Olostep Web Data API for AI Agents & RAG Pipelines

Are you building agents that access Stack Overflow like your friend in a hoodie sitting in a dark room, staring at a glowing screen, wearing fancy headphones, and somehow always knowing the right answer?

Except… instead of a human, it’s your AI.

If yes, then you already know the problem: AI is only as good as the data it can access. And the web is messy, dynamic, JavaScript-heavy, and bot-protected, which is not exactly AI-friendly.

That’s where Olostep comes in.

What is Olostep (in plain English)?

Olostep is a Web Data API that enables your AI to effectively utilize the internet.

Not “trained-on-the-web-in-2023” internet but live, real, structured, up-to-date web data.

Instead of fighting with:

• Headless browsers
• Proxy rotation
• CAPTCHAs
• JavaScript rendering
• Brittle scrapers that break every two weeks

You send Olostep a URL (or a task), and it gives you back clean, usable data ready for:

• AI agents
• RAG pipelines
• Research automation
• Dashboards
• Lead enrichment
• Competitor tracking

Think of Olostep as:

“The data intern your AI deserves but one that never sleeps.”

What can Olostep do?

At a high level, Olostep offers APIs for:

• Scraping individual pages
• Crawling entire websites
• Mapping all URLs on a domain
• Batch processing thousands of URLs
• AI-powered web answers with sources
• Parsing unstructured content into JSON
• Agent-based automation using natural language

Basically:

If the data exists on the public web, Olostep can probably get it.

Core Concepts (Quick Tour)

Scrapes (“Give me this page”):

You pass a URL. Olostep returns the content in HTML, Markdown, or text format.

Perfect for:

• Blog posts
• Documentation
• Product pages
• Landing pages

Crawls (“Give me this whole site”)

You give a starting URL. Olostep recursively follows internal links and collects pages.

Great for:

• Docs ingestion
• Knowledge bases
• RAG pipelines
• Internal search engines

Batches (“Do this at scale”)

Have 1,000 to 10,000 URLs? Send them in one job and let Olostep handle concurrency.

Used for:

• Lead enrichment
• SEO audits
• Price monitoring
• Market research

Answers (“Search the web and explain it to me.”)

Instead of scraping first and prompting later, Olostep can:

• Search the web
• Read multiple sources
• Generate an AI answer
• Attach references

Perfect for:

• Research agents
• Analyst copilots
• Internal Q&A tools

Hands-On Activity (Python): Scrape a Web Page

import requests
API_KEY = "<YOUR_API_KEY>"
API_URL = "https://api.olostep.com/v1/scrapes"
headers = {
    "Authorization": f"Bearer {API_KEY}",
    "Content-Type": "application/json"
}
ppayload = {
    "url_to_scrape": "https://example.com"
}
response = requests.post(API_URL, headers=headers, json=payload)
data = response.json()
print(data["markdown_content"])

What’s happening here?

• Olostep loads the page (JS included)
• Extracts the content
• Returns it in a clean, AI-friendly format

Pros:

• No retries
• No IP blocked issues (Scalable)
• No Selenium

Hands-On Activity (Node.js): Ask the Web a Question (AI-Powered)

const API_KEY = "YOUR_API_KEY";
fetch("https://api.olostep.com/v1/answers", {
  method: "POST",
  headers: {
    "Authorization": `Bearer ${API_KEY}`,
    "Content-Type": "application/json"
  },
  body: JSON.stringify({
    task: "What are the biggest AI trends in 2026?",
    json: {
      trend: "",
      explanation: ""
    }
  })
})
  .then(res => res.json())
  .then(data => console.log(data))
  .catch(err => console.error(err));

Python SDK (Cleaner, Less Boilerplate)

If you don’t want to deal with raw HTTP calls, Olostep’s Python SDK makes life easier.

Installation

pip install olostep

Example: Simple Scrape

from olostep import Olostep
client = Olostep(api_key="YOUR_API_KEY")
result = client.scrapes.create(
    url_to_scrape="https://docs.olostep.com"
)
print(result.markdown_content)

Example: Crawl a Website

crawl = client.crawls.create(
    start_url="https://docs.olostep.com"
)
for page in crawl.pages():
    print(page.url)

When to use the SDK

• You’re building pipelines
• You want pagination handled automatically

Node SDK (Agent-Friendly & Async)

The Node SDK is ideal if you’re building:

• AI agents
• Backend services
• Serverless workflows

Installation

npm install olostep

Example: Scrape a Page

import { Olostep } from "olostep";
const client = new Olostep({
  apiKey: "YOUR_API_KEY"
});
const result = await client.scrapes.create({
  url_to_scrape: "https://example.com"
});
console.log(result.markdown_content);

Example: Batch URLs

const batch = await client.batches.create({
  items: [    { custom_id: "1", url: "https://site1.com" },
    { custom_id: "2", url: "https://site2.com" }
  ]
});
console.log(batch);

Why SDKs matter

• Less error-prone
• Easier retries
• Cleaner agent integration
• Faster prototyping

Supported Platforms

Olostep doesn’t care where your code lives: local machine, cloud, CI pipeline, or some mysterious server you SSH into once and never touch again.

If it can make HTTP requests, Olostep works there.

Programming Languages

Out of the box, Olostep supports:

• Python (For data pipelines, ML workflows, and RAG systems)
• Node.js / JavaScript (For backend services, agents, and serverless functions)

And if you’re using something else? No problem, Olostep is a plain HTTP API, so you can integrate it with:

• Go
• Java
• C#
• PHP
• Ruby
• Bash (yes, really)

Deployment Environments

Olostep works seamlessly across:

• Local development (Mac, Linux, Windows)
• Cloud servers (AWS, GCP, Azure, DigitalOcean)
• Serverless platforms (AWS Lambda, Vercel, Cloudflare Workers*)
• Docker & Kubernetes workloads
• CI/CD pipelines

If your app can reach the internet, it can reach Olostep.

AI & Agent Frameworks

Olostep fits naturally into modern AI stacks and agentic workflows, including:

• LangChain
• LlamaIndex
• Custom RAG pipelines
• Agent-based architectures
• Internal research copilots

It acts as the “web access layer”, the part that actually fetches reality before your LLM starts hallucinating.

Data Formats

Olostep speaks the formats your systems already understand:

• HTML (raw page content)
• Markdown (perfect for RAG ingestion)
• Plain text
• Structured JSON (via parsers or AI extraction)

Conclusion

Most AI systems today don’t fail because the models are bad; they fail because they’re blind to the real, live web.

• They hallucinate.
• They rely on stale knowledge.
• They guess instead of verifying.

Olostep fixes that by giving your AI what it’s been missing all along: reliable, structured, up-to-date access to the internet.

Whether you’re building:

• Agentic RAG systems,
• Research automation,
• Internal copilots,
• Lead enrichment pipelines,
• or large-scale web intelligence tools,

Olostep removes the painful parts of web data extraction, letting you focus on building intelligence instead of infrastructure.

• No brittle scrapers.
• No proxy chaos.
• No JavaScript nightmares.

Just clean data, delivered at scale exactly when your AI needs it. So if you want your AI to stop pretending it knows the web and actually use it, Olostep might just be the hoodie-wearing genius sitting quietly behind the scenes, only faster, scalable, and always online.