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