Scavio for Claude Code HTML Token Optimization

The Problem

An r/ClaudeAI post launched PullMD because Claude Code agents were burning tokens parsing HTML. Same fix via Scavio's hosted MCP: one config command, agent gets a clean extract tool returning markdown.

How Scavio Helps

• 10x reduction in input tokens for HTML-heavy tasks
• Hosted MCP — zero infrastructure
• Same MCP server provides search + extract
• Drop-in replacement for raw-HTML fetch tools

Relevant Platforms

Quick Start: Python Example

Here is a quick example searching Google for "extract markdown from a 60KB article for LLM context":

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 Claude Code skill authors, agent builders processing web pages, RAG pipeline maintainers

Scavio handles the search infrastructure — proxies, CAPTCHAs, rate limits, and anti-bot detection — so you can focus on building your claude code html token optimization 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.