SEO Analytics MCP
Provides access to Google Analytics 4 (GA4) metrics, enabling tools for fetching landing page data, generating trend reports, assessing data quality, and computing merged analytics outputs.
Enables interaction with Google Search Console to list sites and retrieve search performance data, including top queries and top pages.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@SEO Analytics MCP analyze my top pages and give me actionable SEO insights"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
SEO Analytics MCP
MCP server for Google Search Console (GSC) + Google Analytics 4 (GA4).
How It Works
What .venv Means
.venvis this project's private Python environment.It contains its own Python interpreter and dependencies for this repo only.
run-local.shactivates.venvso the MCP server runs with the correct package versions.
What stdio Means
stdiomeans the MCP client and server communicate through standard input/output streams.The client starts
run-local.sh, sends tool requests in, and reads JSON responses out.No web server or HTTP endpoint is required for the default local setup.
Your MCP client (Claude/Codex) launches
run-local.shas a stdio server process.run-local.shprepares.venv, installs dependencies, loadsconfig/.env, and validatesconfig/service-account.json.The Python server (
seo-analytics-mcp) receives tool calls, fetches data from GSC/GA4 using the service account, and computes merged analysis outputs.Results are returned to the MCP client as structured JSON.
Related MCP server: mcp-site-analyst
Deployment Model
This project is deployed as a local process on your machine via stdio.
It is not an HTTP API service by default and does not require cloud hosting.
To "deploy" it for another environment, clone the repo there, provide
config/.envandconfig/service-account.json, then register that machine'srun-local.shpath in the MCP client.
Prerequisites
Python 3.11+
Quick Start
Create local config files from templates:
cp config/.env.example config/.env
cp config/service-account.example.json config/service-account.jsonFill required values:
config/.envDEFAULT_GSC_SITE_URL(required format:sc-domain:example.com)DEFAULT_GA4_PROPERTY_ID
config/service-account.jsonReplace all
REPLACE_WITH_...fields with real Google service-account values.
Run the server:
./run-local.shThe script creates/uses .venv, installs dependencies, loads config/.env, validates credentials, and starts seo-analytics-mcp over stdio.
MCP Client Setup
Use the local launcher script as the MCP server command:
/absolute/path/to/analytics/run-local.shCodex App
Add server:
codex mcp add seo-analytics -- /absolute/path/to/analytics/run-local.shVerify:
codex mcp listRemove:
codex mcp remove seo-analyticsClaude Code CLI
Add server:
claude mcp add -s project seo-analytics -- /absolute/path/to/analytics/run-local.shVerify:
claude mcp listRemove:
claude mcp remove seo-analyticsClaude Desktop App (macOS)
Quit Claude Desktop completely.
Edit
~/Library/Application Support/Claude/claude_desktop_config.json.Add this server entry (merge into existing
mcpServersif present):
{
"mcpServers": {
"seo-analytics": {
"type": "stdio",
"command": "/absolute/path/to/analytics/run-local.sh",
"args": []
}
}
}Start Claude Desktop again.
In a new chat, run tool
capabilitiesto confirm connection.
Main Tools
capabilitiesgsc_list_sitesgsc_top_pagesgsc_top_queriesga4_landing_pagesanalytics_merge_page_metricsanalytics_generate_action_itemsanalytics_trend_reportanalytics_data_quality_report
Screenshots
These screenshots are example outputs produced by using Claude Code with this MCP server. The MCP provides the underlying GSC/GA4 data and analytics tools; dashboard rendering is not generated by default by the server itself. For privacy reasons, values shown in the screenshots are randomized; the actual workflow was executed against real data.

Troubleshooting
service-account.json still contains placeholder valuesReplace all
REPLACE_WITH_...fields inconfig/service-account.json.
No such file or directory: .../credentials/service-account.jsonYou have a stale credential env override from an older setup.
Re-add the MCP server so it runs the latest
run-local.shand usesconfig/service-account.json.
Operation not permittedwhen Claude Desktop starts MCPmacOS is blocking execution from protected folders (commonly
~/Documents).Either grant Claude Desktop access in
System Settings -> Privacy & Security(Files and Foldersand/orFull Disk Access) or move the repo to a non-protected path like~/dev/analytics.After changing permissions/path, restart Claude Desktop and re-add the MCP entry if needed.
Missing property_id and DEFAULT_GA4_PROPERTY_ID is not setSet
DEFAULT_GA4_PROPERTY_IDinconfig/.env.
Missing site_url...Set
DEFAULT_GSC_SITE_URLinconfig/.env.
GSC permission error on
https://...propertyThis server enforces GSC properties in
sc-domain:<domain>format to avoid URL-prefix mismatch issues.Use a Domain property in Search Console and grant your service account access there.
Security
Never commit
config/service-account.jsonorconfig/.env.Commit only template files:
config/service-account.example.jsonconfig/.env.example
Available Tools
16 toolsanalytics_data_quality_reportC
Show merge coverage and top URL mismatches between GSC and GA4.
Inputs: site_url, property_id, start_date, end_date, +2 more. Returns: object
analytics_generate_action_itemsC
Generate prioritized SEO and content action items from merged data.
Inputs: site_url, property_id, start_date, end_date, +4 more. Returns: object
analytics_merge_page_metricsC
Merge normalized GSC + GA4 page metrics into one dataset.
Inputs: site_url, property_id, start_date, end_date, +2 more. Returns: object
analytics_popularity_snapshotC
Get top pages by clicks, impressions, sessions, and conversions.
Inputs: site_url, property_id, start_date, end_date, +2 more. Returns: object
analytics_query_page_opportunitiesC
Find high-impression query/page pairs with weak CTR and weak on-page outcomes.
Inputs: site_url, property_id, start_date, end_date, +3 more. Returns: object
analytics_topic_clustersC
Extract high-impact query token clusters to guide content focus.
Inputs: site_url, start_date, end_date, min_query_impressions, +2 more. Returns: object
analytics_trend_reportC
Compare current vs previous period to surface gainers and decliners.
Inputs: site_url, property_id, start_date, end_date, +2 more. Returns: object
capabilitiesB
Show enabled connectors, defaults, and key analysis thresholds.
Inputs: no named parameters. Returns: object
ga4_channel_reportC
Break down GA4 landing pages by default channel group.
Inputs: property_id, start_date, end_date, top_n. Returns: object
ga4_landing_pagesC
Return GA4 landing pages with engagement and conversion metrics.
Inputs: property_id, start_date, end_date, top_n, +1 more. Returns: object
ga4_run_report_rawC
Run raw GA4 report with optional dimension/metric filters and ordering.
Inputs: property_id, start_date, end_date, dimensions, +8 more. Returns: object
gsc_list_sitesB
List Search Console properties available to the authenticated account.
Inputs: no named parameters. Returns: object
gsc_query_page_pairsC
Return query+page combinations from GSC for intent/page matching analysis.
Inputs: site_url, start_date, end_date, search_type, +2 more. Returns: object
gsc_search_analytics_rawC
Run a raw Search Console Search Analytics query with full options.
Inputs: site_url, start_date, end_date, dimensions, +6 more. Returns: object
gsc_top_pagesC
Return top pages from GSC with clicks, impressions, CTR, and position.
Inputs: site_url, start_date, end_date, search_type, +2 more. Returns: object
gsc_top_queriesC
Return top queries from GSC by clicks.
Inputs: site_url, start_date, end_date, search_type, +2 more. Returns: object
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelog…
TDQS
Scored across 16 tools
Most tools have distinct purposes, such as merging data, generating reports, or querying specific platforms. However, some overlap exists between analytics tools like 'analytics_popularity_snapshot' and 'gsc_top_pages', which could cause confusion in selection for similar tasks.
The naming is mixed, with prefixes like 'analytics_', 'ga4_', and 'gsc_' used consistently within groups, but the overall pattern is not uniform. Tools like 'capabilities' break the verb_noun convention, and there is no single naming style across all tools.
With 16 tools, the count is slightly high but reasonable for an SEO analytics domain that covers data merging, reporting, and platform-specific queries. It provides comprehensive coverage without being overly bloated.
The tool set offers complete coverage for SEO analytics, including data integration from GSC and GA4, trend analysis, opportunity identification, and action item generation. There are no obvious gaps, supporting end-to-end workflows effectively.
Maintenance
Related MCP Connectors
Google Search Console, GA4 and PageSpeed MCP server for Claude, ChatGPT and Cursor. Free, hosted.
Read-only Google Search Console MCP server for AI assistants.
SEO MCP server for keyword research, SERP analysis, audits, and Search Console workflows.
Hosted MCP server for marketing agencies: connect Google Ads, GA4, Search Console, Meta, LinkedIn and more to Claude or ChatGPT. Pull reports and make changes via OAuth login, no setup.
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