# HuggingFace Daily Papers Scraper - Trending AI Research (`ninhothedev/hf-daily-papers-scraper`) Actor

$0.5/1K 🔥 Fast HuggingFace Daily Papers scraper! Trending AI papers — title, authors, upvotes, abstract & arXiv link. No key. JSON, CSV, Excel or API in seconds. Pull daily for AI research tracking & newsletters ⚡

- **URL**: https://apify.com/ninhothedev/hf-daily-papers-scraper.md
- **Developed by:** [ninhothedev](https://apify.com/ninhothedev) (community)
- **Categories:** AI, Developer tools, News
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.50 / 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 Daily Papers Scraper 🤗📄

**Scrape the trending AI research papers from [HuggingFace Daily Papers](https://huggingface.co/papers) — title, authors, upvotes, abstract, comments, GitHub repo, and direct arXiv & HuggingFace links.** No API key. Fast, cheap, and datacenter-proxy friendly.

The HuggingFace Daily Papers feed is where the machine-learning community surfaces the most important new papers every day, ranked by community upvotes. This actor turns that feed into clean, structured JSON/CSV/Excel you can drop into a newsletter, dashboard, spreadsheet, or research pipeline.

***

### ✨ What you get

For every paper:

| Field | Description |
|-------|-------------|
| `arxiv_id` | The arXiv identifier (e.g. `2607.10966`) |
| `title` | Paper title |
| `authors` | List of author names |
| `summary` | Abstract (capped at 5000 chars) |
| `upvotes` | Community upvotes on HuggingFace |
| `num_comments` | Number of discussion comments |
| `github_repo` | Linked code repository (if any) |
| `github_stars` | Stars on the linked repo (if any) |
| `published_at` | Publication date (ISO-8601 UTC) |
| `thumbnail` | Social preview image URL |
| `arxiv_url` | `https://arxiv.org/abs/<id>` |
| `hf_url` | `https://huggingface.co/papers/<id>` |
| `source` | Always `huggingface` |
| `scraped_at` | When this run captured the data |

***

### 🚀 Input

```json
{
  "mode": "papers",
  "date": "",
  "maxItems": 100
}
```

| Field | Type | Description |
|-------|------|-------------|
| `mode` | select | `papers` — fetch the trending daily papers feed. |
| `date` | string | Optional `YYYY-MM-DD` (e.g. `2026-07-14`). Empty = latest trending papers. |
| `maxItems` | integer | Max papers to return. Default `100`, hard cap `500`. |

#### Get the latest trending papers

```json
{ "mode": "papers", "maxItems": 50 }
```

#### Get papers for a specific day

```json
{ "mode": "papers", "date": "2026-07-14", "maxItems": 100 }
```

***

### 📤 Output sample

```json
{
  "arxiv_id": "2607.10966",
  "title": "SVR-R1: Bootstrapping Multi-modal Reasoning with Self-verification in RL",
  "authors": ["Mingyuan Wu", "Jingcheng Yang", "Shengyi Qian"],
  "summary": "We introduce Self-Verified Reasoner (SVR-R1) ...",
  "upvotes": 42,
  "num_comments": 7,
  "github_repo": "https://github.com/example/svr-r1",
  "github_stars": 128,
  "published_at": "2026-07-13T00:00:00+00:00",
  "thumbnail": "https://cdn-thumbnails.huggingface.co/social-thumbnails/papers/2607.10966.png",
  "arxiv_url": "https://arxiv.org/abs/2607.10966",
  "hf_url": "https://huggingface.co/papers/2607.10966",
  "source": "huggingface",
  "scraped_at": "2026-07-20T12:00:00+00:00"
}
```

***

### 💡 Use cases

- **AI research tracking** — never miss a trending paper; poll daily and pipe into Slack/Notion.
- **Trend discovery** — spot the topics gaining upvotes fastest across the ML community.
- **Newsletters** — auto-generate a "Top AI papers this week" digest with links and abstracts.
- **Literature review** — export to Excel/CSV and triage candidate papers with authors and code links.

***

### 💰 Pricing

Cheap by design — this hits a clean public JSON API, so runs are fast and light. Roughly **~$0.50 per 1,000 papers** scraped. A daily 100-paper pull costs pennies.

***

### 🔗 Related actors by the same author

- [arXiv Scraper](https://apify.com/ninhothedev/arxiv-scraper)
- [Semantic Scholar Scraper](https://apify.com/ninhothedev/semantic-scholar-scraper)
- [HuggingFace Models Scraper](https://apify.com/ninhothedev/huggingface-models-scraper)
- [OpenAlex Scraper](https://apify.com/ninhothedev/openalex-scraper)

***

### ⚙️ Notes

- No login or API key required.
- Works on the free datacenter proxy (the API is not IP-gated).
- Returns one dataset item per paper.

***

**Keywords:** huggingface scraper, daily papers, AI research scraper, arxiv scraper, trending machine learning papers, ML papers API, research paper scraper, LLM papers, AI newsletter, paper upvotes, huggingface papers api, academic scraper, deep learning papers.

# Actor input Schema

## `mode` (type: `string`):

What to scrape. 'papers' fetches the trending HuggingFace Daily Papers feed (optionally for a specific date).

## `date` (type: `string`):

Specific day to fetch in YYYY-MM-DD format (e.g. 2026-07-14). Leave empty to get the latest trending daily papers.

## `maxItems` (type: `integer`):

Maximum number of papers to return. Default 100, hard cap 500.

## Actor input object example

```json
{
  "mode": "papers",
  "date": "2026-07-14",
  "maxItems": 100
}
```

# 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("ninhothedev/hf-daily-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("ninhothedev/hf-daily-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 ninhothedev/hf-daily-papers-scraper --silent --output-dataset

```

## MCP server setup

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

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/CLLkJp0TbTZgV0Lj1/builds/6vOTd9t02goP8FOiv/openapi.json