AI Web Search & RAG Markdown Scraper (Live SERP)
Pricing
from $20.00 / 1,000 ai web search & rag grounding queries
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
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Neon Innovation Lab
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AI Search & RAG Scraper (Clean Markdown Context for LLMs)
โก Run directly on Apify Cloud: AI Search & RAG Scraper
๐ 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.
โก 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:
- RAG-Formatted Markdown: Generates clean Markdown snippets with semantic headings and source links designed to minimize prompt tokens.
- Sub-2-Second Latency: Uses lightweight asynchronous request pools that return organic search results in under 2 seconds.
- No External API Keys: Zero requirement for Google Custom Search or Bing API keys.
- Agent Framework Support: Drop-in compatible with LangChain, LlamaIndex, AutoGen, CrewAI, and Model Context Protocol (MCP) servers.
๐ Feature & Competitor Comparison Matrix
| Feature | AI Search RAG Scraper (This Actor) | Google Custom Search API | SerpAPI | Tavily / Exa |
|---|---|---|---|---|
| Pre-Formatted Markdown for Prompts | โ Instant RAG blocks | โ Raw JSON only | โ Raw JSON only | โ ๏ธ Partial |
| API Key Setup Required | โ None (run via Apify) | โ ๏ธ Complex GCP billing | โ ๏ธ Requires paid key | โ ๏ธ Requires paid key |
| Sub-2-Second Latency | โ Lightweight workers | โ Fast | โ ๏ธ 3โ5 seconds | โ Fast |
| Monthly Subscription Required | โ $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 |
๐ฐ Transparent Pricing Breakdown
| Event | Price (USD) | When Charged |
|---|---|---|
apify-actor-start | $0.03 | Charged once when Actor starts running. |
apify-default-dataset-item | $0.0015 | Charged automatically per organic result written to dataset ($1.50 / 1k results). |
query-searched | $0.003 | Charged for successful organic search and RAG markdown generation. |
| Total Effective Price | $4.53 per 1,000 queries | Predictable micropayments. Zero subscriptions. |
๐ป Python & Node.js SDK Examples
Python (apify-client + LangChain RAG)
$pip install apify-client
import osfrom apify_client import ApifyClientclient = 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 blocksrun = 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).