Most local LLM web search setups default to SearXNG, but it gets blocked under sustained use and returns inconsistent JSON. In 2026, better options exist: MCP-connected search APIs that work with Ollama, LM Studio, oMLX, and Pi without self-hosting a search engine. You get structured results, multi-platform coverage, and no proxy maintenance.
The SearXNG problem for local LLMs
- Google blocks SearXNG IP after a few hundred queries
- Public instances share bans across all users
- JSON output format varies between SearXNG versions
- Requires Docker, config files, and ongoing maintenance
- No multi-platform search (Amazon, YouTube, TikTok not available)
Option 1: MCP search with Ollama
# ollama_with_search.py
# Give any Ollama model web search via Scavio API
import requests
import ollama
def web_search(query: str) -> str:
"""Web search tool for Ollama models."""
resp = requests.post(
"https://api.scavio.dev/api/v1/search",
headers={"x-api-key": "YOUR_KEY"},
json={"query": query, "num_results": 5}
)
data = resp.json()
results = []
for r in data.get("organic_results", []):
results.append(f"- {r['title']}: {r.get('snippet', '')}")
return "\\n".join(results)
# Use with function calling
tools = [{
"type": "function",
"function": {
"name": "web_search",
"description": "Search the web for current information",
"parameters": {
"type": "object",
"properties": {
"query": {"type": "string", "description": "Search query"}
},
"required": ["query"]
}
}
}]
response = ollama.chat(
model="qwen3:8b",
messages=[{"role": "user", "content": "What are the best AI frameworks in 2026?"}],
tools=tools
)Option 2: MCP config for oMLX and Pi
{
"mcpServers": {
"scavio": {
"url": "https://mcp.scavio.dev/mcp",
"headers": {
"x-api-key": "YOUR_KEY"
}
}
}
}Option 3: Direct API call from any local LLM
// Universal search function for any local LLM setup
async function searchWeb(query) {
const resp = await fetch("https://api.scavio.dev/api/v1/search", {
method: "POST",
headers: {
"x-api-key": process.env.SCAVIO_KEY,
"Content-Type": "application/json"
},
body: JSON.stringify({
query,
num_results: 5
})
});
const data = await resp.json();
return data.organic_results?.map(r => ({
title: r.title,
url: r.url,
snippet: r.snippet || ""
})) || [];
}
// Works with LM Studio, Ollama, or any local model
// that supports tool/function callingComparison: SearXNG vs API for local LLMs
Factor | SearXNG | MCP Search API
Setup | Docker + config | API key + JSON config
Maintenance | Ongoing | None
Reliability | 60-80% | 99%+
Multi-platform | No | Yes (Google, YT, Amazon...)
Cost | Free (hosting) | 250 free/mo, $0.005 after
Privacy | Full local | Queries sent to API
JSON quality | Inconsistent | Typed schemaPrivacy tradeoff
SearXNG's main advantage is privacy -- queries never leave your network. If that matters (medical research, legal queries), keep SearXNG. For coding assistance, documentation lookup, and general research, the API approach is more practical. The query goes to the API provider, but the LLM processing stays local.
Recommendation
Start with Scavio MCP (250 free credits/month). If you need more than 250 searches/month, the $30/month plan covers 7,000 queries. Keep SearXNG as a fallback for privacy-sensitive queries only.