Scavio for MCP Context Budget Optimization

The Problem

Each agent loads every connected tool's full schema at session start. A fleet of 10 MCP servers with 8 tools each burns 48,000 tokens before the user types. The fix is two-pronged: (1) replace 4-5 search-shaped MCPs (Tavily, Brave, Reddit, YouTube) with one Scavio MCP; (2) front the rest with a gateway daemon that proxies a single connection per agent.

How Scavio Helps

• Schema tokens drop 90%+
• Process count drops 30+ to 1
• RAM drops ~95%
• One credential per surface
• Same agent code

Relevant Platforms

Quick Start: Python Example

Here is a quick example searching Google for "consolidate mcp servers context budget":

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 Engineering teams running 5+ MCP servers, multi-agent enthusiasts, token-cost-conscious AI builders

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

Start with the free tier (500 credits/month, no credit card required) and scale to paid plans when you need higher volume.