The Problem
AI assistants and IDE-based coding tools need web search access through MCP, but building a custom MCP search server from scratch requires handling multiple search provider APIs and response normalization.
How Scavio Helps
- Ready-made MCP endpoint at mcp.scavio.dev/mcp
- Multi-platform search through a single MCP interface
- Build custom MCP servers with business logic on top
- Structured responses optimized for LLM consumption
- Compatible with Claude Code, Cursor, and MCP-enabled tools
Relevant Platforms
Web search with knowledge graph, PAA, and AI overviews
Community, posts & threaded comments from any subreddit
YouTube
Video search with transcripts and metadata
Quick Start: Python Example
Here is a quick example searching Google for "MCP search server custom build Google Reddit YouTube 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 AI tool developers, MCP server builders, and teams integrating search into AI assistants
Scavio handles the search infrastructure — proxies, CAPTCHAs, rate limits, and anti-bot detection — so you can focus on building your mcp custom search server solution. The API returns structured JSON that is ready for processing, analysis, or feeding into AI agents.
Start with the free tier (50 credits on signup, no credit card required) and scale to paid plans when you need higher volume.