Scavio for LangChain DaaS Agent Architecture

The Problem

Real-time scraping in LangChain agents is brittle and expensive. The async DaaS pattern (Scavio dorks → /extract → Llama-3 transform → SQLite cache → MCP serve) is robust and cheap. Sub-50ms repeat reads; weekly maintenance near zero.

How Scavio Helps

• 50ms cache reads
• MCP-served typed JSON for downstream agents
• PDF support via /extract
• No live-scraping fragility
• Scales to multiple LangChain crews

Relevant Platforms

Quick Start: Python Example

Here is a quick example searching Google for "site:gov.br filetype:pdf 2026 contratos":

import requests

API_KEY = "your_scavio_api_key"

response = requests.post(
    "https://api.scavio.dev/api/v1/search",
    headers={
        "x-api-key": API_KEY,
        "Content-Type": "application/json",
    },
    json={"query": query},
)

data = response.json()
for result in data.get("organic_results", [])[:5]:
    print(f"{result['position']}. {result['title']}")
    print(f"   {result['link']}\n")

Built for LangChain teams building DaaS agents, CrewAI builders, government-data SDRs, compliance research teams

Scavio handles the search infrastructure — proxies, CAPTCHAs, rate limits, and anti-bot detection — so you can focus on building your langchain daas agent architecture solution. The API returns structured JSON that is ready for processing, analysis, or feeding into AI agents.

Start with the free tier (50 credits on signup, no credit card required) and scale to paid plans when you need higher volume.