Search Agents

Nimble Web Search Agents (WSA) are ready-to-use extraction agents for popular websites like Amazon, Google, LinkedIn, and hundreds more. No CSS selectors or scraping expertise required - just provide the agent name and parameters, and get structured data instantly.

Quick Start

Example Request

from nimble_python import Nimble

nimble = Nimble(api_key="YOUR-API-KEY")

result = nimble.agent(
    agent="amazon_pdp",
    params={
        "asin": "B0DLKFK6LR",
        "zip_code": "90210"
    }
)

print(f"Product: {result['data']['parsing']['product_title']}")
print(f"Price: ${result['data']['parsing']['web_price']}")

Example Response

{
  "url": "https://www.amazon.com/dp/B08N5WRWNW",
  "task_id": "b1fa7943-cba5-4ec2-a88c-4d2d6799c794",
  "status": "success",
  "data": {
    "html": "...",
    "parsing": {
      "asin": "B08N5WRWNW",
      "product_title": "Apple AirPods Pro (2nd Generation)",
      "brand": "Apple",
      "web_price": 249.00,
      "list_price": 279.00,
      "average_of_reviews": 4.7,
      "number_of_reviews": 125432,
      "availability": true
    }
  },
  "status_code": 200
}

How it works

Select an agent and provide inputs

Choose an agent by name (e.g., amazon_pdp, google_search) and pass the required parameters like product ID, search query, or URL

Nimble handles everything

The agent fetches the page, handles anti-bot protection, and extracts data using battle-tested selectors maintained by Nimble

Receive structured data

Get clean, normalized JSON with consistent field names - ready to use in your application immediately

Two types of agents

Public Search Agent

Maintained by Nimble - Gallery of pre-built agents for popular websites.

Battle-tested, auto-healing, and updated 24/7 when sites change. Browse the Gallery.

Custom Search Agent

Created by you - Build agents for any website using the Agentic Studio.

No coding required - just describe what you need in natural language.

Parameters

Supported input parameters:

agent - Required

agent

string

required

The name of the pre-built agent to use. Each agent is designed for a specific platform or data type.Popular agents:

amazon_pdp - Amazon product pages
amazon_serp - Amazon search results
google_search - Google search results
google_maps_search - Google Maps locations
walmart_pdp - Walmart products
chatgpt - ChatGPT prompt results
perplexity - Perplexity prompt results

Browse all agents →

params - Required

params

object

required

Agent-specific parameters that tell the agent what data to fetch. Each agent has different requirements.Common param types:

Product IDs (ASINs, SKUs)
Search queries
URLs or usernames
Location information (country, zip code)
Page numbers for pagination

Example:

{
  "asin": "B08N5WRWNW",
  "country": "US",
  "zip_code": "90210"
}

localization

boolean

default:"false"

Enable location-based pricing and availability. When enabled, pass zip_code or store_id in params.Only available for agents that support localization (check agent details).Example:

{
  "agent": "amazon_pdp",
  "localization": true,
  "params": {
    "asin": "B08N5WRWNW",
    "zip_code": "90210"
  }
}

Each agent has unique parameter requirements. Check the Agent Gallery for exact parameters for each agent.

Usage

E-commerce product extraction

Extract product data from Amazon, Walmart, and other retailers:

from nimble_python import Nimble

nimble = Nimble(api_key="YOUR-API-KEY")

# Amazon product
result = nimble.agent(
    agent="amazon_pdp",
    params={
        "asin": "B08N5WRWNW",
        "country": "US"
    }
)

print(f"Product: {result['data']['parsing']['product_title']}")
print(f"Price: ${result['data']['parsing']['web_price']}")
print(f"Rating: {result['data']['parsing']['average_of_reviews']}")

Search results extraction

Get search results from Google, Amazon, and other platforms:

from nimble_python import Nimble

nimble = Nimble(api_key="YOUR-API-KEY")

# Amazon search
result = nimble.agent(
    agent="amazon_serp",
    params={
        "query": "wireless headphones",
        "country": "US"
    }
)

print(f"Found {len(result['data']['parsing'])} products")
for product in result['data']['parsing']:
    print(f"- {product['product_name']}: ${product['price']}")

Google Maps extraction

Find businesses and locations:

from nimble_python import Nimble

nimble = Nimble(api_key="YOUR-API-KEY")

result = nimble.agent(
    agent="google_maps_search",
    params={
        "query": "coffee shops near Times Square"
    }
)

for place in result['data']['parsing']['entities']['SearchResult']:
    print(f"- {place['title']} ({place['rating']} stars)")

LLM platform extraction

Get responses from AI platforms like ChatGPT and Perplexity:

from nimble_python import Nimble

nimble = Nimble(api_key="YOUR-API-KEY")

result = nimble.agent(
    agent="chatgpt",
    params={
        "prompt": "What are the best practices for web scraping?"
    }
)

print(result['data']['parsing']['response'])

Localized extraction

Get location-specific pricing and availability:

from nimble_python import Nimble

nimble = Nimble(api_key="YOUR-API-KEY")

# Get New York pricing
result = nimble.agent(
    agent="amazon_pdp",
    localization=True,
    params={
        "asin": "B08N5WRWNW",
        "zip_code": "10001"
    }
)

print(f"Price in NYC: ${result['data']['parsing']['web_price']}")

Async extraction

Run agent extractions asynchronously for batch processing:

from nimble_python import Nimble
import time

nimble = Nimble(api_key="YOUR-API-KEY")

# Submit async extraction
response = nimble.agent_async(
    agent="amazon_pdp",
    params={"asin": "B08N5WRWNW"}
)

task_id = response['task']['id']
print(f"Task created: {task_id}")

# Poll for completion
while True:
    status = nimble.get_task_status(task_id)
    if status['state'] == 'completed':
        results = nimble.get_task_results(task_id)
        print(f"Product: {results['data']['parsing']['product_title']}")
        break
    elif status['state'] == 'failed':
        print(f"Task failed: {status.get('error')}")
        break
    time.sleep(5)

Async mode supports webhooks and cloud storage. See the Agent Usage Guide for batch processing and advanced async options.

Agent Gallery

Browse pre-built agents maintained by Nimble for popular platforms:

Explore Full Gallery

Browse all agents with interactive documentation and live testing

E-commerce

Agent	Platform	Description
`amazon_pdp`	Amazon	Product details, pricing, reviews
`amazon_serp`	Amazon	Search results with products
`walmart_pdp`	Walmart	Product details and pricing
`walmart_search`	Walmart	Search results
`target_pdp`	Target	Product details
`best_buy_pdp`	Best Buy	Product details

Search Engines

Agent	Platform	Description
`google_search`	Google	Search results with snippets
`google_maps_search`	Google Maps	Business listings and locations
`google_search_aio`	Google	AI Overview results

LLM Platforms

Agent	Platform	Description
`chatgpt`	ChatGPT	Prompt responses
`perplexity`	Perplexity	Search + AI responses
`gemini`	Google Gemini	Prompt responses
`grok`	Grok	Prompt responses

Agent	Platform	Description
`tiktok_account`	TikTok	Account profiles and videos
`facebook_page`	Facebook	Page information
`youtube_shorts`	YouTube	Short-form videos

Create Custom Agents

Can’t find an agent for your target website? Create your own using Agentic Studio - no coding required.

Open Agentic Studio

Go to the Agentic Studio in Nimble Platform

Provide URL and describe your needs

Enter the website URL and describe what data you need in plain English:“Extract product name, price, rating, and all review comments”

AI creates your agent

Our AI analyzes the page and builds an extraction agent automatically - no CSS selectors needed

Test and refine

Preview extracted data and refine your description if needed

Use via API

Your custom agent is available via the same Agent API with your chosen name

Custom agent example

from nimble_python import Nimble

nimble = Nimble(api_key="YOUR-API-KEY")

# Use your custom agent just like a public one
result = nimble.agent(
    agent="my_custom_store_pdp",  # Your custom agent name
    params={
        "url": "https://example-store.com/products/widget-pro"
    }
)

print(f"Product: {result['data']['parsing']['product_name']}")
print(f"Price: ${result['data']['parsing']['price']}")

Custom agents are private to your account and not maintained by Nimble. You’re responsible for updating them if the target site changes. For popular sites, always prefer public agents which are maintained by Nimble 24/7.

Response Fields

Field	Type	Description
`url`	string	The URL that was extracted
`task_id`	string	Unique identifier for the request
`status`	string	`success` or `failed`
`data.html`	string	Raw HTML content
`data.parsing`	object	Structured extracted data
`status_code`	number	HTTP status code from target

Use cases

Price Monitoring

Track prices across Amazon, Walmart, and other retailers with consistent data formats

Product Research

Gather comprehensive product data from major e-commerce platforms

Search Tracking

Monitor Google, Bing, and marketplace search results for SEO and visibility

Competitive Intelligence

Extract competitor data from any website using public or custom agents

Agents vs other tools

What you need	Use
Data from popular sites (Amazon, Google, etc.)	Public Agents - browse gallery
Data from sites not in the gallery	Custom Agents - create in Studio
Data from specific URLs (expert users)	Extract - full control with CSS selectors
Data from entire website	Crawl
Search web + extract content from results	Search

Most users should start with Web Search Agents. Public agents cover popular sites with zero configuration. For anything else, create a custom agent in the Agentic Studio - it’s the fastest path to production-ready data extraction.

Introduction

Web Tools

Agentic

Quick Start

Example Request

Example Response

How it works

Two types of agents

Public Search Agent

Custom Search Agent

Parameters

Usage

E-commerce product extraction

Search results extraction

Google Maps extraction

LLM platform extraction

Localized extraction

Async extraction

Agent Gallery

Explore Full Gallery

E-commerce

Search Engines

LLM Platforms

Create Custom Agents

Custom agent example

Response Fields

Use cases

Price Monitoring

Product Research

Search Tracking

Competitive Intelligence

Agents vs other tools

Next steps

Agent Gallery

Agentic Studio

Introduction

Web Tools

Agentic

​Quick Start

​Example Request

​Example Response

​How it works

​Two types of agents

Public Search Agent

Custom Search Agent

​Parameters

​Usage

​E-commerce product extraction

​Search results extraction

​Google Maps extraction

​LLM platform extraction

​Localized extraction

​Async extraction

​Agent Gallery

Explore Full Gallery

​E-commerce

​Search Engines

​LLM Platforms

​Social Media

​Create Custom Agents

​Custom agent example

​Response Fields

​Use cases

Price Monitoring

Product Research

Search Tracking

Competitive Intelligence

​Agents vs other tools

​Next steps

Agent Gallery

Agentic Studio

Quick Start

Example Request

Example Response

How it works

Two types of agents

Parameters

Usage

E-commerce product extraction

Search results extraction

Google Maps extraction

LLM platform extraction

Localized extraction

Async extraction

Agent Gallery

E-commerce

Search Engines

LLM Platforms

Social Media

Create Custom Agents

Custom agent example

Response Fields

Use cases

Agents vs other tools

Next steps