# Hacker News Top Stories and Discussions Radar (`adaptive_nightmare/hacker-news-stories-radar`) Actor

Extract top, best, and newest Hacker News stories, point scores, author handles, comments counts, and article URLs in real time without proxies.

- **URL**: https://apify.com/adaptive_nightmare/hacker-news-stories-radar.md
- **Developed by:** [Darim Quraishi](https://apify.com/adaptive_nightmare) (community)
- **Categories:** News, Developer tools, Open source
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$0.85 / 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

## Hacker News Top Stories and Discussions Radar

Extract top, best, and new stories, point scores, submitter user profiles, comment counts, and outbound links from Hacker News in real time.

### Features

- Queries official Hacker News Firebase feeds for Top, Best, New, Ask HN, and Show HN submissions.
- Collects discussion point scores, total descendant comments, submission dates, and submitter usernames.
- Extracts clean outbound article URLs alongside root domains and permanent Y Combinator discussion threads.
- Runs via direct REST endpoints with zero headless browser overhead and zero proxy cost.
- Exports structured records directly to JSON, CSV, Excel, or API integrations.

### Input parameters

- Feed Category: Select between Top Stories, Best Stories, Newest Stories, Ask HN, or Show HN. Default is top.
- Maximum Stories: Number of stories to collect. Default is 50, maximum is 200.

### Output dataset fields

Each dataset record contains:

- id: Unique Hacker News numeric item identifier.
- title: Submission headline.
- url: Outbound link or self-post discussion link.
- domain: Clean root domain of the outbound link (for example: github.com, nytimes.com).
- by: Username of the submitting member.
- score: Community upvotes received.
- commentsCount: Total number of comments posted in the discussion thread.
- type: Item type such as story, job, or poll.
- storyType: Feed category requested.
- hnUrl: Direct permanent link to the discussion thread on news.ycombinator.com.
- publishedAt: ISO formatted UTC submission timestamp.
- scrapedAt: UTC timestamp when the data was extracted.

### Use cases

- Tech news aggregation: Feed fresh high-signal tech discussions into internal Slack channels or newsletters.
- AI topic modeling: Feed trending developer discussions into language models for sentiment and topic analysis.
- Developer relations monitoring: Track when open source projects or company products reach the Hacker News frontpage.
- Competitive intelligence: Discover new startups and emerging technical tools shared in Show HN threads.

# Actor input Schema

## `storyType` (type: `string`):

Hacker News story list to extract.

## `maxStories` (type: `integer`):

Maximum number of story items to fetch and store.

## Actor input object example

```json
{
  "storyType": "top",
  "maxStories": 50
}
```

# 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 = {};

// Run the Actor and wait for it to finish
const run = await client.actor("adaptive_nightmare/hacker-news-stories-radar").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("adaptive_nightmare/hacker-news-stories-radar").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 '{}' |
apify call adaptive_nightmare/hacker-news-stories-radar --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,adaptive_nightmare/hacker-news-stories-radar"
        }
    }
}
```

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/3C6CXdwIyHjFd0BBm/builds/bnNNvWtdKCOJAwRe2/openapi.json