# Fast PDF to Text & Markdown (no OCR) (`renev3408/pdf-to-markdown`) Actor

Extract clean text and Markdown from text-layer PDFs in seconds. No OCR, no heavy dependencies — fast and cheap. Built for feeding documents into LLM pipelines. Scanned/image-only PDFs are not supported.

- **URL**: https://apify.com/renev3408/pdf-to-markdown.md
- **Developed by:** [Rene Vergara](https://apify.com/renev3408) (community)
- **Security:** Limited permissions
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.01 / 1,000 results

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/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
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.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## 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.

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 examples already wired to this Actor's own input schema, see the [API](#api) section below.

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`).

# README

## Fast PDF to Text & Markdown (no OCR)

Fetch a PDF by URL and return clean **text** and **Markdown** in seconds, ready to feed into an LLM
or a downstream pipeline.

- **Text-layer PDFs only, no OCR.** Scanned/image-only PDFs require OCR and are not supported — this
  keeps every run fast and cheap.
- One row per input URL, pushed to the dataset.
- Markdown output inserts a `---` page separator between pages.

### Input

```json
{
  "urls": ["https://example.com/document.pdf"]
}
```

| Field | Type   | Required | Description                                  |
| ----- | ------ | -------- | -------------------------------------------- |
| urls  | array  | yes      | One or more PDF URLs to extract text from    |

### Output (dataset)

Each item:

| Field    | Type    | Description                                        |
| -------- | ------- | -------------------------------------------------- |
| url      | string  | The PDF URL that was fetched                       |
| pages    | integer | Number of pages in the PDF                         |
| title    | string  | Document title from PDF metadata (may be null)     |
| text     | string  | Raw extracted text                                 |
| markdown | string  | Text with `---` page separators, for LLM context   |
| error    | string  | Present only when a URL could not be fetched/parsed|

### Example output

```json
{
  "url": "https://example.com/document.pdf",
  "pages": 3,
  "title": "Quarterly Report",
  "text": "Page one content…",
  "markdown": "Page one content…\n\n---\n\nPage two content…"
}
```

### Notes

- No API keys, no OCR, no persistent storage — only a key-value store is unused here.
- Fetches are done server-side with a plain Node `fetch`; no browser is launched.

### Run locally

```bash
apify run
```

### Deploy

```bash
apify push
```

# Actor input Schema

## `urls` (type: `array`):

One or more PDF URLs to extract text from. Text-layer PDFs only (scanned/image-only PDFs need OCR and are not supported).

## Actor input object example

```json
{
  "urls": [
    "https://www.w3.org/WAI/ER/tests/xhtml/testfiles/resources/pdf/dummy.pdf"
  ]
}
```

# Actor output Schema

## `results` (type: `string`):

No description

# 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 = {
    "urls": [
        "https://www.w3.org/WAI/ER/tests/xhtml/testfiles/resources/pdf/dummy.pdf"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("renev3408/pdf-to-markdown").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 = { "urls": ["https://www.w3.org/WAI/ER/tests/xhtml/testfiles/resources/pdf/dummy.pdf"] }

# Run the Actor and wait for it to finish
run = client.actor("renev3408/pdf-to-markdown").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "urls": [
    "https://www.w3.org/WAI/ER/tests/xhtml/testfiles/resources/pdf/dummy.pdf"
  ]
}' |
apify call renev3408/pdf-to-markdown --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,renev3408/pdf-to-markdown"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/3CtolZgiAWBRpNdhO/builds/4RHw3cmEx2eNoUVfr/openapi.json