# Hacker News Scraper - Stories, Comments & Trends (`viralanalyzer/hackernews-intelligence`) Actor

Scrape Hacker News stories, comments, and discussions. Track tech trends, startup news, and developer community sentiment.

- **URL**: https://apify.com/viralanalyzer/hackernews-intelligence.md
- **Developed by:** [viralanalyzer](https://apify.com/viralanalyzer) (community)
- **Categories:** News, Developer tools
- **Stats:** 7 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: 5.00 out of 5 stars

## Pricing

from $15.75 / 1,000 story scrapeds

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#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

## 📰 Hacker News Intelligence — Stories, Comments & Trends

> 🔗 [View on Apify Store](https://apify.com/viralanalyzer/hackernews-intelligence) | 🇺🇸 English | [🇧🇷 Português](#português)

Scrape **Hacker News stories and comments** using the public Algolia HN API and Firebase API. Search by keyword, browse the front page, get top stories, or explore **Show HN** and **Ask HN** submissions. No API key needed.

### ✨ Features

- 🔍 **5 scraping modes** — Search, Front Page, Top Stories, Show HN, Ask HN
- 🔑 **Keyword search** — Find stories by topic with relevance or date sorting
- 🕐 **Time range filters** — Past 24h, week, month, year, or all time
- 💬 **Comment extraction** — Fetch top comments per story (optional)
- 📊 **Full metrics** — Points, comment count, author, timestamps
- 🔗 **Direct links** — Original URL + HN discussion URL
- 🛡️ **Anti-placeholder guardrails** — Every result validated as real data
- ⚡ **API-based** — Fast and reliable via Algolia HN Search + Firebase

### 📥 Input

| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
| `mode` | string | ✅ | "search" | Scraping mode: search, front\_page, top\_stories, show\_hn, ask\_hn |
| `searchQueries` | string\[] | ❌ | — | Keywords to search (required in "search" mode, up to 10) |
| `sortBy` | string | ❌ | "relevance" | Sort: relevance, date |
| `timeRange` | string | ❌ | "all" | Time filter: all, 24h, week, month, year |
| `maxItems` | integer | ❌ | 50 | Max stories to scrape (1-500) |
| `includeComments` | boolean | ❌ | false | Fetch top comments for each story |
| `maxCommentsPerStory` | integer | ❌ | 5 | Max comments per story (1-20) |

#### Input Example

```json
{
  "mode": "search",
  "searchQueries": [
    "AI startup",
    "machine learning",
    "open source LLM"
  ],
  "sortBy": "date",
  "timeRange": "week",
  "maxItems": 100,
  "includeComments": true,
  "maxCommentsPerStory": 5
}
```

### 📤 Output

Every story includes these fields:

| Field | Type | Description |
|---|---|---|
| `storyId` | string | Hacker News story ID |
| `title` | string | Story title |
| `url` | string | Original link URL |
| `author` | string | Submitter username |
| `points` | number | Upvote count |
| `numComments` | number | Total comment count |
| `createdAt` | string | Submission timestamp (ISO 8601) |
| `storyText` | string | Story body text (for Ask HN / Show HN) |
| `tags` | string\[] | HN tags (story, show\_hn, ask\_hn, etc.) |
| `hnUrl` | string | Hacker News discussion URL |
| `platform` | string | Always "hackernews" |
| `scrapedAt` | string | ISO 8601 timestamp |
| `topComments` | object\[] | Top comments (when includeComments is enabled) |

#### Comment Fields

| Field | Type | Description |
|---|---|---|
| `commentId` | string | Comment ID |
| `author` | string | Commenter username |
| `text` | string | Comment text (HTML stripped) |
| `createdAt` | string | Comment timestamp |
| `points` | number | Comment points |

#### Output Example

```json
{
  "storyId": "39847261",
  "title": "Show HN: We built an open-source alternative to Notion with local-first sync",
  "url": "https://github.com/AppFlowy-IO/AppFlowy",
  "author": "annieflowy",
  "points": 847,
  "numComments": 213,
  "createdAt": "2026-03-04T16:42:31.000Z",
  "storyText": "",
  "tags": ["story", "show_hn", "front_page"],
  "hnUrl": "https://news.ycombinator.com/item?id=39847261",
  "platform": "hackernews",
  "scrapedAt": "2026-03-06T14:15:22.108Z",
  "topComments": [
    {
      "commentId": "39848102",
      "author": "tptacek",
      "text": "This is impressive work. The offline-first approach with CRDT sync is the right way to build collaborative tools.",
      "createdAt": "2026-03-04T17:08:14.000Z",
      "points": 142
    }
  ]
}
```

### 📋 Use Cases

- **Tech Trend Detection** — Track which technologies and startups are gaining traction
- **Content Marketing** — Find trending topics in your niche for blog inspiration
- **Competitive Intelligence** — Monitor mentions of competitors or products
- **Developer Relations** — Track Show HN launches and community feedback
- **Research** — Analyze discussion patterns and sentiment in tech communities
- **News Aggregation** — Build curated feeds of top stories by topic

### ✅ Capabilities & Limits

Stated up front, so you do not pay a run to find out.

**Built here:** in `search` mode `maxItems` applies twice - once per keyword while fetching, then again as a global cap on the pushed dataset. Every query pulls up to `maxItems` stories, they are merged in query order, deduplicated, and truncated to `maxItems` total. Five keywords at `maxItems: 50` still yield 50 rows, and the last keywords can be cut entirely. One keyword per run is the only way to get 50 each.

| Input / feature | Supported | Notes |
|---|---|---|
| Mode | ✅ | `mode` — required; search, front page or trending |
| Keyword search | ✅ | `searchQueries` — `search` mode only |
| Sort and time range | ✅ | `sortBy`, `timeRange` |
| Top comments | ✅ | `includeComments` with `maxCommentsPerStory` — slower, more data |
| **Full comment threads** | ❌ | top-level comments only, not the whole nested tree |
| User profiles / karma history | ❌ | stories and comments, not accounts |
| Dead or flagged posts | ❌ | what the public HN interface shows |
| Result volume | ⚠️ | `maxItems` |

### 🚦 What a run with zero stories does

The actor tells you *why* it found nothing, and the reason comes from what the HN APIs actually returned — the HTTP status code and the record container inside the response body. No guessing from page text.

| What the origin did | Run status | Dataset | Charged |
|---|---|---|---|
| Answered `HTTP 200` and returned an **empty result set** — no HN story matches your keyword | SUCCEEDED | 1 diagnostic row, `_dataQuality: "diagnostic"` | **No PPE** |
| Blocked every request (`HTTP 403`, `HTTP 429`, timeout) so no record ever arrived | SUCCEEDED | 1 diagnostic row with `_blockReason` | **No PPE** |
| Returned stories but the actor parsed none of them | **FAILED**, exit code 1 | empty | **No PPE** |
| Answered normally with an empty set while `timeRange` was narrowing it | **SUCCEEDED**, diagnostic row names `timeRange` as the likely cause | 1 diagnostic row | **No PPE** |
| Never answered, or changed the response shape | **FAILED**, exit code 1 | empty | **No PPE** |

Parser drift fails loudly on purpose. A run that returns nothing because the HN API renamed a field would otherwise look identical to "your keyword has no matches", and you would pay a run start to find out months later.

The diagnostic row from the first line looks like this:

```json
{
  "setup_status": "DIAGNOSTIC_GUIDE",
  "_dataQuality": "diagnostic",
  "_blockReason": "origin-confirmed-empty (HTTP 200, empty result set)",
  "message": "[DIAGNÓSTICO] Zero stories (mode=search) — Hacker News answered and has no matching story.",
  "potential_causes": [
    "The HN API answered normally and returned an empty result set for this query",
    "No Hacker News story matches [\"quantum yodelling compiler\"]"
  ],
  "remediations": [
    "Use a broader or differently spelled keyword (HN search matches title text, not synonyms)",
    "Try mode=\"front_page\" or mode=\"top_stories\" to confirm the actor reaches HN normally"
  ],
  "mode": "search",
  "searchQueries": ["quantum yodelling compiler"],
  "timeRange": "all",
  "sortBy": "relevance",
  "maxItems": 50,
  "recordsReturnedByOrigin": 0,
  "rawStoriesCollected": 0,
  "uniqueAfterDedup": 0,
  "dataSource": "hn-algolia + hn-firebase",
  "scrapedAt": "2026-08-27T14:15:22.108Z"
}
```

Filter your dataset on `_dataQuality != "diagnostic"` and diagnostic rows never reach your pipeline.

### ❓ FAQ

**Q: Does this actor need an API key?**
A: No. It uses the public Algolia HN Search API and Firebase API, both freely accessible without authentication.

**Q: What is the difference between "front\_page" and "top\_stories" modes?**
A: "front\_page" returns the stories currently displayed on the Hacker News homepage (around 30 items). "top\_stories" uses Firebase's canonical top stories list, which can return up to 500 of the highest-ranked active stories.

**Q: Will enabling comments slow down the scraper?**
A: Yes. Each story with comments requires an additional API call. For large runs (100+ stories), expect significantly longer execution times. Use `maxCommentsPerStory` to control the volume.

**Q: Can I search for multiple keywords in one run?**
A: Yes. The `searchQueries` parameter accepts up to 10 keywords. Results from all queries are deduplicated by story ID.

**Q: Why did the actor return fewer items than maxItems?**
A: Fewer stories matched your criteria. The actor deduplicates by story ID and drops titles shorter than 3 characters.

**Q: What happens on a run that finds zero stories?**
A: The ending depends on what Hacker News answered, and the run never charges PPE. An empty result set confirmed by the API — including one narrowed by your `timeRange`, which is sent to the HN API as a `created_at` filter — ends SUCCEEDED with one diagnostic row; so does a block (403/429/timeout). The failures are the cases where nothing confirms the emptiness: the API returned stories and the parser extracted none, the response had an unexpected shape, or the API never answered. Those exit with code 1. See the table above.

### 💰 Pricing

This actor uses **Pay Per Event (PPE)** pricing:

| Metric | Cost |
|--------|------|
| Per story scraped | $0.03 |

### 🔗 Related Actors

- [Stack Overflow Intelligence](https://apify.com/viralanalyzer/stackoverflow-intelligence) — SO questions & answers
- [GitHub Trending Scraper](https://apify.com/viralanalyzer/github-trending-scraper) — Trending repositories
- [Craigslist Scraper](https://apify.com/viralanalyzer/craigslist-scraper) — Classifieds & listings
- [YouTube Fast Scraper](https://apify.com/viralanalyzer/youtube-fast-scraper) — YouTube video metrics

### 📝 Changelog

#### v1.0 (Current)

- ✅ 5 scraping modes (search, front\_page, top\_stories, show\_hn, ask\_hn)
- ✅ Keyword search with relevance and date sorting
- ✅ Time range filtering (24h, week, month, year, all)
- ✅ Optional top comment extraction per story
- ✅ Dual API support (Algolia HN Search + Firebase)
- ✅ Deduplication by story ID
- ✅ Anti-placeholder guardrails
- ✅ Retry logic with rate limit handling
- ✅ Zero-story runs classified from observed HTTP status and response containers: confirmed-empty and confirmed-block end SUCCEEDED with a diagnostic row; parser drift, a silent API and user-emptied filters fail with exit code 1

***

<a name="português"></a>

## 📰 Hacker News Intelligence — Stories, Comentários & Tendências

> [🇺🇸 English](#-hacker-news-intelligence--stories-comments--trends) | 🇧🇷 Português

Extraia **stories e comentários do Hacker News** usando a API pública Algolia HN e Firebase. Busque por palavra-chave, navegue pela front page, obtenha top stories, ou explore **Show HN** e **Ask HN**. Sem necessidade de API key.

### ✨ Funcionalidades

- 🔍 **5 modos de scraping** — Search, Front Page, Top Stories, Show HN, Ask HN
- 🔑 **Busca por palavra-chave** — Encontre stories por tópico com ordenação por relevância ou data
- 🕐 **Filtros de período** — Últimas 24h, semana, mês, ano ou todos os tempos
- 💬 **Extração de comentários** — Busque top comentários por story (opcional)
- 📊 **Métricas completas** — Pontos, contagem de comentários, autor, timestamps
- 🔗 **Links diretos** — URL original + URL da discussão no HN
- 🛡️ **Guardrails anti-placeholder** — Todo resultado validado como dado real
- ⚡ **Baseado em API** — Rápido e confiável via Algolia HN Search + Firebase

### 📥 Entrada

| Parâmetro | Tipo | Obrigatório | Padrão | Descrição |
|---|---|---|---|---|
| `mode` | string | ✅ | "search" | Modo: search, front\_page, top\_stories, show\_hn, ask\_hn |
| `searchQueries` | string\[] | ❌ | — | Palavras-chave (obrigatório no modo "search", até 10) |
| `sortBy` | string | ❌ | "relevance" | Ordenar: relevance, date |
| `timeRange` | string | ❌ | "all" | Período: all, 24h, week, month, year |
| `maxItems` | inteiro | ❌ | 50 | Máx stories para extrair (1-500) |
| `includeComments` | boolean | ❌ | false | Buscar top comentários por story |
| `maxCommentsPerStory` | inteiro | ❌ | 5 | Máx comentários por story (1-20) |

#### Exemplo de Entrada

```json
{
  "mode": "search",
  "searchQueries": [
    "AI startup",
    "machine learning",
    "open source LLM"
  ],
  "sortBy": "date",
  "timeRange": "week",
  "maxItems": 100,
  "includeComments": true,
  "maxCommentsPerStory": 5
}
```

### 📤 Saída

Cada story inclui estes campos:

| Campo | Tipo | Descrição |
|---|---|---|
| `storyId` | string | ID da story no Hacker News |
| `title` | string | Título da story |
| `url` | string | URL do link original |
| `author` | string | Username do autor |
| `points` | número | Contagem de upvotes |
| `numComments` | número | Total de comentários |
| `createdAt` | string | Timestamp da submissão (ISO 8601) |
| `storyText` | string | Texto da story (para Ask HN / Show HN) |
| `tags` | string\[] | Tags do HN (story, show\_hn, ask\_hn, etc.) |
| `hnUrl` | string | URL da discussão no Hacker News |
| `platform` | string | Sempre "hackernews" |
| `scrapedAt` | string | Timestamp ISO 8601 |
| `topComments` | objeto\[] | Top comentários (quando includeComments habilitado) |

#### Campos do Comentário

| Campo | Tipo | Descrição |
|---|---|---|
| `commentId` | string | ID do comentário |
| `author` | string | Username do comentarista |
| `text` | string | Texto do comentário (HTML removido) |
| `createdAt` | string | Timestamp do comentário |
| `points` | número | Pontos do comentário |

#### Exemplo de Saída

```json
{
  "storyId": "39847261",
  "title": "Show HN: We built an open-source alternative to Notion with local-first sync",
  "url": "https://github.com/AppFlowy-IO/AppFlowy",
  "author": "annieflowy",
  "points": 847,
  "numComments": 213,
  "createdAt": "2026-03-04T16:42:31.000Z",
  "storyText": "",
  "tags": ["story", "show_hn", "front_page"],
  "hnUrl": "https://news.ycombinator.com/item?id=39847261",
  "platform": "hackernews",
  "scrapedAt": "2026-03-06T14:15:22.108Z",
  "topComments": [
    {
      "commentId": "39848102",
      "author": "tptacek",
      "text": "This is impressive work. The offline-first approach with CRDT sync is the right way to build collaborative tools.",
      "createdAt": "2026-03-04T17:08:14.000Z",
      "points": 142
    }
  ]
}
```

### 📋 Casos de Uso

- **Detecção de Tendências Tech** — Acompanhe quais tecnologias e startups estão ganhando tração
- **Marketing de Conteúdo** — Encontre tópicos em alta no seu nicho para inspiração de blog
- **Inteligência Competitiva** — Monitore menções de concorrentes ou produtos
- **Developer Relations** — Acompanhe lançamentos Show HN e feedback da comunidade
- **Pesquisa** — Analise padrões de discussão e sentimento em comunidades tech
- **Agregação de Notícias** — Monte feeds curados de top stories por tópico

### 🚦 O que acontece quando a execução não encontra nenhuma story

O actor informa *por que* não achou nada, e o motivo vem do que as APIs do HN de fato responderam — o código HTTP e o contêiner de registros dentro do corpo da resposta. Nada é deduzido do texto da página.

| O que a origem fez | Status da execução | Dataset | Cobrança |
|---|---|---|---|
| Respondeu `HTTP 200` com **conjunto de resultados vazio** — nenhuma story do HN casa com sua palavra-chave | SUCCEEDED | 1 linha de diagnóstico, `_dataQuality: "diagnostic"` | **Sem PPE** |
| Bloqueou todas as requisições (`HTTP 403`, `HTTP 429`, timeout) e nenhum registro chegou | SUCCEEDED | 1 linha de diagnóstico com `_blockReason` | **Sem PPE** |
| Devolveu stories e o actor não extraiu nenhuma | **FAILED**, exit code 1 | vazio | **Sem PPE** |
| Respondeu normalmente com conjunto vazio enquanto o `timeRange` estreitava a busca | **SUCCEEDED**, linha de diagnóstico aponta `timeRange` como causa provável | 1 linha de diagnóstico | **Sem PPE** |
| Nunca respondeu, ou mudou o formato da resposta | **FAILED**, exit code 1 | vazio | **Sem PPE** |

Drift de parser falha alto de propósito. Uma execução que volta vazia porque a API do HN renomeou um campo seria idêntica a "sua palavra-chave não tem resultado", e você pagaria o start da execução para descobrir isso meses depois.

A linha de diagnóstico da primeira situação sai assim:

```json
{
  "setup_status": "DIAGNOSTIC_GUIDE",
  "_dataQuality": "diagnostic",
  "_blockReason": "origin-confirmed-empty (HTTP 200, empty result set)",
  "message": "[DIAGNÓSTICO] Zero stories (mode=search) — Hacker News answered and has no matching story.",
  "potential_causes": [
    "The HN API answered normally and returned an empty result set for this query",
    "No Hacker News story matches [\"quantum yodelling compiler\"]"
  ],
  "remediations": [
    "Use a broader or differently spelled keyword (HN search matches title text, not synonyms)",
    "Try mode=\"front_page\" or mode=\"top_stories\" to confirm the actor reaches HN normally"
  ],
  "mode": "search",
  "searchQueries": ["quantum yodelling compiler"],
  "timeRange": "all",
  "sortBy": "relevance",
  "maxItems": 50,
  "recordsReturnedByOrigin": 0,
  "rawStoriesCollected": 0,
  "uniqueAfterDedup": 0,
  "dataSource": "hn-algolia + hn-firebase",
  "scrapedAt": "2026-08-27T14:15:22.108Z"
}
```

Filtre o dataset por `_dataQuality != "diagnostic"` e nenhuma linha de diagnóstico entra no seu pipeline.

### ❓ Perguntas Frequentes

**P: Este actor precisa de uma API key?**
R: Não. Ele usa a API pública Algolia HN Search e a API Firebase, ambas acessíveis livremente sem autenticação.

**P: Qual é a diferença entre os modos "front\_page" e "top\_stories"?**
R: "front\_page" retorna as stories atualmente exibidas na página inicial do Hacker News (cerca de 30 itens). "top\_stories" usa a lista canônica de top stories do Firebase, que pode retornar até 500 das stories ativas com melhor classificação.

**P: Habilitar comentários vai deixar o scraper mais lento?**
R: Sim. Cada story com comentários requer uma chamada API adicional. Para execuções grandes (100+ stories), espere tempos de execução significativamente maiores. Use `maxCommentsPerStory` para controlar o volume.

**P: Posso buscar várias palavras-chave em uma execução?**
R: Sim. O parâmetro `searchQueries` aceita até 10 palavras-chave. Resultados de todas as queries são deduplicados por story ID.

**P: Por que o actor retornou menos itens que maxItems?**
R: Menos stories corresponderam aos seus critérios. O actor deduplica por story ID e descarta títulos com menos de 3 caracteres.

**P: O que acontece numa execução que não encontra nenhuma story?**
R: O desfecho depende do que o Hacker News respondeu, e a execução nunca cobra PPE. Conjunto vazio confirmado pela API — inclusive quando o seu `timeRange` estreitou a busca, já que ele é enviado à API do HN como filtro `created_at` — termina SUCCEEDED com uma linha de diagnóstico; bloqueio (403/429/timeout) também. Falham as situações em que nada confirma o vazio: a API devolveu stories e o parser não extraiu nenhuma, a resposta veio com formato inesperado, ou a API nunca respondeu. Essas saem com exit code 1. Veja a tabela acima.

### 💰 Preços

Este actor usa precificação **Pay Per Event (PPE)**:

| Métrica | Custo |
|---------|-------|
| Por story extraída | $0.03 |

### 🔗 Actors Relacionados

- [Stack Overflow Intelligence](https://apify.com/viralanalyzer/stackoverflow-intelligence) — Perguntas e respostas do SO
- [GitHub Trending Scraper](https://apify.com/viralanalyzer/github-trending-scraper) — Repositórios em alta
- [Craigslist Scraper](https://apify.com/viralanalyzer/craigslist-scraper) — Classificados & anúncios
- [YouTube Fast Scraper](https://apify.com/viralanalyzer/youtube-fast-scraper) — Métricas do YouTube

### 📝 Changelog

#### v1.0 (Atual)

- ✅ 5 modos de scraping (search, front\_page, top\_stories, show\_hn, ask\_hn)
- ✅ Busca por palavra-chave com ordenação por relevância e data
- ✅ Filtragem por período (24h, semana, mês, ano, todos)
- ✅ Extração opcional de top comentários por story
- ✅ Suporte dual API (Algolia HN Search + Firebase)
- ✅ Deduplicação por story ID
- ✅ Guardrails anti-placeholder
- ✅ Lógica de retry com tratamento de rate limit
- ✅ Execução com zero stories classificada pelo status HTTP e pelo contêiner de registros observados: vazio-confirmado e bloqueio-confirmado terminam SUCCEEDED com linha de diagnóstico; drift de parser, API muda e filtro do usuário falham com exit code 1

# Actor input Schema

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

What data to collect.

## `searchQueries` (type: `array`):

Keywords to search for (only used in 'search' mode).

## `sortBy` (type: `string`):

How to sort search results.

## `timeRange` (type: `string`):

Filter stories by time period.

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

Maximum number of stories to scrape.

## `includeComments` (type: `boolean`):

Fetch top comments for each story (slower, more data).

## `maxCommentsPerStory` (type: `integer`):

Maximum comments to fetch per story.

## Actor input object example

```json
{
  "mode": "search",
  "searchQueries": [
    "AI startup",
    "machine learning"
  ],
  "sortBy": "relevance",
  "timeRange": "all",
  "maxItems": 50,
  "includeComments": false,
  "maxCommentsPerStory": 5
}
```

# Actor output Schema

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

Dataset containing all scraped results. Each item follows the dataset schema.

# 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 = {
    "searchQueries": [
        "AI startup",
        "machine learning"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("viralanalyzer/hackernews-intelligence").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 = { "searchQueries": [
        "AI startup",
        "machine learning",
    ] }

# Run the Actor and wait for it to finish
run = client.actor("viralanalyzer/hackernews-intelligence").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 '{
  "searchQueries": [
    "AI startup",
    "machine learning"
  ]
}' |
apify call viralanalyzer/hackernews-intelligence --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,viralanalyzer/hackernews-intelligence"
        }
    }
}

```

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/Zo9PrgWnd6wb7A1ja/builds/NvwAoBdULsu8vSxop/openapi.json