# Perplexity Search Answers Scraper (`searchapi/perplexity-search-answers-scraper`) Actor Scrapes AI-generated answer content from Perplexity (perplexity.ai/search). Extracts the full canonical answer-vertical schema: query, full answer text, answer HTML, model used, citation count, related questions, answer sections, and timestamp. - **URL**: https://apify.com/searchapi/perplexity-search-answers-scraper.md - **Developed by:** [Search API](https://apify.com/searchapi) (community) - **Categories:** Developer tools, Automation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $1.99 / 1,000 perplexity search answers scraper results This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. 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 ## Perplexity Search Answers Scraper ### What is this tool? Perplexity Search Answers Scraper helps you collect ai data from Perplexity (the AI-powered answer engine). Just type in a question, and the tool will ask the AI and gather a comprehensive answer with the sources it used. ### What can you use it for? - Research on any topic with AI-generated summaries - Gather cited sources for fact-checking - Content creation and writing research - Quick answers to complex questions ### What data do you get? Each result includes up to **29 fields**, organized into the following categories: **Identity** (5 fields): #, type, resultType, page, modelId **URLs** (2 fields): URL, citationUrls **Ratings** (1 fields): Answer (preview) **Location** (1 fields): relatedQuestions **Source** (2 fields): Sources, sourceList **Search Context** (6 fields): Query, searchQuery, answerLanguage, searchEngine, parentQuery, searchMetadata **Other** (12 fields): Model, Mode, Citations, Sections, Words, Scraped At, answerHtml, answerLength, sections, citationIndexes, followUpQuestions, isFollowUp ### How to use it #### Step 1: Enter your search Type in any question you want answered, like "What is artificial intelligence?" or "How does solar power work?" #### Step 2: Set your preferences Adjust the options below to customize your search. #### Step 3: Run the tool Click the run button and wait for your results. The tool will gather all the data and save it in a clean, organized format. ### Input options | Option | What it means | Required | Default | |--------|---------------|----------|---------| | **Search Query** | The question to ask Perplexity. Perplexity returns one AI-generated answer per query. | Yes | What is the capital of France? | | **Max Items** | Max answer records to push (typically 1 per query; allow higher for batch multi-query mode). | No | 1 | | **Multiple Queries (batch)** | Optional array of additional queries to ask in batch mode. Each query produces a separate answer record. | No | — | | **Focus Mode** | Perplexity's focus mode (search scope). 'web' searches the whole web, 'academic' uses scholarly sources, 'social' uses social media, 'youtube' uses YouTube, etc. Options: web (Web), academic (Academic), social (Social), youtube (YouTube), reddit (Reddit), writing (Writing). | No | web | | **Model** | Optional model override. Leave empty to use Perplexity's default. 'pplx-pro' selects the Pro search model. | No | — | | **Language** | Language code for the answer locale (e.g. 'en-US', 'en-GB', 'de-DE', 'fr-FR'). | No | en-US | ### Output Your results come in a clean, organized table with **two views**: #### Overview view Shows the most important fields at a glance: - **#** - **Query** - **Answer (preview)** - **Model** - **Mode** - **Citations** - **Sources** - **Sections** - **Words** - **URL** - **Scraped At** #### Full details view Shows all 29 fields in detail. See "What data do you get?" above for the complete list. ### Tips for best results ✅ **Be specific** with your search terms for more relevant results ✅ **Try different variations** of your search term to discover more results ✅ **Browse multiple pages** of results to get a wider variety ### Frequently asked questions **Why use Perplexity?** Perplexity is an AI-powered answer engine that combines the best of search engines and large language models. It searches the web in real-time and uses AI to generate comprehensive answers with cited sources. **How do I get the results?** Your results are saved in your Apify dashboard. You can download them in various formats (JSON, CSV, Excel) or access them via the API. **Can I run it on a schedule?** Yes! Apify supports scheduled runs. You can set up the tool to run automatically at any interval (hourly, daily, weekly, etc.) from your dashboard. **What if I get fewer results than I asked for?** This can happen if the search engine doesn't have enough matching results for your search, or if some results are blocked. Try different keywords or relax your filters. **Need more help?** If you have questions or run into issues, our support team is ready to help. Just reach out through the Apify platform and we'll get back to you quickly. # Actor input Schema ## `query` (type: `string`): The question to ask Perplexity. Perplexity returns one AI-generated answer per query. ## `maxItems` (type: `integer`): Maximum number of answer records to push (typically 1 per query; allow higher for batch multi-query mode). ## `queries` (type: `array`): Optional array of additional queries to ask in batch mode. Each query produces a separate answer record. ## `focusMode` (type: `string`): Perplexity's focus mode (search scope). 'web' searches the whole web, 'academic' uses scholarly sources, 'social' uses social media, 'youtube' uses YouTube, etc. ## `model` (type: `string`): Optional model override. Leave empty to use Perplexity's default. 'pplx-pro' selects the Pro search model. ## `language` (type: `string`): Language code for the answer locale (e.g. 'en-US', 'en-GB', 'de-DE', 'fr-FR'). ## `proxyConfiguration` (type: `object`): Proxy settings. Residential proxies are strongly recommended — Perplexity aggressively blocks datacenter IPs. ## Actor input object example ```json { "query": "What is the capital of France?", "maxItems": 1, "queries": [ "history of the Roman Empire", "renewable energy statistics 2026" ], "focusMode": "web", "model": "", "language": "en-US", "proxyConfiguration": { "useApifyProxy": true } } ```` # 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 = { "query": "What is the capital of France?", "maxItems": 1, "queries": [], "focusMode": "web", "model": "", "language": "en-US", "proxyConfiguration": { "useApifyProxy": true } }; // Run the Actor and wait for it to finish const run = await client.actor("searchapi/perplexity-search-answers-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 = { "query": "What is the capital of France?", "maxItems": 1, "queries": [], "focusMode": "web", "model": "", "language": "en-US", "proxyConfiguration": { "useApifyProxy": True }, } # Run the Actor and wait for it to finish run = client.actor("searchapi/perplexity-search-answers-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 '{ "query": "What is the capital of France?", "maxItems": 1, "queries": [], "focusMode": "web", "model": "", "language": "en-US", "proxyConfiguration": { "useApifyProxy": true } }' | apify call searchapi/perplexity-search-answers-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=searchapi/perplexity-search-answers-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Perplexity Search Answers Scraper", "description": "Scrapes AI-generated answer content from Perplexity (perplexity.ai/search). Extracts the full canonical answer-vertical schema: query, full answer text, answer HTML, model used, citation count, related questions, answer sections, and timestamp.", "version": "2.0", "x-build-id": "IlyBYt6aTiNdIdlzd" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/searchapi~perplexity-search-answers-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-searchapi-perplexity-search-answers-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/searchapi~perplexity-search-answers-scraper/runs": { "post": { "operationId": "runs-sync-searchapi-perplexity-search-answers-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/searchapi~perplexity-search-answers-scraper/run-sync": { "post": { "operationId": "run-sync-searchapi-perplexity-search-answers-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "query" ], "properties": { "query": { "title": "Search Query", "type": "string", "description": "The question to ask Perplexity. Perplexity returns one AI-generated answer per query." }, "maxItems": { "title": "Max Items", "minimum": 1, "maximum": 50, "type": "integer", "description": "Maximum number of answer records to push (typically 1 per query; allow higher for batch multi-query mode).", "default": 1 }, "queries": { "title": "Multiple Queries (batch)", "type": "array", "description": "Optional array of additional queries to ask in batch mode. Each query produces a separate answer record.", "items": { "type": "string" } }, "focusMode": { "title": "Focus Mode", "enum": [ "web", "academic", "social", "youtube", "reddit", "writing" ], "type": "string", "description": "Perplexity's focus mode (search scope). 'web' searches the whole web, 'academic' uses scholarly sources, 'social' uses social media, 'youtube' uses YouTube, etc.", "default": "web" }, "model": { "title": "Model", "type": "string", "description": "Optional model override. Leave empty to use Perplexity's default. 'pplx-pro' selects the Pro search model.", "default": "" }, "language": { "title": "Language", "type": "string", "description": "Language code for the answer locale (e.g. 'en-US', 'en-GB', 'de-DE', 'fr-FR').", "default": "en-US" }, "proxyConfiguration": { "title": "Proxy Configuration", "type": "object", "description": "Proxy settings. Residential proxies are strongly recommended — Perplexity aggressively blocks datacenter IPs." } } }, "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 } } } } } } } } } } ```