Tutorial

How to Configure OpenClaw with Scavio Search

Set up Scavio as the search backend for your OpenClaw agent. Replace Brave or Tavily with structured multi-platform search via MCP.

OpenClaw agents need a reliable search backend to ground their responses in current web data. Many OpenClaw deployments use Brave Search or Tavily, but these can be limited in platform coverage or require separate configurations for different search types. Scavio provides a single MCP endpoint that covers Google, Reddit, YouTube, Amazon, and Walmart, simplifying your agent's search setup. This tutorial shows how to configure Scavio as the search tool for your OpenClaw agent using either MCP or direct API integration.

Prerequisites

  • OpenClaw agent installed and running
  • A Scavio API key from scavio.dev
  • Basic familiarity with MCP server configuration

Walkthrough

Step 1: Add Scavio MCP to OpenClaw config

Configure the Scavio MCP server in your OpenClaw agent's MCP settings.

Python
# Add to your OpenClaw MCP configuration:
# {
#   "mcpServers": {
#     "scavio": {
#       "url": "https://mcp.scavio.dev/mcp",
#       "headers": {
#         "x-api-key": "your_scavio_api_key"
#       }
#     }
#   }
# }

Step 2: Verify the MCP connection

Test that the OpenClaw agent can reach the Scavio MCP server and list available tools.

Python
# After adding the MCP config, restart your OpenClaw agent
# The agent should discover these Scavio tools:
# - search: Query Google, Reddit, YouTube, Amazon, Walmart
# - extract: Extract content from URLs

# Test with a simple query in your agent:
# "Search for the latest Python web frameworks"

Step 3: Test direct API as fallback

Verify the Scavio API works directly in case you need a non-MCP integration.

Python
import os, requests

API_KEY = os.environ["SCAVIO_API_KEY"]
resp = requests.post("https://api.scavio.dev/api/v1/search",
    headers={"x-api-key": API_KEY},
    json={"platform": "google", "query": "OpenClaw agent deployment guide"})
results = resp.json().get("organic_results", [])[:3]
for r in results:
    print(f"{r['title']}: {r['link']}")

Step 4: Configure multi-platform search

Set up the agent to use different platforms based on the query type.

Python
import os, requests

API_KEY = os.environ["SCAVIO_API_KEY"]

def agent_search(query, platform="google"):
    resp = requests.post("https://api.scavio.dev/api/v1/search",
        headers={"x-api-key": API_KEY},
        json={"platform": platform, "query": query})
    return resp.json().get("organic_results", [])[:5]

# Google for general queries
print(agent_search("best CRM tools"))
# Reddit for opinions
print(agent_search("best CRM tools", "reddit"))

Python Example

Python
import os, requests
API_KEY = os.environ["SCAVIO_API_KEY"]
def search(query, platform="google"):
    resp = requests.post("https://api.scavio.dev/api/v1/search",
        headers={"x-api-key": API_KEY},
        json={"platform": platform, "query": query})
    return resp.json().get("organic_results", [])[:5]

for r in search("OpenClaw agent setup"):
    print(r["title"])

JavaScript Example

JavaScript
const H = {"x-api-key": process.env.SCAVIO_API_KEY, "Content-Type": "application/json"};
async function search(query, platform = "google") {
  const r = await fetch("https://api.scavio.dev/api/v1/search", {
    method: "POST", headers: H,
    body: JSON.stringify({platform, query})
  });
  return (await r.json()).organic_results || [];
}
(await search("OpenClaw agent setup")).forEach(r => console.log(r.title));

Expected Output

JSON
An OpenClaw agent configured with Scavio as its search backend, capable of querying multiple platforms through a single MCP endpoint.

Related Tutorials

Frequently Asked Questions

Most developers complete this tutorial in 15 to 30 minutes. You will need a Scavio API key (free tier works) and a working Python or JavaScript environment.

OpenClaw agent installed and running. A Scavio API key from scavio.dev. Basic familiarity with MCP server configuration. A Scavio API key gives you 250 free credits per month.

Yes. The free tier includes 250 credits per month, which is more than enough to complete this tutorial and prototype a working solution.

Scavio has a native LangChain package (langchain-scavio), an MCP server, and a plain REST API that works with any HTTP client. This tutorial uses the raw REST API, but you can adapt to your framework of choice.

Start Building

Set up Scavio as the search backend for your OpenClaw agent. Replace Brave or Tavily with structured multi-platform search via MCP.