# PDF Text Extractor Batch (`snapperwapper/pdf-text-extractor-batch`) Actor

Extract text and document metadata from a bounded batch of public PDF URLs.

- **URL**: https://apify.com/snapperwapper/pdf-text-extractor-batch.md
- **Developed by:** [snapperwapper](https://apify.com/snapperwapper) (community)
- **Categories:** Developer tools, AI
- **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, 0 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 web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
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.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — 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 Batch

Extract searchable text, basic PDF metadata, and page counts from up to 50 public PDF URLs. One dataset row is emitted for every input, including structured errors, so a bad PDF does not hide successful results.

### Input

```json
{
  "pdfUrls": ["https://example.com/report.pdf"],
  "timeoutSecs": 30,
  "maxTextChars": 1000000
}
```

- `pdfUrls`: 1–50 public HTTP(S) PDF URLs.
- `timeoutSecs`: 1–120 seconds per request.
- `maxTextChars`: 1–5,000,000 returned characters per PDF.

Each download is streamed into bounded memory and rejected above **20 MB**. Redirects are limited and every target is DNS-checked to block localhost, private/link-local networks, credentials, and non-HTTP schemes.

### Output

Successful rows contain `url`, `status`, `text`, `textLength`, `textTruncated`, `pageCount`, and `metadata`. Failed rows contain `url`, `status: "error"`, and `error.code`/`error.message`.

### Limits and rights

This Actor performs text extraction only: **no OCR**, browser, proxy, paid API, login/paywall bypass, or binary persistence. PDF bytes exist only in bounded memory for parsing and are never pushed to Apify storage. Process only user-supplied public URLs that you are authorized to access, and ensure you have the necessary rights for downstream storage and reuse of extracted content.

### Local development

Requires Node.js 22 or newer.

```bash
npm ci
npm test
apify validate-schema
```

# Actor input Schema

## `pdfUrls` (type: `array`):

One to 50 public HTTP(S) PDF URLs.

## `timeoutSecs` (type: `integer`):

Maximum time for each HTTP request.

## `maxTextChars` (type: `integer`):

Text is truncated after this many characters; PDFs are still limited to 20 MB downloads.

## Actor input object example

```json
{
  "timeoutSecs": 30,
  "maxTextChars": 1000000
}
```

# 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 '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {};

// Run the Actor and wait for it to finish
const run = await client.actor("snapperwapper/pdf-text-extractor-batch").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 '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {}

# Run the Actor and wait for it to finish
run = client.actor("snapperwapper/pdf-text-extractor-batch").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 '{}' |
apify call snapperwapper/pdf-text-extractor-batch --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=snapperwapper/pdf-text-extractor-batch",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/acts/bM9YUWnBiMgWGeEsb/builds/5HN6IFbVib7PWCyC6/openapi.json