# PDF Text Extractor - Bulk PDF to Text & Metadata (`santamaria-automations/pdf-extractor`) Actor Extract text and metadata from any PDF URL in bulk. Get page content, author, title, creation date, and more. Detects scanned PDFs that need OCR. Perfect for document analysis, research, and compliance. - **URL**: https://apify.com/santamaria-automations/pdf-extractor.md - **Developed by:** [Alessandro Santamaria](https://apify.com/santamaria-automations) (community) - **Categories:** AI, Developer tools, Automation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $5.00 / 1,000 pdf extracteds 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 ## PDF Text Extractor - Bulk PDF to Text & Metadata Extract text and structured metadata from any PDF URL at scale. Perfect for document analysis, research papers, compliance docs, and building searchable archives. ### What you get - **Full text extraction** — clean text from every page - **PDF metadata** — title, author, creation date, producer, keywords - **Page-level info** — count, dimensions, character distribution - **Scanned detection** — flags PDFs that need OCR (heuristic: low text density) - **Encryption detection** — flags password-protected PDFs - **Bulk processing** — verify hundreds in one run, parallel safe - **Pay-per-result** — $0.005 per PDF, no monthly fees ### Example output ```json { "url": "https://example.com/whitepaper.pdf", "file_size_bytes": 524288, "success": true, "page_count": 14, "text_length": 28450, "text": "Introduction\n\nThis whitepaper explores...", "metadata": { "title": "Quarterly Report 2026", "author": "Jane Smith", "creation_date": "2026-03-15T10:23:00Z", "creator": "Microsoft Word", "producer": "Acrobat Distiller" }, "is_encrypted": false, "is_scanned": false, "needs_ocr": false } ```` ### Use cases - **Research & academia** — extract content from papers, white papers, dissertations - **Document archiving** — build searchable indexes from PDF libraries - **Compliance** — bulk-extract contract text for review - **Data extraction** — invoice/receipt text mining - **Content moderation** — scan PDFs for keywords - **OCR preparation** — flag scanned PDFs that need image-to-text processing ### Pricing | Event | Price | |-------|-------| | Actor start | $0.001 | | PDF extracted | $0.005 | **Example**: Process 1,000 PDFs ≈ **$5.00** ### Issues & Feedback Found a bug or have a feature request? [Open an issue on the Issues tab](https://console.apify.com/actors/4h1HeF87bxEsek8FR/issues) — we respond within 24 hours. ### Related Actors - [Website Contact Extractor](https://apify.com/santamaria-automations/website-contact-extractor) — pull contacts from any website - [Website Tech Stack Detector](https://apify.com/santamaria-automations/website-tech-detector) — detect site technologies - [Email Verifier](https://apify.com/santamaria-automations/email-verifier) — bulk email validation - [Domain WHOIS & DNS](https://apify.com/santamaria-automations/domain-whois-dns) — domain intelligence # Actor input Schema ## `pdfUrls` (type: `array`): List of direct PDF URLs to download and extract. Each PDF is processed independently. ## `maxFileSizeMB` (type: `integer`): PDFs larger than this will be skipped with an error. Protects against runaway downloads. ## `extractMetadata` (type: `boolean`): Pull document metadata (title, author, creation date, producer, keywords). ## `extractText` (type: `boolean`): Pull full text content from every page. Disable if you only need metadata. ## `timeoutSeconds` (type: `integer`): Per-PDF download + parsing timeout. Increase for very large documents. ## `proxyConfiguration` (type: `object`): Optional proxy for downloading PDFs from restricted sources. ## Actor input object example ```json { "pdfUrls": [ "https://www.w3.org/WAI/ER/tests/xhtml/testfiles/resources/pdf/dummy.pdf", "https://www.irs.gov/pub/irs-pdf/f1040.pdf" ], "maxFileSizeMB": 50, "extractMetadata": true, "extractText": true, "timeoutSeconds": 60, "proxyConfiguration": { "useApifyProxy": false } } ``` # Actor output Schema ## `extractions` (type: `string`): Dataset containing one extraction record per input PDF URL # 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 = { "pdfUrls": [ "https://www.w3.org/WAI/ER/tests/xhtml/testfiles/resources/pdf/dummy.pdf", "https://www.irs.gov/pub/irs-pdf/f1040.pdf" ] }; // Run the Actor and wait for it to finish const run = await client.actor("santamaria-automations/pdf-extractor").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 = { "pdfUrls": [ "https://www.w3.org/WAI/ER/tests/xhtml/testfiles/resources/pdf/dummy.pdf", "https://www.irs.gov/pub/irs-pdf/f1040.pdf", ] } # Run the Actor and wait for it to finish run = client.actor("santamaria-automations/pdf-extractor").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 '{ "pdfUrls": [ "https://www.w3.org/WAI/ER/tests/xhtml/testfiles/resources/pdf/dummy.pdf", "https://www.irs.gov/pub/irs-pdf/f1040.pdf" ] }' | apify call santamaria-automations/pdf-extractor --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=santamaria-automations/pdf-extractor", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "PDF Text Extractor - Bulk PDF to Text & Metadata", "description": "Extract text and metadata from any PDF URL in bulk. Get page content, author, title, creation date, and more. Detects scanned PDFs that need OCR. Perfect for document analysis, research, and compliance.", "version": "1.0", "x-build-id": "dFHSHbHiKKmf4Uj6v" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/santamaria-automations~pdf-extractor/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-santamaria-automations-pdf-extractor", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/santamaria-automations~pdf-extractor/runs": { "post": { "operationId": "runs-sync-santamaria-automations-pdf-extractor", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/santamaria-automations~pdf-extractor/run-sync": { "post": { "operationId": "run-sync-santamaria-automations-pdf-extractor", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "pdfUrls" ], "properties": { "pdfUrls": { "title": "PDF URLs", "type": "array", "description": "List of direct PDF URLs to download and extract. Each PDF is processed independently.", "items": { "type": "string" } }, "maxFileSizeMB": { "title": "Max File Size (MB)", "minimum": 1, "maximum": 500, "type": "integer", "description": "PDFs larger than this will be skipped with an error. Protects against runaway downloads.", "default": 50 }, "extractMetadata": { "title": "Extract Metadata", "type": "boolean", "description": "Pull document metadata (title, author, creation date, producer, keywords).", "default": true }, "extractText": { "title": "Extract Text", "type": "boolean", "description": "Pull full text content from every page. Disable if you only need metadata.", "default": true }, "timeoutSeconds": { "title": "Timeout (seconds)", "minimum": 5, "maximum": 600, "type": "integer", "description": "Per-PDF download + parsing timeout. Increase for very large documents.", "default": 60 }, "proxyConfiguration": { "title": "Proxy Configuration", "type": "object", "description": "Optional proxy for downloading PDFs from restricted sources.", "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 } } } } } } } } } } ```