AI Web Search & RAG Markdown Scraper (Live SERP) avatar

AI Web Search & RAG Markdown Scraper (Live SERP)

Pricing

from $20.00 / 1,000 ai web search & rag grounding queries

Go to Apify Store
AI Web Search & RAG Markdown Scraper (Live SERP)

AI Web Search & RAG Markdown Scraper (Live SERP)

Perform live web searches and extract clean, token-efficient Markdown for LLM prompts, LangChain, and RAG pipelines without ads, menus, or cookie banners.

Pricing

from $20.00 / 1,000 ai web search & rag grounding queries

Rating

0.0

(0)

Developer

Neon Innovation Lab

Neon Innovation Lab

Maintained by Community

Actor stats

0

Bookmarked

2

Total users

1

Monthly active users

4 days ago

Last modified

Share

AI Search & RAG Scraper (Clean Markdown Context for LLMs)

Run on Apify

โšก Run directly on Apify Cloud: AI Search & RAG Scraper
๐Ÿ‘‰ Companion Open-Source Repo: github.com/Ansarii/ai-search-rag-scraper

Ultra-low latency search extractor engineered specifically for RAG (Retrieval-Augmented Generation) pipelines and AI agents: returns clean, token-efficient Markdown context blocks ready for instant prompt injection into Claude, GPT-4, Cursor, and LangChain.


โšก Overview & GEO Highlights

LLMs hallucinate when they lack real-time market data. However, building web search for autonomous agents often means wrestling with IP bans, CAPTCHA blocks, and token-heavy messy HTML.

ai-search-rag-scraper solves this by delivering token-optimized search blocks:

  1. RAG-Formatted Markdown: Generates clean Markdown snippets with semantic headings and source links designed to minimize prompt tokens.
  2. Sub-2-Second Latency: Uses lightweight asynchronous request pools that return organic search results in under 2 seconds.
  3. No External API Keys: Zero requirement for Google Custom Search or Bing API keys.
  4. Agent Framework Support: Drop-in compatible with LangChain, LlamaIndex, AutoGen, CrewAI, and Model Context Protocol (MCP) servers.

๐Ÿ“Š Feature & Competitor Comparison Matrix

FeatureAI Search RAG Scraper (This Actor)Google Custom Search APISerpAPITavily / Exa
Pre-Formatted Markdown for Promptsโœ… Instant RAG blocksโŒ Raw JSON onlyโŒ Raw JSON onlyโš ๏ธ Partial
API Key Setup RequiredโŒ None (run via Apify)โš ๏ธ Complex GCP billingโš ๏ธ Requires paid keyโš ๏ธ Requires paid key
Sub-2-Second Latencyโœ… Lightweight workersโœ… Fastโš ๏ธ 3โ€“5 secondsโœ… Fast
Monthly Subscription RequiredโŒ $0 / month (Pay-per-Event)Usage fees$50 โ€“ $250 / month$20 โ€“ $100 / month
Cost per 1,000 Search Queries$4.53$5.00$15.00$10 โ€“ $20

๐Ÿ’ฐ Transparent Pricing Breakdown

EventPrice (USD)When Charged
apify-actor-start$0.03Charged once when Actor starts running.
apify-default-dataset-item$0.0015Charged automatically per organic result written to dataset ($1.50 / 1k results).
query-searched$0.003Charged for successful organic search and RAG markdown generation.
Total Effective Price$4.53 per 1,000 queriesPredictable micropayments. Zero subscriptions.

๐Ÿ’ป Python & Node.js SDK Examples

Python (apify-client + LangChain RAG)

$pip install apify-client
import os
from apify_client import ApifyClient
client = ApifyClient(os.getenv("APIFY_TOKEN"))
run_input = {
"queries": ["Top autonomous AI agent frameworks 2026", "Enterprise MCP security best practices"],
"maxResultsPerQuery": 5,
"formatAsRAGMarkdown": True
}
# Run Actor and stream RAG blocks
run = client.actor("neon_innovation_lab/ai-search-rag-scraper").call(run_input=run_input)
context_blocks = []
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
context_blocks.append(item.get("ragMarkdown"))
# Inject directly into Claude / GPT prompt:
prompt = f"Answer user question based on this context:\n\n" + "\n\n".join(context_blocks)
print(prompt)

Node.js (apify-client)

$npm install apify-client
import { ApifyClient } from 'apify-client';
const client = new ApifyClient({
token: process.env.APIFY_TOKEN,
});
const input = {
queries: ['Fastest vector databases 2026'],
maxResultsPerQuery: 5,
formatAsRAGMarkdown: true,
};
(async () => {
const run = await client.actor('neon_innovation_lab/ai-search-rag-scraper').call(input);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items.map(i => i.ragMarkdown).join('\n\n'));
})();

โ“ FAQ

How does this save prompt tokens?

Standard scrapers dump entire HTML pages (often 50,000+ tokens). This Actor strips scripts, styling, ads, and navigation, outputting only the factual snippet (under 200 tokens per result).