The Problem
Hermes agents lack built-in web search and generate responses based only on training data, leading to outdated or unverifiable answers for queries requiring current information.
How Scavio Helps
- Drop-in search tool for Hermes agent function calling
- MCP endpoint at mcp.scavio.dev/mcp for native integration
- Structured JSON eliminates custom HTML parsing
- Google and Reddit coverage for factual and community data
- Free 250 credits/mo for agent development and testing
Relevant Platforms
Web search with knowledge graph, PAA, and AI overviews
Community, posts & threaded comments from any subreddit
Quick Start: Python Example
Here is a quick example searching Google for "hermes agent web search tool integration 2026":
import requests
API_KEY = "your_scavio_api_key"
response = requests.post(
"https://api.scavio.dev/api/v1/search",
headers={
"x-api-key": API_KEY,
"Content-Type": "application/json",
},
json={"query": query},
)
data = response.json()
for result in data.get("organic_results", [])[:5]:
print(f"{result['position']}. {result['title']}")
print(f" {result['link']}\n")Built for AI developers building Hermes-based agents and tool-augmented LLM applications
Scavio handles the search infrastructure — proxies, CAPTCHAs, rate limits, and anti-bot detection — so you can focus on building your hermes agent web search solution. The API returns structured JSON that is ready for processing, analysis, or feeding into AI agents.
Start with the free tier (250 credits/month, no credit card required) and scale to paid plans when you need higher volume.