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Tutorial

How to Ground AI Agents to Prevent Hallucination

Stop AI agent hallucination by grounding with live web search. MCP config for Claude Code and Python agent examples.

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AI agents hallucinate outdated APIs, wrong versions, and fabricated data because their training data is months old. Search grounding gives agents live web access to verify facts before responding. Cost: 3-5 searches per task at $0.015-0.025.

Prerequisites

  • Claude Code or Python agent framework
  • Scavio API key
  • Basic understanding of MCP or tool calling

Walkthrough

Step 1: Configure MCP search server

Add Scavio MCP to your .mcp.json for native Claude Code integration.

Step 2: Define search tool for agents

Create a search tool function that the agent can call when uncertain about facts.

Step 3: Add grounding logic

Instruct the agent to search before recommending packages, APIs, or version numbers.

Step 4: Test with known-stale queries

Ask about recent releases to verify the agent searches instead of guessing.

Python Example

Python
import requests, os

H = {'x-api-key': os.environ['SCAVIO_API_KEY'], 'Content-Type': 'application/json'}

def search_ground(query):
    resp = requests.post('https://api.scavio.dev/api/v1/search',
        headers=H, json={'query': query, 'country_code': 'us', 'num_results': 5})
    data = resp.json()
    return [{'title': r['title'], 'snippet': r.get('snippet', '')} for r in data.get('organic_results', [])[:5]]

# Agent uses this before recommending
results = search_ground('next.js latest version 2026')
for r in results:
    print(f"{r['title']}: {r['snippet'][:100]}")

JavaScript Example

JavaScript
async function searchGround(query) {
  const resp = await fetch('https://api.scavio.dev/api/v1/search', {
    method: 'POST',
    headers: {'x-api-key': process.env.SCAVIO_API_KEY, 'Content-Type': 'application/json'},
    body: JSON.stringify({query, country_code: 'us', num_results: 5})
  });
  const data = await resp.json();
  return data.organic_results?.slice(0,5).map(r => ({title: r.title, snippet: r.snippet}));
}
const results = await searchGround('next.js latest version 2026');
results.forEach(r => console.log(r.title));

Expected Output

JSON
Next.js 16.1 Release Notes: Next.js 16.1 introduces...
Next.js Blog: Announcing Next.js 16...
...

Related Tutorials

  • How to Add MCP Search to Claude Code
  • How to Ground a Local LLM with Structured Search

Frequently Asked Questions

Most developers complete this tutorial in 15 to 30 minutes. You will need a Scavio API key (free tier works) and a working Python or JavaScript environment.

Claude Code or Python agent framework. Scavio API key. Basic understanding of MCP or tool calling. A Scavio API key gives you 50 free credits on signup.

Yes. The free tier includes 50 credits on signup, which is more than enough to complete this tutorial and prototype a working solution.

Scavio has a native LangChain package (langchain-scavio), an MCP server, and a plain REST API that works with any HTTP client. This tutorial uses the raw REST API, but you can adapt to your framework of choice.

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Start Building

Stop AI agent hallucination by grounding with live web search. MCP config for Claude Code and Python agent examples.

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