Scavio for Firebase Genkit Search Integration

The Problem

Firebase Genkit's built-in search grounding requires Vertex AI (enterprise pricing and Google Cloud setup), leaving developers without an affordable, simple web search tool for Genkit flows.

How Scavio Helps

• Genkit tool definition in under 20 lines of code
• Works with any Genkit-supported model
• No Vertex AI or Google Cloud setup required
• Free 250 queries/month covers development
• Structured JSON maps to Genkit tool output format

Relevant Platforms

Quick Start: Python Example

Here is a quick example searching Google for "Firebase Genkit search grounding tool API integration 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 Firebase Genkit developers, Node.js and Go engineers building AI features, and teams avoiding Vertex AI overhead

Scavio handles the search infrastructure — proxies, CAPTCHAs, rate limits, and anti-bot detection — so you can focus on building your firebase genkit search integration 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.