n8nsearchcomparison
n8n Search Nodes vs HTTP Request in 2026
HTTP Request node with structured search API beats dedicated n8n search nodes. More flexible, cheaper, supports AI Overview data and multi-platform search.
8 min
n8n offers multiple ways to add web search: dedicated search nodes (SerpAPI, Google Search), the generic HTTP Request node, and MCP integration. In 2026, the HTTP Request node with a structured search API is the most flexible approach -- it avoids vendor lock-in to specific n8n nodes, supports any API, and returns clean JSON that downstream nodes parse easily.
n8n search options compared
Text
Approach | Cost | Flexibility | Maintenance
SerpAPI node | $25/mo=1K | Low | Node updates lag API
Google Search node | $5/1K | Low | Limited params
HTTP Request node | API cost | High | You control everything
MCP integration | API cost | Medium | Still experimental in n8nHTTP Request node setup with Scavio
JSON
{
"nodes": [
{
"name": "Search API",
"type": "n8n-nodes-base.httpRequest",
"parameters": {
"method": "POST",
"url": "https://api.scavio.dev/api/v1/search",
"sendHeaders": true,
"headerParameters": {
"parameters": [
{ "name": "x-api-key", "value": "={{ $env.SCAVIO_KEY }}" },
{ "name": "Content-Type", "value": "application/json" }
]
},
"sendBody": true,
"bodyParameters": {
"parameters": [
{ "name": "query", "value": "={{ $json.keyword }}" },
{ "name": "num_results", "value": "10" },
{ "name": "include_ai_overview", "value": "true" }
]
}
}
}
]
}Why HTTP Request beats dedicated nodes
- Access all API parameters (dedicated nodes expose limited options)
- Switch providers by changing URL (no node replacement needed)
- Multi-platform search: same node for Google, Amazon, YouTube, Reddit
- AI Overview data: dedicated search nodes do not support this yet
Complete n8n workflow: keyword research pipeline
Python
# Python equivalent of the n8n workflow for testing
import requests
def n8n_search_workflow(keywords: list) -> list:
"""Simulate n8n keyword research workflow."""
results = []
for kw in keywords:
# Step 1: Google search (HTTP Request node equivalent)
resp = requests.post(
"https://api.scavio.dev/api/v1/search",
headers={"x-api-key": "YOUR_KEY"},
json={
"query": kw,
"num_results": 10,
"include_ai_overview": True
}
)
data = resp.json()
# Step 2: Extract insights (Code node equivalent)
organic_count = len(data.get("organic_results", []))
has_ai_overview = bool(data.get("ai_overview"))
paa_questions = [
q["question"] for q in data.get("people_also_ask", [])
]
results.append({
"keyword": kw,
"organic_results": organic_count,
"has_ai_overview": has_ai_overview,
"related_questions": paa_questions[:3],
"top_result": data.get("organic_results", [{}])[0].get("title", "")
})
return results
report = n8n_search_workflow(["best crm 2026", "project management tools"])
for r in report:
print(f"{r['keyword']}: {r['organic_results']} results, AI Overview: {r['has_ai_overview']}")
Multi-platform search in n8n
JavaScript
// n8n Code node: search multiple platforms from one workflow
const platforms = ["google", "youtube", "amazon"];
const query = $input.first().json.query;
const results = {};
for (const platform of platforms) {
const resp = await fetch("https://api.scavio.dev/api/v1/search", {
method: "POST",
headers: {
"x-api-key": $env.SCAVIO_KEY,
"Content-Type": "application/json"
},
body: JSON.stringify({ query, platform, num_results: 5 })
});
results[platform] = await resp.json();
}
return [{ json: results }];
Cost comparison for n8n workflows
Text
Approach | 1K queries/mo | 10K queries/mo
SerpAPI node | $25 | $150
Scavio HTTP | $5 | $50
Google CSE | Free (100/day)| $5
Brave Search | $5 | $50Recommendation
Use the HTTP Request node with a structured search API. It gives you the most control, costs less than dedicated nodes, and works with any provider. Switch providers by changing one URL.