# PDF parser: text, metadata, links and form fields as JSON

**Use case:** 

Parse PDFs into structured JSON: the text per page, headings as Markdown, the title, author and dates, every link, and the values of filled-in form fields. Good for building your own document pipeline without running a PDF library yourself.

## Input

```json
{
  "urls": [
    "https://arxiv.org/pdf/1706.03762v7",
    "https://www.irs.gov/pub/irs-pdf/f1040.pdf"
  ],
  "outputFormat": "both",
  "splitBy": "page",
  "chunkSize": 2000,
  "chunkOverlap": 200,
  "includePages": false,
  "removeHeadersFooters": true,
  "ocr": false,
  "ocrLanguages": [
    "eng"
  ],
  "maxPdfsPerPage": 20,
  "maxFileSizeMb": 100,
  "maxConcurrency": 3
}
```

## Output

```json
{
  "fileName": {
    "label": "File",
    "format": "text"
  },
  "status": {
    "label": "Status",
    "format": "text"
  },
  "title": {
    "label": "Title",
    "format": "text"
  },
  "pageCount": {
    "label": "Pages",
    "format": "number"
  },
  "pageNumber": {
    "label": "Page",
    "format": "number"
  },
  "chunkIndex": {
    "label": "Chunk",
    "format": "number"
  },
  "charCount": {
    "label": "Characters",
    "format": "number"
  },
  "text": {
    "label": "Text",
    "format": "text"
  },
  "errorMessage": {
    "label": "Problem",
    "format": "text"
  },
  "url": {
    "label": "URL",
    "format": "link"
  }
}
```

## How it works

### 1. Sign up on Apify or log in

The PDF Text Extractor: PDF and Image to Text, with OCR Actor is ready to run with the inputs already set for "PDF parser: text, metadata, links and form fields as JSON". [Sign up or log in](https://console.apify.com/create-task-from-example/836bfSYtRcx5Ykbzx) and you'll land in Apify Console with a copy of this exact task.

### 2. Start the "PDF parser: text, metadata, links and form fields as JSON" task

The PDF Text Extractor: PDF and Image to Text, with OCR Actor will start running based on the input automatically. You can also change all the input fields, like PDF or image URLs, or web pages, output format, and more, to match your specific use case.

### 3. Receive the "PDF parser: text, metadata, links and form fields as JSON" output

Monitor the progress in real time. You will be notified as soon as your dataset is complete and ready for review. Each result includes data such as file, status, title, and more.

### 4. Integrate into your workflow

The final output is delivered in JSON, CSV, or Excel format, ready to be plugged into your workflow. You can also [run the "PDF parser: text, metadata, links and form fields as JSON" task via API](https://apify.com/vindr/pdf-text-extractor.md).

## About this Actor

This example demonstrates how to use [PDF Text Extractor: PDF and Image to Text, with OCR](https://apify.com/vindr/pdf-text-extractor.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/vindr/pdf-text-extractor.md) to learn more, explore other use cases, and run it yourself.


## How to integrate an Actor?

This Task's input is already configured above. Use it as-is rather than inventing a new one.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For full API examples (JavaScript, Python, CLI, MCP, OpenAPI), see this Task's Actor page: https://apify.com/vindr/pdf-text-extractor.md

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).