Let’s talk about your data goals and show you how Nimble’s Web Search Agents and SDK can power them.
Trusted By:
Native Integrations, Including:
Give your AI the ability to browse the live web in real time, delivering far more accurate, source-grounded data at a fraction of the cost of other tools.
Nimble Search API finds the truth where it actually lives, without the expensive overhead of index-based engines.
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Nimble’s Search API is priced for high-volume, production-grade agent workloads, giving you predictable economics, transparent metering, and dramatically lower cost-per-page:
Nimble’s Search API pulls information directly from the live web, producing the most accurate real-time results available; without paying index-maintenance premiums.Your agents get:
Other APIs return cached summaries. Nimble returns the actual data, in real time, for a fraction of the price.
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Use our REST APIs, connect our MCP server, or install our official integrations (LangChain, AI-SDK) to give your agents everything they need to navigate web pages, extract meaning, and return structured insights instantly.
Nimble’s Search API includes site-specialized sub-agents trained to navigate specific domains.
Each sub-agent knows how a particular site is structured, what to click, and how to extract the right data, enabling the streaming of precise, structured results without custom code.
Get started in minutes with simple command-line tools and async Python clients that make calling MCP endpoints straightforward.
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Nimble's MCP server connects effortlessly to popular AI platforms like Claude Desktop, Cursor, and Qodo - no custom setup required.
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The Nimble Cookbook offers hands-on guides that show you how to use MCP data for real use cases like LLM grounding, real-time web extraction, and AI workflow automation.
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Copy code
from langchain_nimble import NimbleSearchTool
from langchain.agents import create_agent
agent = create_agent(model="gpt-5.2", tools=[NimbleSearchTool()])
response = agent.invoke({"messages": [{
"role": "user", "content": "Latest Holiday Deals"
}]})
print(response)Copy code
const response = await fetch("https://nimble-retriever.webit.live/search", {
method: "POST",
headers: {
"Authorization": `Bearer ${process.env.NIMBLE_API_KEY}`,
"Content-Type": "application/json",
},
body: JSON.stringify({
query: "Latest Holiday Deals",
})
});
const data = await response.json();
console.log(data);Copy code
import os
import requests
response = requests.post(
"https://nimble-retriever.webit.live/search",
headers={
"Authorization": f"Bearer {os.environ.get('NIMBLE_API_KEY')}",
"Content-Type": "application/json",
},
json={
"query": "Latest Holiday Deals",
}
)
print(response.json())Copy code
curl https://nimble-retriever.webit.live/search \
-H "Content-Type: application/json" \
-H "Authorization: Bearer NIMBLE_API_KEY" \
-d '{
"query": "Latest Holiday Deals",
}'When you connect AI systems with data sources, trust is non-negotiable.
Compliance with Global Standards
GDPR, CCPA-aligned data collection with anonymized sessions
Customizable Access Controls
Manage permissions and data access based on roles and responsibilities within your team. This ensures that only authorized users can access sensitive information or critical functions within your pipelines.
Secure Infrastructure
Nimble uses secure cloud environments with leading providers such as AWS and GCP, leveraging their robust security measures, including DDoS protection, threat detection, and compliance certifications.
Privacy-Centric Approach
Nimble ensures the responsible gathering of publicly available data, always prioritizing privacy and best practices and respecting the websites to maintain a compliant data-gathering process.
Whether you're crafting your first AI assistant or scaling a production-grade agentic system, Nimble delivers the real-time web context your models need to reason, act, and adapt.
