The Problem
AI agents using a single search MCP server can only query one platform. When a research task needs Google results plus Reddit discussions plus YouTube tutorials, the agent either makes do with one source or the developer wires up three separate MCP servers with different auth.
The Scavio Solution
Use Scavio's MCP server to give agents access to Google, YouTube, Reddit, Amazon, and more through a single MCP connection. The agent specifies the platform parameter and gets structured results from any source without additional configuration.
Before
Three MCP servers configured (Brave for web, separate Reddit tool, YouTube tool). Each has its own auth, rate limits, and result format. Agent tool definitions are cluttered.
After
One Scavio MCP server provides all platforms. Agent tool definition is one function with a platform parameter. Auth is one API key.
Who It Is For
AI agent developers who want multi-platform search through a single MCP server instead of managing multiple search tool integrations.
Key Benefits
- One MCP server covers 6+ search platforms
- Single API key for all platforms
- Structured JSON reduces token consumption
- Agent chooses platform per query dynamically
- Drop-in replacement for Brave, Tavily, or Serper MCP
Python Example
import requests, os
API_KEY = os.environ["SCAVIO_API_KEY"]
def mcp_search_tool(query: str, platform: str = "google") -> dict:
"""MCP-compatible search tool for AI agents.
Supports: google, youtube, reddit, amazon, google-maps, tiktok"""
resp = requests.post(
"https://api.scavio.dev/api/v1/search",
headers={"x-api-key": API_KEY, "Content-Type": "application/json"},
json={"query": query, "platform": platform, "country_code": "us"},
timeout=15,
)
data = resp.json()
results = data.get("organic_results", [])[:10]
return {
"platform": platform,
"query": query,
"results": [
{"title": r.get("title", ""), "url": r.get("link", ""), "snippet": r.get("snippet", "")}
for r in results
],
}
# Agent can call with any platform
google = mcp_search_tool("react server components 2026", "google")
reddit = mcp_search_tool("react server components experience", "reddit")
youtube = mcp_search_tool("react server components tutorial", "youtube")
print(f"Google: {len(google['results'])}, Reddit: {len(reddit['results'])}, YouTube: {len(youtube['results'])}")JavaScript Example
const H = {'x-api-key': process.env.SCAVIO_API_KEY, 'Content-Type': 'application/json'};
async function mcpSearch(query, platform='google') {
const r = await fetch('https://api.scavio.dev/api/v1/search', {method:'POST', headers:H, body:JSON.stringify({query, platform, country_code:'us'})});
const d = await r.json();
return {platform, query, results:(d.organic_results||[]).slice(0,10).map(r=>({title:r.title, url:r.link, snippet:r.snippet}))};
}
const [g, r, y] = await Promise.all([mcpSearch('react 2026','google'), mcpSearch('react experience','reddit'), mcpSearch('react tutorial','youtube')]);
console.log('Google:'+g.results.length+' Reddit:'+r.results.length+' YouTube:'+y.results.length);Platforms Used
Web search with knowledge graph, PAA, and AI overviews
YouTube
Video search with transcripts and metadata
Community, posts & threaded comments from any subreddit
Amazon
Product search with prices, ratings, and reviews