Scavio for Deep Research Grounding

The Problem

Deep research agents produce plausible but unverifiable reports because they lack structured access to current web data for real-time fact-checking and source validation.

How Scavio Helps

• Real-time web results ground agent claims in current data
• Source URLs enable proper citation in generated reports
• Multi-platform cross-referencing reduces single-source bias
• MCP interface at mcp.scavio.dev/mcp integrates with agent frameworks
• 250 free credits to prototype grounding pipelines

Relevant Platforms

Quick Start: Python Example

Here is a quick example searching Google for "latest AI regulation EU AI Act enforcement 2026":

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 AI researchers and teams building deep research agent systems

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

Start with the free tier (250 credits/month, no credit card required) and scale to paid plans when you need higher volume.