Scavio for Vercel AI SDK Agent with Live Search

The Problem

Vercel AI SDK's tool-calling pattern wants a typed response. Scavio's organic_results + ai_overview + knowledge_graph shape maps cleanly. The wrapper is one file in lib/tools/scavio.ts.

How Scavio Helps

• Edge-runtime friendly
• 30-line tool wrapper
• Multi-surface from one key
• Plain fetch() — no SDK
• Free 500 credits/mo for prototyping

Relevant Platforms

Quick Start: Python Example

Here is a quick example searching Google for "add live web search to an AI SDK chatbot":

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 Vercel-first builders, Next.js + AI SDK developers, edge-runtime teams

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

Start with the free tier (500 credits/month, no credit card required) and scale to paid plans when you need higher volume.