Scavio for Combined Memory and Search Agent Grounding

The Problem

Agents with only memory eventually drift as stored facts become outdated. Agents with only search re-discover known information every session, wasting tokens and time. Neither alone provides reliable grounding.

How Scavio Helps

• Memory stores verified facts to avoid re-searching
• Search validates and updates stale memory entries
• Reduces token waste from redundant searches
• Catches when remembered facts become outdated
• Works with MCP memory servers and search tools together

Relevant Platforms

Quick Start: Python Example

Here is a quick example searching Google for "Agent remembers that Tavily pricing is $30/mo (stored 3 months ago). When user asks about Tavily pricing, agent searches Google to verify. Finds that Nebius acquired Tavily in February 2026 and pricing page changed. Updates memory with current pricing. Next time the question comes up, memory is already current. Search only fires when confidence is low or memory is older than 30 days.":

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 Agent builders, Claude Code power users, teams building long-running autonomous agents

Scavio handles the search infrastructure — proxies, CAPTCHAs, rate limits, and anti-bot detection — so you can focus on building your combined memory and search agent grounding 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.