Quora's Cloudflare fingerprint protection automatically - Configurable maximum items and answers per question - Supports topic pages and search result pages ### Usage #### Keyword Search Provide one or more keywords — the actor searches Quora for matching questions and scrapes the results: ```json { "keywords": ["machine learning", "artificial intelligence"], "maxItems": 20, "maxAnswersPerQuestion": 5 } ```` #### Direct URL Scraping Provide specific Quora question URLs to scrape directly: ```json { "startUrls": [ { "url": "https://www.quora.com/What-is-machine-learning" }, { "url": "https://www.quora.com/What-is-Python-programming" } ], "maxItems": 10, "maxAnswersPerQuestion": 3 } ``` ### Input Parameters | Parameter | Type | Default | Description | |---|---|---|---| | `startUrls` | Array | — | Direct Quora question or search URLs. Takes priority over `keywords`. | | `keywords` | Array | — | Search terms. Used when `startUrls` is empty. | | `maxItems` | Integer | 10 | Maximum total records (question+answer pairs) to scrape. | | `maxAnswersPerQuestion` | Integer | 5 | Maximum answers to extract per question page. | One of `startUrls` or `keywords` is required. ### Output Each output record represents one answer to a Quora question: ```json { "question_url": "https://www.quora.com/What-is-machine-learning", "question_title": "What is machine learning?", "answer_author": "Jane Smith", "answer_author_bio": "PhD in Computer Science, Stanford", "answer_text": "Machine learning is a branch of computer science...", "answer_upvotes": "2.1K", "answer_index": 1, "scraped_at": "2026-06-07T20:00:00.000Z" } ``` If a question has no accessible answers (login gating), a record is still saved with the question title and null answer fields. ### Notes - Quora content is public for most questions but may require a login for some. The actor scrapes available content without authentication. - The actor uses real browser rendering to handle Quora's Cloudflare protection. No proxy or CAPTCHA solver is required. - Answer counts per question depend on how many answers Quora renders before the login wall appears. # 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`): One or more direct Quora question URLs to scrape (e.g. https://www.quora.com/What-is-machine-learning). This is the supported input mode. ## `keywords` (type: `array`): Keyword search is temporarily unavailable: Quora does not server-render search results, so they cannot be read without a logged-in session. Use startUrls with direct question URLs instead. ## `maxItems` (type: `integer`): Maximum number of records (question+answer pairs) to scrape ## `maxAnswersPerQuestion` (type: `integer`): Maximum number of answers to extract per question page ## 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": [ { "url": "https://www.quora.com/What-is-machine-learning" } ], "maxItems": 5, "maxAnswersPerQuestion": 3 } ``` # 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": [ { "url": "https://www.quora.com/What-is-machine-learning" } ], "maxItems": 5, "maxAnswersPerQuestion": 3 }; // Run the Actor and wait for it to finish const run = await client.actor("jungle_synthesizer/quora-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": [{ "url": "https://www.quora.com/What-is-machine-learning" }], "maxItems": 5, "maxAnswersPerQuestion": 3, } # Run the Actor and wait for it to finish run = client.actor("jungle_synthesizer/quora-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": [ { "url": "https://www.quora.com/What-is-machine-learning" } ], "maxItems": 5, "maxAnswersPerQuestion": 3 }' | apify call jungle_synthesizer/quora-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=jungle_synthesizer/quora-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Quora Scraper", "description": "Scrape Quora questions and answers by keyword search or direct question URLs.\nExtracts question title, answer text, author info, upvote counts, and engagement metrics.\nSupports bulk extraction with configurable result limits.\n", "version": "0.1", "x-build-id": "Kjwuea32uM7r6fVEN" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/jungle_synthesizer~quora-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-jungle_synthesizer-quora-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~quora-scraper/runs": { "post": { "operationId": "runs-sync-jungle_synthesizer-quora-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~quora-scraper/run-sync": { "post": { "operationId": "run-sync-jungle_synthesizer-quora-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": [ "maxItems" ], "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": "One or more direct Quora question URLs to scrape (e.g. https://www.quora.com/What-is-machine-learning). This is the supported input mode.\n", "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } }, "keywords": { "title": "Keywords (currently unavailable)", "type": "array", "description": "Keyword search is temporarily unavailable: Quora does not server-render search results, so they cannot be read without a logged-in session. Use startUrls with direct question URLs instead.\n", "items": { "type": "string" } }, "maxItems": { "title": "Max Items", "type": "integer", "description": "Maximum number of records (question+answer pairs) to scrape", "default": 10 }, "maxAnswersPerQuestion": { "title": "Max Answers Per Question", "type": "integer", "description": "Maximum number of answers to extract per question page", "default": 5 } } }, "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 } } } } } } } } } } ```