Scavio for Graph Memory + Search for Coding Agents

The Problem

Coding agents either forget context between sessions (no memory) or use stale training data (no search). The combination solves both.

How Scavio Helps

• Persistent memory across coding sessions
• Live web search for current documentation
• Graph structure captures code relationships
• Search fills gaps in training data
• Combined cost under $0.10/session

Relevant Platforms

Quick Start: Python Example

Here is a quick example searching Google for "prisma orm latest migration syntax":

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 Developers running long-term projects with AI coding assistants

Scavio handles the search infrastructure — proxies, CAPTCHAs, rate limits, and anti-bot detection — so you can focus on building your graph memory + search for coding agents 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.