Scavio + CrewAI

What is CrewAI?

Framework for orchestrating autonomous AI agents that collaborate to complete tasks. Supports multi-agent crews with defined roles.

How It Works

Scavio connects to CrewAI via a custom tool definition. Once connected, your CrewAI agent can search Google, Amazon, YouTube, and Walmart in real time. Each search returns structured JSON -- no HTML parsing, no scraping infrastructure.

Setup

pip install crewai requests

Code Example

Here is a complete CrewAI integration with Scavio:

from crewai import Agent, Task, Crew
from crewai.tools import tool
import requests

@tool("Scavio Search")
def scavio_search(query: str, platform: str = 'google') -> str:
    """Search the web 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="Research Specialist",
    goal="Find accurate, up-to-date information using web search",
    backstory="You are an expert researcher with access to real-time search data.",
    tools=[scavio_search],
)

task = Task(
    description="Research: best AI frameworks for building agents in 2026",
    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 the web 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="Research Specialist",
    goal="Find accurate, up-to-date information",
    backstory="Expert researcher with real-time search access.",
    tools=[scavio_search],
)

task = Task(
    description="Research: best AI frameworks for building agents in 2026",
    expected_output="Detailed summary with key findings and sources",
    agent=researcher,
)

crew = Crew(agents=[researcher], tasks=[task], verbose=True)
result = crew.kickoff()
print(result)

Available Platforms

Once connected, your CrewAI agent has access to all four Scavio platforms:

• Google — Web search with knowledge graph, PAA, and AI overviews
• Amazon — Product search with prices, ratings, and reviews
• Reddit — Community, posts & threaded comments from any subreddit
• YouTube — Video search with transcripts and metadata
• Walmart — Product search with pricing and fulfillment data
• LinkedIn — Post, profile, and company discovery via search
• TikTok — Trending video, creator, and product discovery
• Shopify — Cross-store product discovery and enrichment
• X (Twitter) — Post and profile discovery via search
• Apple App Store — App discovery, ranking, and review data
• Google Play Store — Android app discovery and ranking data
• Google Reviews — Business review extraction with ratings and responses
• Google Scholar — Academic paper search with citation counts
• Google Ads Transparency — Competitor ad creative and transparency data via SERP
• Reddit Comments Tree — Deep threaded comment fetch for brand monitoring
• YouTube Shorts — Shorts-specific search with metadata
• YouTube Playlists — Playlist discovery and removal tracking
• Google Jobs — Live jobs-board search for recruiting
• Amazon Bestsellers — Bestseller rank-change feed across categories

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.