# PDF Toolkit — Extract Text, Metadata & Page Count (`accurate_pouch/pdf-toolkit`) Actor Extract text from PDFs, read metadata (title, author, dates), count pages. Bulk processing from URLs. $0.003 per PDF. - **URL**: https://apify.com/accurate\_pouch/pdf-toolkit.md - **Developed by:** [Manchitt Sanan](https://apify.com/accurate_pouch) (community) - **Categories:** Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## 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 Toolkit — Extract Text, Metadata & Page Count Process PDFs from URLs in bulk. Extract full text content, read document metadata (title, author, creation date), and count pages. $0.003 per PDF processed. --- ### Operations | Operation | What it returns | |-----------|----------------| | `extract-text` | Full text content + page count | | `get-metadata` | Title, author, subject, creator, producer, creation/modification dates + page count | | `page-count` | Number of pages only | --- ### Quick start ```json { "items": [ { "url": "https://www.w3.org/WAI/ER/tests/xhtml/testfiles/resources/pdf/dummy.pdf", "operation": "extract-text" } ] } ```` *** ### Input Each item in the `items` array: | Field | Type | Required | Description | |-------|------|----------|-------------| | `url` | string | Yes | URL to a PDF file | | `operation` | enum | Yes | `extract-text`, `get-metadata`, or `page-count` | *** ### Output ```json { "url": "https://example.com/document.pdf", "operation": "extract-text", "text": "Full extracted text content...", "pageCount": 12, "fileSize": 245760, "status": "success", "error": null } ``` *** ### Pricing **$0.003 per PDF processed** (pay-per-event pricing). - Errors and dry runs are never charged. - 100 PDFs = $0.30 - 1,000 PDFs = $3.00 *** ### Limitations - **Text extraction only** — no OCR. Scanned PDFs (images of text) will return empty or minimal text. - **Max file size** depends on Apify memory allocation. Default 256MB handles most PDFs. - **No PDF generation** — this actor reads PDFs, doesn't create them. Use Apify's official HTML-to-PDF actor for generation. *** ### Related Tools by manchittlab - **[Image Processor](https://apify.com/accurate_pouch/image-processor)** — Batch resize, convert, compress, watermark images. - **[QR Code Toolkit](https://apify.com/accurate_pouch/qr-code-toolkit)** — Generate and decode QR codes with custom colors and logos. - **[Broken Link Checker](https://apify.com/accurate_pouch/broken-link-checker)** — Find every broken link on your website. - **[Email Validator Pro](https://apify.com/accurate_pouch/email-validator)** — Bulk email validation with SMTP check. - **[Domain Age Checker](https://apify.com/accurate_pouch/domain-age-checker)** — Bulk RDAP domain age lookup. - **[Google Sheets Reader & Writer](https://apify.com/accurate_pouch/google-sheets-rw)** — Read/write Google Sheets via Service Account. *** ### Run on Apify [![Run on Apify](https://apify.com/static/run-on-apify.svg)](https://apify.com/accurate_pouch/pdf-toolkit) No setup needed. Click above to run in the cloud. $0.003 per operation. # Actor input Schema ## `items` (type: `array`): Array of PDF operations. Each has a url and operation (extract-text, get-metadata, page-count). ## `dryRun` (type: `boolean`): Process PDFs but don't charge. ## Actor input object example ```json { "items": [ { "url": "https://www.w3.org/WAI/ER/tests/xhtml/testfiles/resources/pdf/dummy.pdf", "operation": "extract-text" } ], "dryRun": false } ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "items": [ { "url": "https://www.w3.org/WAI/ER/tests/xhtml/testfiles/resources/pdf/dummy.pdf", "operation": "extract-text" } ] }; // Run the Actor and wait for it to finish const run = await client.actor("accurate_pouch/pdf-toolkit").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${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 = { "items": [{ "url": "https://www.w3.org/WAI/ER/tests/xhtml/testfiles/resources/pdf/dummy.pdf", "operation": "extract-text", }] } # Run the Actor and wait for it to finish run = client.actor("accurate_pouch/pdf-toolkit").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 '{ "items": [ { "url": "https://www.w3.org/WAI/ER/tests/xhtml/testfiles/resources/pdf/dummy.pdf", "operation": "extract-text" } ] }' | apify call accurate_pouch/pdf-toolkit --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=accurate_pouch/pdf-toolkit", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "PDF Toolkit — Extract Text, Metadata & Page Count", "description": "Extract text from PDFs, read metadata (title, author, dates), count pages. Bulk processing from URLs. $0.003 per PDF.", "version": "0.1", "x-build-id": "x2DbGk57u034bkZv8" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/accurate_pouch~pdf-toolkit/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-accurate_pouch-pdf-toolkit", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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/accurate_pouch~pdf-toolkit/runs": { "post": { "operationId": "runs-sync-accurate_pouch-pdf-toolkit", "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/accurate_pouch~pdf-toolkit/run-sync": { "post": { "operationId": "run-sync-accurate_pouch-pdf-toolkit", "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": [ "items" ], "properties": { "items": { "title": "PDF Operations", "type": "array", "description": "Array of PDF operations. Each has a url and operation (extract-text, get-metadata, page-count)." }, "dryRun": { "title": "Dry Run", "type": "boolean", "description": "Process PDFs but don't charge.", "default": 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 } } } } } } } } } } ```