The Problem
Multi-agent systems with 3-5 agents all making search calls create unpredictable search API usage. Each agent manages its own search connection, leading to duplicated queries, no caching, no budget controls, and no failover. A single search provider outage cascades to all agents simultaneously.
The Scavio Solution
Deploy an MCP search gateway that all agents connect to. The gateway exposes a single 'search' tool via MCP protocol, handles provider failover internally, caches recent results to prevent duplicate queries, and enforces budget limits across all agents. Scavio serves as the primary provider at mcp.scavio.dev/mcp.
Before
Before the gateway, 4 agents each had their own Scavio connection. Two agents searching the same keyword within 5 minutes made duplicate queries. No global budget control existed. When the team exceeded 7K monthly credits, all 4 agents failed simultaneously.
After
After deploying the gateway, duplicate queries are cached (30% query reduction). Budget is managed centrally with per-agent limits and alerts. Failover to Brave handles any provider issues transparently. Monthly query count dropped from 9,200 to 6,400 through deduplication.
Who It Is For
Teams running multi-agent systems that all need search access. Platform teams providing search infrastructure to multiple agent projects. SREs building reliable agent search infrastructure.
Key Benefits
- Centralized search for all agents through one MCP endpoint
- Result caching reduces duplicate queries by 20-30%
- Global budget controls prevent credit exhaustion
- Automatic failover transparent to all connected agents
- Per-agent usage tracking for cost allocation
Python Example
import requests
import json
import time
from functools import lru_cache
SCAVIO_KEY = "your_scavio_api_key"
BRAVE_KEY = "your_brave_api_key"
DAILY_BUDGET = 500 # queries
query_count = 0
@lru_cache(maxsize=1000)
def cached_search(query: str, platform: str) -> str:
"""Cache search results for 30 minutes."""
return json.dumps(_do_search(query, platform))
def _do_search(query: str, platform: str) -> dict:
global query_count
if query_count >= DAILY_BUDGET:
return {"error": "Daily budget exceeded", "results": []}
# Primary: Scavio
try:
res = requests.post(
"https://api.scavio.dev/api/v1/search",
headers={"x-api-key": SCAVIO_KEY},
json={"platform": platform, "query": query, "ai_overview": True},
timeout=10,
)
if res.ok and len(res.json().get("organic", [])) >= 1:
query_count += 1
return {"provider": "scavio", "data": res.json()}
except Exception:
pass
# Fallback: Brave
try:
res = requests.get(
"https://api.search.brave.com/res/v1/web/search",
headers={"X-Subscription-Token": BRAVE_KEY},
params={"q": query},
timeout=8,
)
if res.ok:
query_count += 1
return {"provider": "brave", "data": res.json()}
except Exception:
pass
return {"provider": "none", "data": {}}
# MCP tool handler
def handle_search_tool(params: dict) -> dict:
query = params.get("query", "")
platform = params.get("platform", "google")
cached = cached_search(query, platform)
return json.loads(cached)
result = handle_search_tool({"query": "best search api 2026", "platform": "google"})
print(f"Provider: {result.get('provider')}, Budget used: {query_count}/{DAILY_BUDGET}")JavaScript Example
const SCAVIO_KEY = "your_scavio_api_key";
const cache = new Map();
let queryCount = 0;
const DAILY_BUDGET = 500;
async function gatewaySearch(query, platform = "google") {
const cacheKey = `${platform}:${query}`;
if (cache.has(cacheKey)) return cache.get(cacheKey);
if (queryCount >= DAILY_BUDGET) return { error: "Budget exceeded" };
try {
const res = await fetch("https://api.scavio.dev/api/v1/search", {
method: "POST",
headers: { "x-api-key": SCAVIO_KEY, "content-type": "application/json" },
body: JSON.stringify({ platform, query, ai_overview: true }),
});
if (res.ok) {
const data = await res.json();
queryCount++;
cache.set(cacheKey, { provider: "scavio", data });
return { provider: "scavio", data };
}
} catch {}
return { provider: "none", data: {} };
}
const r = await gatewaySearch("best search api 2026");
console.log(`Provider: ${r.provider}, Budget: ${queryCount}/${DAILY_BUDGET}`);Platforms Used
Web search with knowledge graph, PAA, and AI overviews
Amazon
Product search with prices, ratings, and reviews
YouTube
Video search with transcripts and metadata
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