Scavio for Agent Web Search for Local LLM

The Problem

Local LLM deployments lack web access because browser-based solutions require heavy infrastructure and most search APIs are designed for cloud-native architectures.

How Scavio Helps

• Simple REST API works with any local LLM tool-calling setup
• No browser automation or Selenium infrastructure needed
• Keep data private while still accessing live web results
• Structured JSON responses parse easily in local pipelines
• 250 free credits to test integration before committing

Relevant Platforms

Quick Start: Python Example

Here is a quick example searching Google for "ollama tool calling web search integration guide":

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 Privacy-focused developers running local LLMs for personal or enterprise use

Scavio handles the search infrastructure — proxies, CAPTCHAs, rate limits, and anti-bot detection — so you can focus on building your agent web search for local llm 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.