The Problem
AI agents with single-platform search (Google only) miss context from Reddit discussions, YouTube tutorials, Amazon reviews, and TikTok trends. Multi-source grounding produces better-informed agent decisions.
The Scavio Solution
Configure Scavio as the agent's search tool via MCP or function calling. One tool provides access to 6 platforms. The agent chooses which platform to search based on the query context.
Before
Before multi-platform search, a research agent answering 'best noise-cancelling headphones 2026' searched Google only. It missed Reddit's r/headphones consensus picks and Amazon's actual pricing.
After
After adding multi-platform search, the same agent searches Google for rankings, Reddit for community preferences, and Amazon for actual prices. The answer includes real-time pricing from Amazon and user sentiment from Reddit. 3 searches = $0.015.
Who It Is For
AI agent developers, LangChain/CrewAI builders, research assistant developers, and teams building multi-source grounding pipelines.
Key Benefits
- 6 platforms from one search tool
- Agent chooses platform based on query context
- MCP server for zero-code integration
- Each platform search costs $0.005
- Free tier covers 250 multi-platform searches
Python Example
import requests, os
H = {'x-api-key': os.environ['SCAVIO_API_KEY'], 'Content-Type': 'application/json'}
def multi_search(query, platforms=['google', 'reddit', 'amazon']):
results = {}
for p in platforms:
params = {'query': query, 'country_code': 'us'}
if p != 'google': params['platform'] = p
data = requests.post('https://api.scavio.dev/api/v1/search',
headers=H, json=params).json()
results[p] = [{'title': r.get('title', ''), 'snippet': r.get('snippet', '')}
for r in data.get('organic_results', [])[:3]]
return results
# Agent decides which platforms to search based on query
results = multi_search('best noise cancelling headphones 2026')
for p, r in results.items():
print(f'{p}: {len(r)} results')JavaScript Example
const H = {'x-api-key': process.env.SCAVIO_API_KEY, 'Content-Type': 'application/json'};
async function multiSearch(query, platforms = ['google', 'reddit', 'amazon']) {
const results = {};
for (const p of platforms) {
const params = {query, country_code: 'us'};
if (p !== 'google') params.platform = p;
const r = await fetch('https://api.scavio.dev/api/v1/search', {
method: 'POST', headers: H, body: JSON.stringify(params)
}).then(r => r.json());
results[p] = (r.organic_results || []).slice(0, 3).map(r => ({title: r.title, snippet: r.snippet}));
}
return results;
}
multiSearch('best headphones 2026').then(r => Object.entries(r).forEach(([p, d]) => console.log(`${p}: ${d.length}`)));Platforms Used
Web search with knowledge graph, PAA, and AI overviews
Community, posts & threaded comments from any subreddit
YouTube
Video search with transcripts and metadata
Amazon
Product search with prices, ratings, and reviews
TikTok
Trending video, creator, and product discovery
Walmart
Product search with pricing and fulfillment data