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Oaida Adrian
Oaida Adrian

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5 APIs Every Developer Needs for Content Processing (RSS, Extraction, Sitemaps, AI)

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5 APIs Every Developer Needs for Content Processing

Every developer who has built a content-driven application knows the pain: you need RSS feeds parsed, web pages extracted cleanly, sitemaps crawled, structured data generated for AI crawlers, and sometimes local business data — all in the same project. Traditionally, that meant juggling five different libraries, each with its own quirks, rate limits, and failure modes.

What if you could replace all of them with a single API?

In this tutorial, I'll walk you through five real-world use cases using the Multi-Tool Content API on RapidAPI — one endpoint per problem, with copy-paste Python code for each.

Why a Multi-Tool Content API?

Content processing pipelines share common infrastructure needs:

  • Reliable HTTP fetching with proper headers and redirects
  • HTML/XML parsing that handles malformed markup gracefully
  • Structured output (JSON) instead of raw blobs
  • Rate limiting and error handling that doesn't break your app

Instead of bolting together feedparser, BeautifulSoup, requests-HTML, xmltodict, and a scraping framework, the Multi-Tool Content API provides all five capabilities behind a single REST interface with consistent request/response schemas.

Available on: RapidAPI · Apify

1. RSS Feed Parsing

Whether you're building a news aggregator, a monitoring dashboard, or a content curation tool, RSS parsing is often the first step. The Multi-Tool Content API handles feed discovery, XML parsing, and item normalisation in a single call.

Code Example 

import requests

url = "https://multi-tool-content.p.rapidapi.com/rss/parse"
headers = {
    "X-RapidAPI-Key": "YOUR_RAPIDAPI_KEY",
    "X-RapidAPI-Host": "multi-tool-content.p.rapidapi.com",
    "Content-Type": "application/json"
}
payload = {
    "feed_url": "https://feeds.feedburner.com/TheHackersNews",
    "max_items": 10
}
response = requests.post(url, json=payload, headers=headers)
print(response.json())
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What You Get

The response includes normalised feed metadata (title, description, link) and an array of items, each with title, link, pub_date, description, and guid. No more dealing with RSS 2.0 vs Atom format differences — the API handles that for you.

Use cases: News aggregators, content monitoring, social media auto-posting, newsletter generation.

2. Content Extraction

Need the clean text content of a web page without the navigation, ads, sidebars, and footer noise? The extraction endpoint strips away everything except the main article content — perfect for RAG pipelines, readability views, or archival.

Code Example 

import requests

url = "https://multi-tool-content.p.rapidapi.com/content/extract"
headers = {
    "X-RapidAPI-Key": "YOUR_RAPIDAPI_KEY",
    "X-RapidAPI-Host": "multi-tool-content.p.rapidapi.com",
    "Content-Type": "application/json"
}
payload = {
    "url": "https://blog.python.org/2024/12/python-3131-released.html"
}
response = requests.post(url, json=payload, headers=headers)
print(response.json())
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What You Get

The response returns the extracted title, content (clean HTML), text (plain text), author, published_date, and excerpt. This is ideal for feeding into LLMs, building search indexes, or creating reader-mode views.

Use cases: Content summarisation, RAG (Retrieval-Augmented Generation), SEO analysis, full-text search indexing.

3. Sitemap Crawling

Sitemaps are the most efficient way to discover all URLs on a website. Whether you're building a SEO auditor, a content migration tool, or a competitive analysis platform, the sitemap crawler handles XML parsing, nested sitemap indexes, and URL filtering.

Code Example 

import requests

url = "https://multi-tool-content.p.rapidapi.com/sitemap/crawl"
headers = {
    "X-RapidAPI-Key": "YOUR_RAPIDAPI_KEY",
    "X-RapidAPI-Host": "multi-tool-content.p.rapidapi.com",
    "Content-Type": "application/json"
}
payload = {
    "sitemap_url": "https://example.com/sitemap.xml",
    "max_urls": 100
}
response = requests.post(url, json=payload, headers=headers)
print(response.json())
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What You Get

A structured list of URLs with loc, lastmod, changefreq, and priority fields. The endpoint follows sitemap index references automatically, so you get every URL on the site without writing recursion logic.

Use cases: SEO auditing, content discovery, broken link checking, competitive intelligence.

4. LLMs.txt Generation

If you're building for the AI era, you need llms.txt — the emerging standard for making your content accessible to AI crawlers and agents. Think of it as robots.txt but for LLMs. This endpoint analyses your site and generates an optimised llms.txt file automatically.

Code Example 

import requests

url = "https://multi-tool-content.p.rapidapi.com/llms-txt/generate"
headers = {
    "X-RapidAPI-Key": "YOUR_RAPIDAPI_KEY",
    "X-RapidAPI-Host": "multi-tool-content.p.rapidapi.com",
    "Content-Type": "application/json"
}
payload = {
    "url": "https://docs.python.org/3/"
}
response = requests.post(url, json=payload, headers=headers)
print(response.json())
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What You Get

The response includes the generated llms.txt content with structured sections for your project's title, description, documentation links, and API references. Drop it at the root of your domain and AI crawlers will index your content intelligently.

Use cases: AI-friendly documentation sites, improving LLM discoverability, content marketing for AI search engines.

5. Romanian Business Search

If you're building apps for the Romanian market — directories, lead generation, market analysis — the Romanian Business Search endpoint provides structured company data from Romanian business registries.

Code Example 

import requests

url = "https://multi-tool-content.p.rapidapi.com/ro-businesses/search"
headers = {
    "X-RapidAPI-Key": "YOUR_RAPIDAPI_KEY",
    "X-RapidAPI-Host": "multi-tool-content.p.rapidapi.com",
    "Content-Type": "application/json"
}
payload = {
    "query": "coffeeshop",
    "location": "Bucuresti",
    "limit": 20
}
response = requests.post(url, json=payload, headers=headers)
print(response.json())
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What You Get

Structured business listings with name, address, phone, website, category, and rating data. Perfect for building local business directories, lead lists, or market research dashboards.

Use cases: Lead generation, market research, local SEO tools, business directory apps.

Pricing

The Multi-Tool Content API is designed to be accessible for developers at every stage:

Plan Price Requests/Month
Free $0 100
Basic $10/mo 5,000
Pro $29/mo 25,000

The Free tier gives you 100 requests per month — enough to prototype all five endpoints and build a proof of concept. The Basic plan ($10/mo) covers most personal projects and small applications, while Pro ($29/mo) is designed for production workloads.

Available Platforms

RapidAPI

The Multi-Tool Content API is available on RapidAPI:

🔗 https://rapidapi.com/oaidaadrian/api/multi-tool-content

RapidAPI provides a clean dashboard, usage analytics, and automatic key management. Subscribe to any plan and get instant access to all five endpoints.

Apify

Prefer the Apify ecosystem? Each tool is also available as standalone Apify actors with the same functionality:

🔗 https://apify.com/darknezz

Apify actors are ideal if you need scheduling, proxy rotation, or integration with Apify's storage and webhooks.

Putting It All Together

Here's a real-world pipeline that combines multiple endpoints:

import requests

BASE_URL = "https://multi-tool-content.p.rapidapi.com"
HEADERS = {
    "X-RapidAPI-Key": "YOUR_RAPIDAPI_KEY",
    "X-RapidAPI-Host": "multi-tool-content.p.rapidapi.com",
    "Content-Type": "application/json"
}

def parse_rss(feed_url, max_items=10):
    r = requests.post(f"{BASE_URL}/rss/parse", json={"feed_url": feed_url, "max_items": max_items}, headers=HEADERS)
    return r.json()

def extract_content(url):
    r = requests.post(f"{BASE_URL}/content/extract", json={"url": url}, headers=HEADERS)
    return r.json()

def crawl_sitemap(sitemap_url, max_urls=100):
    r = requests.post(f"{BASE_URL}/sitemap/crawl", json={"sitemap_url": sitemap_url, "max_urls": max_urls}, headers=HEADERS)
    return r.json()

# Pipeline: Parse RSS → Extract full content from each article
feed = parse_rss("https://feeds.feedburner.com/TheHackersNews", max_items=5)
for item in feed.get("items", []):
    article = extract_content(item["link"])
    print(f"Extracted: {article.get('title', 'Unknown')}")
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This pattern — RSS → Extract → Store → Analyse — is the backbone of news aggregators, content monitoring tools, and AI-powered research assistants.

Conclusion

Content processing doesn't have to be a patchwork of libraries. With five well-designed endpoints, you can build RSS aggregators, content extractors, SEO crawlers, AI-readiness tools, and local business directories — all from a single API with consistent authentication and response formats.

Start building: RapidAPI · Apify

The free tier gives you 100 requests to prototype everything. Upgrade when you're ready for production.

Happy building! 🚀

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