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. Introduction
AI agents are just as effective as they access to fresh, reliable information. Behind the scenes, many agents use web search tools to pull the latest context and ensure their results remain relevant. However, not all search APIs are made equal, and not every option will fit your stack or workflow without interruption.
In this article, we review the top 7 web search APIS that you can integrate into your agent workflow. Each API LOO, for example you will find an example to help you start soon. Best of all, whatever API we cover offers a free (though a limited) degree, allowing you to experience the credit card or experience without the need to face additional obstacles.
1. The firecrackers
Cracker It provides a dedicated search API built “for AI” along with its crawl/scrap steak. You can choose your output format: Clean Mark Down, Raw HTML, Link Lists, or Screenshots, so data fits your flow workflow. It also supports custom search parameters (such as language and country) to target the results through local, and is designed for AI agents who need web data on a scale.
Installation: pip install firecrawl-py
from firecrawl import Firecrawl
firecrawl = Firecrawl(api_key="fc-YOUR-API-KEY")
results = firecrawl.search(
query="KDnuggets",
limit=3,
)
print(results)2. Tavily
tavily There is a search engine for AI agents and LLMS that transforms questions into a single API call into LLM -ready insights. Instead of returning the raw links and noise pieces, it is widely accumulated up to 20 sources, then uses proprietary AI to score, filter and classify the most relevant content of its work, which can reduce the need for customs scraping and post processing.
Installation: pip install tavily-python
from tavily import TavilyClient
tavily_client = TavilyClient(api_key="tvly-YOUR_API_KEY")
response = tavily_client.search("Who is MLK?")
print(response)3. Exa
Exa A modern, AI-local search engine that offers four ways: auto, sharp, keywords and nerves. This methods are effectively balanced, healthy, speed and spiritual understanding. Made on its high quality web index, EXA uses the “Next Link Prediction” embedded in its nervous search. This feature is at a level level of meaning -based links rather than precise words, making it particularly effective for searching questions and complex, layered filters.
Installation: pip install exa_py
from exa_py import Exa
import os
exa = Exa(os.getenv('EXA_API_KEY'))
result = exa.search(
"hottest AI medical startups",
num_results=2
)4. Serve.uu
Visit A fast and cost -effective Google SERP (search engine results page) is API, which provides the results in just 1 to 2 seconds. It supports all major Google vertical in an API, which includes search, photos, news, maps, places, videos, shopping, scholars, patents, and automatically. It provides structural SERP data, which enables you to develop real -time search features without the need to scratch. Siripper allows you to start immediately with 2,500 free search questions, no credit card is required.
Installation: pip install --upgrade --quiet langchain-community langchain-openai
import os
import pprint
os.environ("SERPER_API_KEY") = "your-serper-api-key"
from langchain_community.utilities import GoogleSerperAPIWrapper
search = GoogleSerperAPIWrapper()
search.run("Top 5 programming languages in 2025")5.
Pollution With the support of additional search engines, offers a powerful Google Search API, providing the page data of structural search engine results. It features a strong infrastructure, which includes a captcha solution to ensure global IPS, a complete browser cluster, and reliable and accurate results. In addition, SerPAPI provides advanced parameters, such as location parameters and the exact control of the location through a / -looting.
Installation: pip install google-search-results
from serpapi import GoogleSearch
params = {
"engine": "google_news", # use Google News engine
"q": "Artificial Intelligence", # search query
"hl": "en", # language
"gl": "us", # country
"api_key": "secret_api_key" # replace with your SerpAPI key
}
search = GoogleSearch(params)
results = search.get_dict()
# Print top 5 news results with title + link
for idx, article in enumerate(results.get("news_results", ()), start=1):
print(f"{idx}. {article('title')} - {article('link')}")6.
Source Google News, Scholar, Automplete, Lens, Finance, Patent, Jobs, and Events, as well as Amazon, Bang, and Google Play, as well as non -Google sources such as Google News, Scholars, Automplete, Lens, Finance, as well as exposing Google Web, as well as exposing the Google Web. This expansion allows agents to target the correct vertical while maintaining a JSON scheme and permanent integration.
import requests
url = "
params = {
"engine": "google_maps",
"q": "best sushi restaurants in New York"
}
response = requests.get(url, params=params)
print(response.text)7. Brave finding
Brave search Offers the first API of privacy on an independent web index, which is the end of the web, news and photos that work better to ground LLM without tracking the user. This developer is friendly, performance, and it includes a free use plan.
import requests
url = "
headers = {
"Accept": "application/json",
"Accept-Encoding": "gzip",
"X-Subscription-Token": ""
}
params = {
"q": "greek restaurants in san francisco"
}
response = requests.get(url, headers=headers, params=params)
if response.status_code == 200:
data = response.json()
print(data)
else:
print(f"Error {response.status_code}: {response.text}") Wrap
I connect the search API with the cursor IDE by searching the MCP to pull fresh documents within my editor, which accelerates debugging and improves my programming flow. These tools do real -time web applications, agent’s workflow workflows, and more, while keeping the results in the ground and reducing fraud in sensitive scenarios.
Key Benefits:
- Customized for precise questions, including filters, freshness windows, area, and language
- Flexible output formats such as JSON, Mark Down, or Simple Text for Smooth Agent Hand Office
- Option to find and scratch the web to strengthen the context of your AI agents
- Free level and cheap use -based pricing so that you can experience and scale without any hassle
Select API matching your steak, delayed requirements, content coverage and budget. If you need a place to start, I recommend firecrackers and faster. I use both of them almost every day.
Abid Ali Owan For,,,,,,,,,, for,, for,,,, for,,,, for,,, for,,,, for,,,, for,,,, for,,, for,,, for,,, for,,, for,,,, for,,, for,,, for,,,, for,,, for,,,, for,,, for,,, for,,,, for,,, for,,, for,,,, for,,, for,,,, for,,, for,,,, for,,, for,,,, for,,, for,,,, for,,,, for,,,, for,,,, for,,,, for,,,, for,,,, for,,, for,,, for,,, for,,, for,,,,, for,,,, for,,,, for,,,, for,, for,.@1abidaliawan) A certified data scientist is a professional who loves to create a machine learning model. Currently, he is focusing on creating content and writing technical blogs on machine learning and data science technologies. Abid has a master’s degree in technology management and a bachelor’s degree in telecommunications engineering. Its vision is to create AI products using a graph neural network for students with mental illness.