The Problem
Google Custom Search Engine (CSE) has been the default embedded search solution for many websites and applications since 2010. In 2026, Google's pricing changes and tighter rate limits are pushing teams to find alternatives. But CSE is deeply integrated into existing codebases: search forms, result rendering, pagination logic, and analytics all assume CSE's response format. A full rewrite is too expensive. Teams need a drop-in replacement that requires minimal code changes.
The Scavio Solution
Replace Google CSE API calls with Scavio's Google search endpoint. The response structure is similar enough that a thin adapter layer handles the mapping. Search query parameters, result fields (title, link, snippet), and pagination translate directly. Most teams complete the migration in under a day with fewer than 50 lines of adapter code.
Before
Before: A SaaS product used Google CSE for its in-app search feature. Google raised CSE pricing and the $100/mo bill was projected to hit $300/mo at current growth. Rewriting the search integration was estimated at 2 weeks of engineering time. The team delayed the migration for 3 months while costs climbed.
After
After: The team wrote a 40-line adapter that maps Scavio's response format to their existing CSE response handler. Migration took 4 hours. Monthly cost dropped from $300/mo to $30/mo (7K credits). Search quality improved because Scavio returns AI Overview and Knowledge Graph data that CSE did not include.
Who It Is For
Engineering teams running Google CSE integrations facing pricing increases or rate limit changes. Anyone needing to migrate off CSE with minimal code changes.
Key Benefits
- Migrate from Google CSE in under a day with a thin adapter layer
- Drop monthly search costs from $100-300/mo to $30/mo
- Get AI Overview and Knowledge Graph data CSE never provided
- Fewer than 50 lines of adapter code for most integrations
- No changes to existing search UI or result rendering logic
Python Example
import requests
API_KEY = "your_scavio_api_key"
def cse_compatible_search(query: str, start: int = 1, num: int = 10) -> dict:
"""Drop-in replacement for Google CSE API calls.
Returns a response shaped like CSE for minimal migration.
"""
r = requests.post(
"https://api.scavio.dev/api/v1/search",
headers={"x-api-key": API_KEY},
json={"platform": "google", "query": query},
timeout=10,
)
data = r.json()
organic = data.get("organic", [])
# Map to CSE-compatible response shape
return {
"queries": {"request": [{"totalResults": str(len(organic)), "searchTerms": query}]},
"items": [{
"title": item.get("title", ""),
"link": item.get("link", ""),
"snippet": item.get("snippet", ""),
"displayLink": item.get("link", "").split("/")[2] if item.get("link") else "",
} for item in organic[start-1:start-1+num]],
}
# Existing CSE consumer code works with minimal changes
results = cse_compatible_search("machine learning frameworks 2026")
for item in results["items"]:
print(f"{item["title"]}\n {item["link"]}")JavaScript Example
const API_KEY = "your_scavio_api_key";
async function cseCompatibleSearch(query, start = 1, num = 10) {
const res = await fetch("https://api.scavio.dev/api/v1/search", {
method: "POST",
headers: { "x-api-key": API_KEY, "content-type": "application/json" },
body: JSON.stringify({ platform: "google", query }),
});
const data = await res.json();
const organic = data.organic || [];
// Map to CSE-compatible response shape
return {
queries: { request: [{ totalResults: String(organic.length), searchTerms: query }] },
items: organic.slice(start - 1, start - 1 + num).map(item => ({
title: item.title || "",
link: item.link || "",
snippet: item.snippet || "",
displayLink: item.link ? new URL(item.link).hostname : "",
})),
};
}
// Existing CSE consumer code works with minimal changes
const results = await cseCompatibleSearch("machine learning frameworks 2026");
for (const item of results.items) {
console.log(`${item.title}\n ${item.link}`);
}Platforms Used
Web search with knowledge graph, PAA, and AI overviews