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How to Replace the Bing Web Search API for a Deep Research Agent

Bing Web Search API was retired in August 2025. This tutorial wires Scavio in as a drop-in replacement for deep research agents.

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An r/AI_Agents thread asked what to use after the Bing Web Search API retired in August 2025. This tutorial wires Scavio as a multi-surface replacement and shows the agent loop that uses SERP, Reddit, and YouTube together.

Prerequisites

  • Python 3.10+
  • Anthropic API key
  • Scavio API key

Walkthrough

Step 1: Replace the Bing call

Same query, new endpoint.

Python
import requests, os
API_KEY = os.environ['SCAVIO_API_KEY']

def serp(q):
    return requests.post('https://api.scavio.dev/api/v1/search',
        headers={'x-api-key': API_KEY}, json={'query': q}).json()

Step 2: Add Reddit surface

Reddit threads catch context Bing missed.

Python
def reddit(q):
    return requests.post('https://api.scavio.dev/api/v1/reddit/search',
        headers={'x-api-key': API_KEY}, json={'query': q}).json()

Step 3: Add YouTube surface

Videos surface primary-source quotes.

Python
def yt(q):
    return requests.post('https://api.scavio.dev/api/v1/youtube/search',
        headers={'x-api-key': API_KEY}, json={'query': q}).json()

Step 4: Compose the deep research loop

Three surfaces fan out per question.

Python
def deep_research(q):
    return {
        'serp': serp(q).get('organic_results', [])[:5],
        'reddit': reddit(q).get('posts', [])[:5],
        'youtube': yt(q).get('videos', [])[:3],
    }

Step 5: Have the LLM compose the answer

Claude sees three surfaces in one prompt.

Python
import anthropic
client = anthropic.Anthropic()

def answer(q):
    data = deep_research(q)
    msg = client.messages.create(model='claude-sonnet-4-6', max_tokens=600,
        messages=[{'role':'user','content':f'Q: {q}\nDATA: {data}\nWrite a sourced answer.'}])
    return msg.content[0].text

Python Example

Python
import os, requests
API_KEY = os.environ['SCAVIO_API_KEY']
H = {'x-api-key': API_KEY}

def research(q):
    s = requests.post('https://api.scavio.dev/api/v1/search', headers=H, json={'query': q}).json()
    r = requests.post('https://api.scavio.dev/api/v1/reddit/search', headers=H, json={'query': q}).json()
    return {'serp': s.get('organic_results', [])[:5], 'reddit': r.get('posts', [])[:5]}

print(research('agentic search api 2026'))

JavaScript Example

JavaScript
const H = { 'x-api-key': process.env.SCAVIO_API_KEY, 'Content-Type': 'application/json' };
export async function research(q) {
  const [s, r] = await Promise.all([
    fetch('https://api.scavio.dev/api/v1/search', { method: 'POST', headers: H, body: JSON.stringify({ query: q }) }).then(r => r.json()),
    fetch('https://api.scavio.dev/api/v1/reddit/search', { method: 'POST', headers: H, body: JSON.stringify({ query: q }) }).then(r => r.json())
  ]);
  return { s, r };
}

Expected Output

JSON
Per question, three structured surfaces returned in one round trip. Total cost ~3 credits per question = $0.013 at the $30 tier.

Related Tutorials

  • How to Add Structured Search to an AI Assistant
  • How to Build a Research Assistant Without Token Overflow

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.

Python 3.10+. Anthropic API key. Scavio API key. 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.

Related Resources

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Start Building

Bing Web Search API was retired in August 2025. This tutorial wires Scavio in as a drop-in replacement for deep research agents.

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