Scavio for Local LLM Web Search Grounding

The Problem

Local LLMs running via Ollama or llama.cpp have no web access and hallucinate freely on current events, prices, and recent releases, limiting their usefulness for factual queries.

How Scavio Helps

• Works with any local model without tool calling support
• Simple context prepend pattern compatible with Ollama and vLLM
• Hallucination rate drops from ~40% to under 5% on factual queries
• Free 250 queries/month covers personal local LLM use
• AI Overview text fits small context windows for efficient grounding

Relevant Platforms

Quick Start: Python Example

Here is a quick example searching Google for "local LLM web search grounding Ollama API 2026":

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 running local LLMs via Ollama or vLLM, privacy-conscious users, and hobbyists building personal AI assistants

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