What is CrewAI?
Framework for orchestrating autonomous AI agents that collaborate to complete tasks. Supports multi-agent crews with defined roles.
Searching Amazon Bestsellers with CrewAI
This integration lets your CrewAI agent search Amazon Bestsellers in real time via the Scavio API. The agent gets back structured JSON with product title, ASIN, bestseller rank, category — ready for reasoning and decision-making.
Setup
pip install crewai requestsCode Example
Here is a complete CrewAI agent that searches Amazon Bestsellers using Scavio:
from crewai import Agent, Task, Crew
from crewai.tools import tool
import requests
@tool("Scavio Search")
def scavio_search(query: str) -> str:
"""Search Amazon Bestsellers using Scavio API."""
response = requests.post(
"https://api.scavio.dev/api/v1/search",
headers={"x-api-key": "your_scavio_api_key", "Content-Type": "application/json"},
json={"query": query},
)
return str(response.json())
researcher = Agent(
role="Amazon Bestsellers Research Specialist",
goal="Find accurate, up-to-date information using Amazon Bestsellers search",
backstory="You are an expert researcher with access to real-time search data.",
tools=[scavio_search],
)
task = Task(
description="Research: electronics bestsellers",
expected_output="A detailed summary with sources",
agent=researcher,
)
crew = Crew(agents=[researcher], tasks=[task])
result = crew.kickoff()
print(result)Full Working Example
A production-ready example with error handling:
from crewai import Agent, Task, Crew
from crewai.tools import tool
import requests
@tool("Scavio Search")
def scavio_search(query: str) -> str:
"""Search Amazon Bestsellers using Scavio API."""
response = requests.post(
"https://api.scavio.dev/api/v1/search",
headers={"x-api-key": "your_scavio_api_key", "Content-Type": "application/json"},
json={"query": query},
)
return str(response.json())
researcher = Agent(
role="Amazon Bestsellers Research Specialist",
goal="Find accurate, up-to-date information",
backstory="Expert researcher with real-time search access.",
tools=[scavio_search],
)
task = Task(
description="Research: electronics bestsellers",
expected_output="Detailed summary with key findings and sources",
agent=researcher,
)
crew = Crew(agents=[researcher], tasks=[task], verbose=True)
result = crew.kickoff()
print(result)Pricing
Scavio offers a free tier with 500 credits/month (1 credit per search). No credit card required. This is enough to build and test your CrewAI integration. Paid plans start at $30/month for higher volumes.