Scavio for MCP Stack Curation

The Problem

An r/mcp post asked which free MCPs are actually useful vs cool in theory. Default 70+ skill installs cost real per-message tokens.

How Scavio Helps

• 4-6 MCPs matched to real workflow
• Scavio replaces 5-8 narrow web skills
• Per-message input drops 4-8K tokens
• Routing accuracy improves
• Quarterly re-audit prevents drift

Relevant Platforms

Quick Start: Python Example

Here is a quick example searching Google for "2-week task log → categorize external dependencies → install 4-6 named MCPs (filesystem + git + scavio + linear + memory)":

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 Heavy Claude Code / Hermes / OpenClaw users, agent power-users (200+ messages/week), agencies billing per-message agent time

Scavio handles the search infrastructure — proxies, CAPTCHAs, rate limits, and anti-bot detection — so you can focus on building your mcp stack curation 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.