Scavio for MCP Pre-Coding Search Routine

The Problem

Coding agents waste time guessing at class names, SDK methods, and API patterns from stale training data. A pre-coding search routine eliminates this.

How Scavio Helps

• 60-second routine saves hours of debugging
• Verify SDK versions before writing code
• Load codebase context via memory MCP
• Search documentation via web MCP
• Prevent entire categories of hallucination

Relevant Platforms

Quick Start: Python Example

Here is a quick example searching Google for "next.js 15 app router api routes":

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 Developers using Claude Code, Cursor, or other AI coding tools

Scavio handles the search infrastructure — proxies, CAPTCHAs, rate limits, and anti-bot detection — so you can focus on building your mcp pre-coding search routine solution. The API returns structured JSON that is ready for processing, analysis, or feeding into AI agents.

Start with the free tier (250 credits/month, no credit card required) and scale to paid plans when you need higher volume.