Seeking Alpha Articles Scraper

Scrape public Seeking Alpha article URLs and RSS feeds into structured records for financial-news monitoring, market research, and AI agents.

Extracted fields

Field	Description
url, canonicalUrl, articleId	Article identity and canonical public URL
title, description, summary	Public article metadata and summary
author, authorUrl	Author metadata when published
publishedAt, modifiedAt	Source publication timestamps
symbols, categories	Symbols and article taxonomy found in structured data or RSS
imageUrls	Public article image URLs
headings, content	Accessible page headings and text, when enabled
isAccessibleForFree	Source-declared free-access flag

Input

Use public article URLs, RSS feed URLs, or both. If no source is supplied, the actor uses Seeking Alpha’s public all-articles RSS feed.

{
  "articleUrls": [{"url": "https://seekingalpha.com/article/4938616-lowes-the-retailer-to-watch-and-wait-even-as-q2-results-saw-growth-rating-downgrade"}],
  "rssFeedUrls": [{"url": "https://seekingalpha.com/feed.xml"}],
  "maxResults": 10,
  "includeContent": true,
  "requestDelayMs": 500
}

Output and pricing

Each validated article is one default-dataset item and one primary apify-default-dataset-item event at $0.004. A small actor-start event is $0.00005. The OUTPUT key-value record contains status, counts, warnings, and expected result-event count.

The actor uses public page and RSS responses only. It does not log in, use subscriber cookies, bypass paywalls, solve CAPTCHAs, or defeat access controls. If a page is blocked or exposes only limited public content, the run reports that condition in OUTPUT and item warnings.

Legal note

Use this actor only for data you are allowed to access and process. Respect Seeking Alpha’s Terms of Use, RSS restrictions, robots directives, copyright, and applicable laws. The RSS feed itself notes that its use is limited to personal, non-commercial use.

Use cases

• Monitor public articles and build research or alerting datasets.
• Run a one-off research job and export the structured result as JSON, CSV, Excel, XML, or RSS from Apify.
• Schedule the same input to monitor changes over time and send completed datasets to a webhook or integration.
• Feed schema-shaped records into a database, spreadsheet, BI tool, or AI workflow with the source URL retained for verification.

Run Seeking Alpha Articles Scraper with the Apify API

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('muhammadafzal/seeking-alpha-articles-scraper').call({
  "articleUrls": [],
  "rssFeedUrls": [
    {
      "url": "https://seekingalpha.com/feed.xml"
    }
  ],
  "maxResults": 10,
  "includeContent": true,
  "requestDelayMs": 500
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

You can also run the Actor from Apify Console, schedules, webhooks, the REST API, Make, Zapier, n8n, or the hosted Apify MCP server.

Support

When reporting a problem, include the Actor run ID, a redacted input, the expected result, and a small public example URL when applicable. Do not post API tokens, cookies, credentials, or personal data in an issue.

Frequently asked questions

Can I schedule Seeking Alpha Articles Scraper?

Yes. Use an Apify schedule to run the same saved input at a chosen interval, then connect a webhook or integration to process the dataset when the run finishes.

How should I test a new input?

Begin with the prefilled example or a small limit. Confirm that the output fields, source coverage, runtime, and live charges match your workflow before increasing the scope.

How do I export the results?

Open the run's default dataset in Apify Console and export JSON, CSV, Excel, XML, or RSS. Applications can retrieve the same records through the Apify API client or REST dataset endpoint.

Can an AI agent call this Actor?

Yes. Add muhammadafzal/seeking-alpha-articles-scraper through the hosted Apify MCP server or call it through the API. The Actor's input and dataset schemas help agents construct valid requests and interpret returned records.

Recommended workflow

1. Define the smallest useful scope. Choose a representative public URL, query, identifier, or filter and keep the first result limit low.
2. Run and inspect. Check the run log, dataset item count, field coverage, source URLs, and live event or usage charges.
3. Validate downstream assumptions. Confirm nullable fields, deduplication keys, timestamps, and any locale-specific formats before importing records into another system.
4. Scale gradually. Increase limits or scheduling frequency only after the small run behaves as expected. Use Apify's maximum-cost and timeout controls to bound large jobs.
5. Monitor changes. Keep a small known-good input as a canary. If the source layout or API changes, compare the new dataset with a previously validated run and report the run ID when requesting support.

For recurring workflows, store the exact Actor input with your pipeline configuration. This makes runs reproducible and helps distinguish a source-data change from an input change.