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LangChain – ScraperAPI

Give your AI agent the ability to browse websites, search Google and Amazon in just two lines of code.

The langchain-scraperapi package adds three ready-to-use LangChain tools backed by the ScraperAPI service:

Tool class Use it to
ScraperAPITool Grab the HTML/text/markdown of any web page
ScraperAPIGoogleSearchTool Get structured Google Search SERP data
ScraperAPIAmazonSearchTool Get structured Amazon product-search data

Installation

pip install -U langchain-scraperapi

Setup

Create an account at https://www.scraperapi.com/ and get an API key, then set it as an environment variable:

import os
os.environ["SCRAPERAPI_API_KEY"] = "your-api-key"

Quick Start

ScraperAPITool — Browse any website

Scrape HTML, text, or markdown from any webpage:

from langchain_scraperapi.tools import ScraperAPITool

tool = ScraperAPITool()

# Get text content
result = tool.invoke({
    "url": "https://example.com",
    "output_format": "text",
    "render": True
})
print(result)

Parameters:

  • url (required) – target page URL
  • output_format – "text" | "markdown" (default returns HTML)
  • country_code – e.g. "us", "de"
  • device_type – "desktop" | "mobile"
  • premium – use premium proxies
  • render – run JavaScript before returning content
  • keep_headers – include response headers

ScraperAPIGoogleSearchTool — Structured Google Search

Get structured Google Search results:

from langchain_scraperapi.tools import ScraperAPIGoogleSearchTool

google_search = ScraperAPIGoogleSearchTool()

results = google_search.invoke({
    "query": "what is langchain",
    "num": 20,
    "output_format": "json"
})
print(results)

Parameters:

  • query (required) – search terms
  • output_format – "json" (default) or "csv"
  • country_code, tld, num, hl, gl – optional search modifiers

ScraperAPIAmazonSearchTool — Structured Amazon Search

Get structured Amazon product search results:

from langchain_scraperapi.tools import ScraperAPIAmazonSearchTool

amazon_search = ScraperAPIAmazonSearchTool()

products = amazon_search.invoke({
    "query": "noise cancelling headphones",
    "tld": "co.uk",
    "page": 2
})
print(products)

Parameters:

  • query (required) – product search terms
  • output_format – "json" (default) or "csv"
  • country_code, tld, page – optional search modifiers

Example: AI Agent that can browse the web

from langchain_openai import ChatOpenAI
from langchain.agents import AgentExecutor, create_tool_calling_agent
from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
from langchain_scraperapi.tools import ScraperAPITool

# Set up tools and LLM
tools = [ScraperAPITool()]
llm = ChatOpenAI(model_name="gpt-4o", temperature=0)

# Create prompt
prompt = ChatPromptTemplate.from_messages([
    ("system", "You are a helpful assistant that can browse websites. Use ScraperAPITool to access web content."),
    ("human", "{input}"),
    MessagesPlaceholder(variable_name="agent_scratchpad"),
])

# Create and run agent
agent = create_tool_calling_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)

response = agent_executor.invoke({
    "input": "Browse hackernews and summarize the top story"
})

Documentation

For complete parameter details and advanced usage, see the ScraperAPI documentation.

Metadata

Release files for langchain-scraperapi 0.1.2

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

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