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 products, badge, sales_volume, price -- ready for reasoning and decision-making.
Setup
Bash
pip install crewai requestsCode Example
Here is a complete CrewAI agent that searches Amazon Bestsellers using Scavio:
Python
from crewai import Agent, Task, Crew
from crewai.tools import tool
import json
import os
import requests
# There is no bestsellers endpoint and Amazon search takes no sort parameter, so this is the marketplace's default ranking for the query, not the Best Sellers chart. Store position per ASIN on each run to see movement.
@tool("Scavio Search")
def scavio_search(query: str) -> str:
"""Query Amazon Bestsellers through the Scavio API (POST /api/v1/amazon/search)."""
response = requests.post(
"https://api.scavio.dev/api/v1/amazon/search",
headers={
"Authorization": "Bearer " + os.environ["SCAVIO_API_KEY"],
"Content-Type": "application/json",
},
json={"query": query, "country": "us"},
timeout=60,
)
response.raise_for_status()
return json.dumps(response.json())
researcher = Agent(
role="Amazon Bestsellers Research Specialist",
goal="Find accurate, up-to-date information using Amazon Bestsellers data",
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:
Python
from crewai import Agent, Task, Crew
from crewai.tools import tool
import json
import os
import requests
# There is no bestsellers endpoint and Amazon search takes no sort parameter, so this is the marketplace's default ranking for the query, not the Best Sellers chart. Store position per ASIN on each run to see movement.
@tool("Scavio Search")
def scavio_search(query: str) -> str:
"""Query Amazon Bestsellers through the Scavio API (POST /api/v1/amazon/search)."""
response = requests.post(
"https://api.scavio.dev/api/v1/amazon/search",
headers={
"Authorization": "Bearer " + os.environ["SCAVIO_API_KEY"],
"Content-Type": "application/json",
},
json={"query": query, "country": "us"},
timeout=60,
)
response.raise_for_status()
return json.dumps(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 50 credits on signup (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.