An r/DigitalMarketing post asked how to get Claude to analyze GA and GSC data for SEO recommendations. The answer: use MCP to connect Claude to your analytics, then add Scavio MCP for live SERP data. Claude can then cross-reference your GSC impressions with current SERP positions.
Prerequisites
- Claude Code or Claude Desktop
- Google Analytics 4 property
- Google Search Console verified site
- Scavio API key
Walkthrough
Step 1: Add Scavio MCP to Claude
Register the Scavio MCP server so Claude can search.
Bash
# In Claude Code:
claude mcp add scavio https://mcp.scavio.dev/mcp \
--header 'x-api-key: YOUR_SCAVIO_KEY'
# Verify it loaded:
claude mcp listStep 2: Export GSC data as CSV
Download your Search Console performance data for Claude to analyze.
Python
# From GSC UI: Performance > Export > CSV
# Or use the GSC API:
from googleapiclient.discovery import build
from google.oauth2 import service_account
creds = service_account.Credentials.from_service_account_file('sa.json',
scopes=['https://www.googleapis.com/auth/webmasters.readonly'])
service = build('searchconsole', 'v1', credentials=creds)
resp = service.searchanalytics().query(siteUrl='https://yoursite.com',
body={'startDate': '2026-04-01', 'endDate': '2026-05-01',
'dimensions': ['query'], 'rowLimit': 100}).execute()
for row in resp.get('rows', []):
print(f"{row['keys'][0]}: {row['clicks']} clicks, pos {row['position']:.1f}")Step 3: Cross-reference GSC queries with live SERP
For your top GSC queries, check current SERP position via Scavio.
Python
import requests, os
H = {'x-api-key': os.environ['SCAVIO_API_KEY']}
def check_serp_position(query, domain):
data = requests.post('https://api.scavio.dev/api/v1/search',
headers=H,
json={'platform': 'google', 'query': query}).json()
for r in data.get('organic_results', []):
if domain in r.get('link', ''):
return r['position']
return None
# Compare GSC avg position vs live SERP position
# Divergence means recent ranking changesStep 4: Ask Claude to generate SEO recommendations
With both data sources connected, Claude can give specific recommendations.
Text
# In Claude Code with Scavio MCP active:
# 'Analyze my top 10 GSC queries from this CSV.
# For each, check the current SERP position using Scavio.
# Identify queries where I dropped positions and suggest
# content improvements based on what currently ranks above me.'Python Example
Python
# Workflow: GSC data -> Claude MCP -> Scavio SERP check -> recommendations
# Cost: 10 keyword checks = 10 x $0.005 = $0.05
# Compare to: Ahrefs Lite $129/mo or Semrush Pro $139.95/mo for similar insightsJavaScript Example
JavaScript
const res = await fetch('https://api.scavio.dev/api/v1/search', {
method: 'POST',
headers: {'x-api-key': process.env.SCAVIO_API_KEY, 'Content-Type': 'application/json'},
body: JSON.stringify({platform: 'google', query: gscKeyword})
});
const serp = await res.json();
const liveRank = serp.organic_results?.findIndex(r => r.link.includes(myDomain)) + 1;Expected Output
JSON
Claude analyzes GSC performance data and cross-references with live SERP positions via Scavio MCP. Outputs specific content improvement recommendations for dropping keywords.