The Problem
NousResearch Hermes Agent can reason over provided context but cannot search the web. This limits it to static information available at invocation time. For research tasks, fact-checking, and any workflow requiring current data, the agent hallucinates or refuses rather than finding the answer. Adding web search requires either building a custom tool integration or connecting to an MCP-compatible search server.
The Scavio Solution
Connect Hermes Agent to Scavio's MCP server at mcp.scavio.dev. The agent discovers search tools (search_google, search_reddit, search_amazon, etc.) automatically and can invoke them during multi-step reasoning. No custom HTTP client code is needed. For teams wanting more control, a direct REST API integration with a custom tool definition provides explicit request/response handling.
Before
Before MCP integration, Hermes Agent answered questions based solely on its training data and provided context. Any question about current events, prices, or recent developments produced either a hallucinated answer or a refusal.
After
After connecting to Scavio MCP, Hermes Agent searches Google, Reddit, Amazon, YouTube, TikTok, and Walmart as part of its reasoning chain. The agent grounds answers in current data, cites sources, and handles research tasks that were previously impossible.
Who It Is For
Teams building research agents on the Hermes framework who need web search grounding. Developers prototyping agent workflows that require current web data without complex API integrations.
Key Benefits
- Zero-code search integration via MCP protocol
- Six platforms available as native agent tools
- Agent discovers search capabilities automatically
- Structured JSON responses that fit within context windows
- Per-query pricing at $0.005 with no subscription lock-in
Python Example
import requests
API_KEY = "your_scavio_api_key"
def search_tool(query: str, platform: str = "google") -> dict:
"""Custom search tool for Hermes Agent integration."""
res = requests.post(
"https://api.scavio.dev/api/v1/search",
headers={"x-api-key": API_KEY},
json={"platform": platform, "query": query, "ai_overview": platform == "google"},
timeout=15,
)
res.raise_for_status()
data = res.json()
results = []
for r in data.get("organic", [])[:5]:
results.append({
"title": r.get("title", ""),
"snippet": r.get("snippet", ""),
"link": r.get("link", ""),
})
return {
"query": query,
"platform": platform,
"results": results,
"ai_overview": (data.get("ai_overview", {}) or {}).get("text", "")[:500] if platform == "google" else None,
}
# Register as Hermes tool:
# tools = [{"name": "web_search", "function": search_tool, "description": "Search the web for current information"}]
result = search_tool("hermes agent framework", "google")
print(f"Found {len(result['results'])} results")
for r in result["results"]:
print(f" {r['title']}")JavaScript Example
const API_KEY = "your_scavio_api_key";
async function searchTool(query, platform = "google") {
const res = await fetch("https://api.scavio.dev/api/v1/search", {
method: "POST",
headers: { "x-api-key": API_KEY, "content-type": "application/json" },
body: JSON.stringify({ platform, query, ai_overview: platform === "google" }),
});
if (!res.ok) throw new Error(`scavio ${res.status}`);
const data = await res.json();
return {
query,
platform,
results: (data.organic ?? []).slice(0, 5).map((r) => ({ title: r.title ?? "", snippet: r.snippet ?? "", link: r.link ?? "" })),
aiOverview: data.ai_overview?.text?.slice(0, 500) ?? null,
};
}
// Register as Hermes tool in agent config
const result = await searchTool("hermes agent framework");
console.log(`Found ${result.results.length} results`);
for (const r of result.results) console.log(` ${r.title}`);Platforms Used
Web search with knowledge graph, PAA, and AI overviews
Community, posts & threaded comments from any subreddit
Amazon
Product search with prices, ratings, and reviews
YouTube
Video search with transcripts and metadata
TikTok
Trending video, creator, and product discovery
Walmart
Product search with pricing and fulfillment data