Best Search APIs for AI Agents — Real-Time Data Access Compared

AI agents need real-time web data to function — whether answering user questions, researching topics, or grounding LLM outputs in current information. But not all search APIs are built for agent workflows. Some return raw HTML that wastes tokens, others are too slow for interactive loops, and many lack the structured output formats agents need.

This guide compares the best search APIs for AI agent development, focusing on latency, output format, token efficiency, and cost at the volumes agents typically consume.

Key Takeaways

• AI agents have different search needs than traditional applications — structured output and low latency matter more than raw result count
• Tavily and SearchHive are built specifically for agent workflows with pre-processed outputs
• Exa offers sub-200ms search latency for real-time agent loops
• SearchHive uniquely combines search, scraping, and deep research in one API
• Token efficiency can save 60-80% on LLM costs compared to raw search results

What Makes a Search API Good for AI Agents?

Traditional search APIs return titles, URLs, and snippets — designed for human consumption or application integration. AI agents need something different:

• Structured output: free JSON formatter responses with clean, deduplicated content
• Token efficiency: Pre-processed content that doesn't waste context window space
• Low latency: Sub-second response times for interactive agent loops
• Content access: Ability to fetch full page content, not just snippets
• Flexible queries: Support for natural language, semantic, and keyword search

1. SearchHive

SearchHive provides three endpoints designed for agent workflows: SwiftSearch for web search, ScrapeForge for content extraction, and DeepDive for research synthesis.

Pricing: Free 500 credits, Starter $9/5K, Builder $49/100K, Unicorn $199/500K. Credits work across all three endpoints.

import requests

# Search with content extraction in one call
response = requests.post(
    "https://api.searchhive.dev/v1/swiftsearch",
    headers={"Authorization": "Bearer YOUR_API_KEY"},
    json={
        "query": "RAG vs fine-tuning comparison 2026",
        "limit": 5,
        "include_content": True,
        "content_length": 2000
    }
)

results = response.json()["results"]
for r in results:
    print(f"[{r.get('score', 'N/A')}] {r['title']}")
    if r.get("content"):
        print(f"  Content: {r['content'][:200]}...")
    print()

Why agents love it: SearchHive's unified API means one integration covers search, scraping, and deep research. An agent can search for information, scrape specific pages, and synthesize findings — all through the same API with the same auth and billing. This reduces integration complexity and makes agent code cleaner.

/compare/tavily

2. Tavily

Tavily is built exclusively for AI agents. Every response is optimized for LLM context — clean content, relevant results, minimal noise.

Pricing: Free 1,000 credits/month, pay-as-you-go $0.008/credit.

import requests

response = requests.post(
    "https://api.tavily.com/search",
    json={
        "api_key": "YOUR_KEY",
        "query": "latest React Server Components best practices",
        "search_depth": "advanced",
        "include_answer": True,
        "include_raw_content": False,
        "max_results": 5
    }
)

data = response.json()
# Tavily returns a pre-summarized answer
if data.get("answer"):
    print(f"Summary: {data['answer']}")
for r in data.get("results", []):
    print(f"  {r['title']}: {r['url']}")

Why agents love it: The include_answer parameter returns an AI-generated summary, saving the agent a reasoning step. The search_depth: "advanced" mode runs additional searches to find more comprehensive results. Output is already formatted for LLM consumption.

3. Exa

Exa specializes in neural search — finding conceptually relevant content using embeddings, not just keyword matching.

Pricing: Search $7/1K requests, Deep Search $12/1K, Answer $5/1K.

import requests

response = requests.post(
    "https://api.exa.ai/search",
    headers={"x-api-key": "YOUR_KEY"},
    json={
        "query": "academic research on chain-of-thought prompting",
        "numResults": 5,
        "contents": {"text": {"maxCharacters": 1000}},
        "type": "neural"
    }
)

for result in response.json()["results"]:
    print(f"Score: {result.get('score', 'N/A')}")
    print(f"Title: {result['title']}")
    if result.get("text"):
        print(f"Text: {result['text'][:200]}...")
    print()

Why agents love it: Exa's neural search finds semantically relevant content that keyword search misses. The sub-200ms latency option keeps agent loops responsive. The contents parameter fetches page text inline, eliminating a separate content extraction step.

4. Brave Search API

Brave offers search through its independent index — no Google scraping, no legal ambiguity.

Pricing: $5/1K web searches, $4/1K AI answers. $5 free credits/month.

import requests

headers = {"X-Subscription-Token": "YOUR_KEY"}
response = requests.get(
    "https://api.search.brave.com/res/v1/web/search",
    headers=headers,
    params={"q": "Python asyncio best practices 2026", "count": 10}
)

for item in response.json().get("web", {}).get("results", []):
    print(f"{item['title']}: {item['url']}")

Why agents love it: Clean API, independent index, and the AI Answers endpoint returns summarized responses. The $5/month free credits are useful for prototyping.

5. Serper.dev

Serper provides fast Google search results in JSON with minimal overhead.

Pricing: 2,500 free on signup, then $50/50K ($1/1K), scaling to $0.50/1K at volume.

import requests

response = requests.get(
    "https://google.serper.dev/search",
    headers={"X-API-KEY": "YOUR_KEY"},
    params={"q": "vector database benchmark comparison", "num": 10}
)

data = response.json()
for result in data.get("organic", []):
    print(f"{result['title']}: {result['link']}")
    print(f"  {result.get('snippet', '')[:150]}")

Why agents love it: Fast, cheap, and returns Google-quality results. The JSON format is clean. At scale ($0.50/1K), it's one of the cheapest search options available.

6. SerpApi

SerpApi parses Google, Bing, YouTube, and other search engines into structured JSON.

Pricing: Free 250/mo, Starter $25/1K, scaling to $3,750/1M.

import requests

response = requests.get(
    "https://serpapi.com/search",
    params={"api_key": "YOUR_KEY", "q": "best hosting for ML workloads", "engine": "google"}
)

for result in response.json().get("organic_results", [])[:10]:
    print(f"{result['title']}: {result['link']}")

Best for: Multi-engine search needs (Google, YouTube, Bing, etc.). Expensive compared to alternatives.

Comparison Table

Verdict

For pure AI agent search, Tavily and Exa are the most purpose-built options. Tavily's pre-summarized answers save agent reasoning steps, while Exa's semantic search finds conceptually relevant results that keyword search misses.

SearchHive stands out as the most complete option — it handles search, content scraping, and deep research through a single API. For agents that need to search, read pages, and synthesize information, this unified approach eliminates the complexity of juggling multiple search and scraping APIs.

Start with 500 free credits and see how it fits your agent architecture.

/blog/best-serpapi-alternatives-for-search-api-developers /compare/tavily