# HuggingFace Papers Scraper (`dadhalfdev/huggingface-papers-scraper`) Actor

Scrape trending HuggingFace Papers by day, week, or month. Get titles, dates, submitters, organizations, upvotes, abstracts, summaries, PDFs, project links, and agent-ready commands for AI agents, RAG pipelines, research monitoring, and automation.

- **URL**: https://apify.com/dadhalfdev/huggingface-papers-scraper.md
- **Developed by:** [Marco Rodrigues](https://apify.com/dadhalfdev) (community)
- **Categories:** News, Other
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$20.00 / 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/platform/actors/running/actors-in-store#pay-per-event

## 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

## 🤗 HuggingFace Papers Scraper

Track trending AI research from **[HuggingFace Papers](https://huggingface.co/papers)** and turn it into clean, structured data for agents, dashboards, and research workflows.

Choose a **period** (`Daily`, `Weekly`, or `Monthly`), pick an **end date**, and scrape up to **200 papers** with titles, abstracts, summaries, upvotes, PDF links, and more. The actor starts from the end date and walks older papers.

![HuggingFace Papers](https://i.ibb.co/pBB8jM3H/Screenshot-From-2026-06-01-17-29-27.png)

### 💡 Perfect for…

- **🤖 AI agents:** Fresh research context with `pdf_url`, `project_url`, and `agent_command`.
- **📚 RAG pipelines:** Index abstracts, summaries, and source URLs with citations.
- **🔬 Research monitoring:** Spot emerging models, benchmarks, and methods.
- **📈 Trend analysis:** Compare upvotes, organizations, and topics over time.

### ✨ Why you'll love this scraper

- 📅 **Flexible windows:** Daily, weekly, or monthly views from a date you choose.
- 📄 **Research-ready fields:** Abstract, summary, PDF link, project page, and HuggingFace read command.
- 🏢 **Attribution:** Submitter and organization details when available.

### 📦 What's inside the data?

- **Core:** `url`, `title`, `published_date`, `submitted_date`
- **People/org:** `submitted_by`, `submitted_by_url`, `organization`, `organization_url`
- **Engagement:** `upvotes`
- **Content:** `abstract`, `summary`
- **Links:** `pdf_url`, `project_url`, `agent_command` (e.g. `hf papers read 2605.29486`)

### 🚀 Quick start

1. Choose **`period`**: Daily, Weekly, or Monthly.
2. Optionally set **`end_date`** (YYYY-MM-DD). Empty or future → uses today.
3. Set **`max_papers`** (up to 200).
4. Start and export JSON, CSV, or Excel.

***

#### Example input

```json
{
  "period": "Daily",
  "end_date": "2026-06-01",
  "max_papers": 100
}
```

#### Example output

```json
{
  "url": "https://huggingface.co/papers/2605.29486",
  "title": "PhoneWorld: Scaling Phone-Use Agent Environments",
  "published_date": "2026-05-28T00:00:00",
  "submitted_date": "2026-05-29T00:00:00",
  "submitted_by": "Zhengyang Tang",
  "submitted_by_url": "https://huggingface.co/tangzhy",
  "organization": "shanghai ailab",
  "organization_url": "https://huggingface.co/ShanghaiAiLab",
  "upvotes": 2,
  "abstract": "PhoneWorld is a pipeline that transforms real GUI trajectories…",
  "summary": "A central bottleneck for phone-use agents…",
  "pdf_url": "https://arxiv.org/pdf/2605.29486",
  "project_url": null,
  "agent_command": "hf papers read 2605.29486"
}
```

| Parameter | Type | Required | Description |
|-----------|------|----------|-------------|
| `period` | string | No | `Daily`, `Weekly`, or `Monthly`. Default: `Daily`. |
| `end_date` | string | No | Latest date to start from (`YYYY-MM-DD`). Empty/future → today. |
| `max_papers` | integer | No | How many papers to collect. Min 10, max 200, default 100. |

# Actor input Schema

## `period` (type: `string`):

Time window on HuggingFace Papers: Daily, Weekly, or Monthly.

## `end_date` (type: `string`):

Latest date to start from. The scraper then walks older papers from this date. Leave empty (or pick a future date) to use today.

## `max_papers` (type: `integer`):

How many papers to collect.

## Actor input object example

```json
{
  "period": "Daily",
  "max_papers": 100
}
```

# Actor output Schema

## `overview` (type: `string`):

Table view of scraped Hugging Face papers using the dataset 'overview' view.

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

All scraped Hugging Face paper records from the default dataset without view transformation.

# 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("dadhalfdev/huggingface-papers-scraper").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("dadhalfdev/huggingface-papers-scraper").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 dadhalfdev/huggingface-papers-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=dadhalfdev/huggingface-papers-scraper",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/WxgRFziXJdcuR0Agu/builds/ni7hZQxFfreuXUpIB/openapi.json