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🚀 DESIGNED FOR MODERN DATA ARCHITECTS

Why Your Team Needs FlyCrawl
Purpose-Built for AI, SEO, GEO & Engineering

From RAG pipelines and autonomous AI agents to modern Technical SEO audits, Generative Engine Optimization (GEO), and high-scale market intelligence — FlyCrawl turns the raw, chaotic web into clean, token-efficient Fit-Markdown and structured JSON.

🤖

For AI Engineers & LLM Developers

RAG Ingestion • Agent Tool Calling • Structured JSON Extraction • Fit-Markdown Compression

The Traditional Nightmare
  • • Bloated raw HTML burns 100k+ LLM tokens per webpage, exploding OpenAI/Claude bills.
  • • Noisy scripts, navbars, and cookie modals cause severe LLM hallucinations in RAG.
  • • Headless Chromium browsers leak memory and crash under high concurrent scraping loads.
How FlyCrawl Solves It
  • Fit-Markdown: Cleans noise, strip tags, and strips 95% of useless tokens while preserving semantic headers and tables.
  • Schema-Driven Extraction: Extract strongly-typed JSON data matching your exact Pydantic / TypeScript schema.
  • MCP & Agent Ready: Plug directly into Cursor, LangChain, LlamaIndex, and Claude Desktop via native MCP protocol.

💡 AI Workflow: From Complex Web to Vector DB in 3 Steps

1. Scrape & Crawl
FlyCrawl extracts pages into clean Fit-Markdown
2. Chunk & Embed
Zero token waste, high semantic density
3. Vector Store & RAG
Pinecone / Qdrant / Chroma query with 0 hallucination
🐍 Python RAG Pipeline Ingestion Example
import requests

# 1. Fetch token-optimized Fit-Markdown with FlyCrawl API
response = requests.post(
    "https://api.flycrawl.net/api/v1/scrape",
    headers={"Authorization": "Bearer fly_live_your_key"},
    json={
        "url": "https://docs.example.com/api-reference",
        "format": "markdown",
        "onlyMainContent": True
    }
)
clean_markdown = response.json().get("data", {}).get("markdown")

# 2. Feed directly into LangChain / LlamaIndex Vector Store
from langchain_core.documents import Document
doc = Document(page_content=clean_markdown, metadata={"source": "https://docs.example.com"})
# 95% fewer tokens = instant embeddings & zero hallucinations
💰 INTERACTIVE ROI CALCULATOR

See How Much You Save on LLM Token Costs

Compare raw bloated HTML token consumption versus FlyCrawl token-optimized Fit-Markdown on OpenAI GPT-4o & Claude 3.5 Sonnet.

Estimated Monthly LLM Token Cost Savings
$2,185 / mo
Raw HTML Cost
$2,300
FlyCrawl Cost
$115
95% Token Reduction + Zero Memory Leaks
🚨 CONTINUOUS CRAWLER ENHANCEMENT

Found a Website That Failed to Scrape?

Log into your account and submit the target link! Our crawler engineers inspect the anti-bot defenses, JS hydration bottlenecks, or encoding quirks and patch the scraping core within 24 hours.

🚀 Report Unscrapable Site
❓ FAQ

Frequently Asked Questions

How does FlyCrawl handle Cloudflare Turnstile and anti-bot protection?

FlyCrawl utilizes an automated residential IP proxy pool, dynamic TLS fingerprint emulation, and stealth header randomization. It executes realistic browser mouse movements and timing to bypass Cloudflare Turnstile, DataDome, and Akamai without requiring user intervention.

Can I extract structured JSON data using a custom schema?

Yes! Use our /api/v1/extract endpoint and provide your JSON Schema. FlyCrawl will parse the webpage and extract exact key-value pairs (e.g. product price, author, publication date, specs) validated against your schema.

How does FlyCrawl's MCP Server work with Cursor and Claude Desktop?

The Model Context Protocol (MCP) server allows AI agents in Cursor, Windsurf, and Claude Desktop to execute live web searches and scrape up-to-date documentation directly into your coding context using your FlyCrawl API key.

Is KYC verification required to purchase crawl credits?

No KYC is ever required. FlyCrawl supports instant anonymous cryptocurrency payments via USDT (TRC-20), TON, and TRX with automated on-chain confirmation in under 30 seconds.

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