mcp-search-console

Google Search Console MCP Server for SEOs

A Model Context Protocol (MCP) server that connects Google Search Console (GSC) to AI assistants, allowing you to analyze your SEO data through natural language conversations. Works with Claude Desktop, Cursor, Codex CLI, Gemini CLI, Antigravity, and any other MCP-compatible client.

Skip setup, get more. A more advanced hosted version — one-click sign-in, GA4, Google Ads, SERP lookups, keyword research, and a lot more. Works with Claude, ChatGPT, Cursor, Grok, and any other MCP client. → Advanced MCP for SEO professionals (hosted)

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What's New

[0.4.2] — November 2026

• Read-only OAuth tokens work again, and a failed refresh no longer deletes your token — the server now requests only the scope it needs (read-only by default, write only when GSC_ALLOW_DESTRUCTIVE=true) and loads existing tokens with their granted scope, so a webmasters.readonly token refreshes instead of being rejected. A transient refresh failure keeps your token file instead of silently deleting it. Thanks @christian-fastcorp. (#56)
• Tools no longer block the event loop — blocking Search Console API calls now run in a worker thread, so a slow request no longer stalls every other in-flight tool call. Thanks @kuldiph. (#52)
• get_advanced_search_analytics pagination fixed when capped — requesting more than 25,000 rows no longer drops the next page; has_more/next_start_row use the effective (capped) limit. Thanks @dajiaohuang. (#62)
• Optional tool arguments accept an explicit null — nine str | None parameters now validate when a client sends the advertised null default. Thanks @vishalhabib99. (#58)
• Raised the mcp[cli] floor to >=1.27.2 (kept the <2.0.0 cap) to clear four published SDK advisories. Thanks @prateekparshwa. (#40)

See the full version history in the Changelog below.

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What Can This Do?

Property Management

• See all your GSC properties in one place
• Get verification details and ownership information
• Add or remove properties from your account

Search Analytics & Reporting

• Discover which queries bring visitors to your site
• Track impressions, clicks, and click-through rates
• Analyze performance trends and compare time periods
• Visualize data with charts created by your AI assistant

URL Inspection & Indexing

• Check if specific pages have indexing problems
• See when Google last crawled your pages
• Inspect multiple URLs at once to identify patterns

Sitemap Management

• View all sitemaps and their status
• Submit new sitemaps
• Check for errors or warnings

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Available Tools

Tool	What It Does	What You Need to Provide
get_capabilities	Lists all tools and shows auth status — call this first if unsure	Nothing
list_properties	Shows all your GSC properties	Nothing
get_site_details	Details about a specific site	Site URL
get_search_analytics	Top queries and pages with clicks, impressions, CTR, position	Site URL, time period
get_performance_overview	Summary of site performance	Site URL, time period
compare_search_periods	Compare performance between two time periods	Site URL, two date ranges
get_search_by_page_query	Search terms driving traffic to a specific page	Site URL, page URL
get_advanced_search_analytics	Analytics with filters by country, device, query, page	Site URL
inspect_url_enhanced	Detailed crawl/index status for a URL	Site URL, page URL
batch_url_inspection	Inspect up to 10 URLs at once	Site URL, list of URLs
check_indexing_issues	Check multiple URLs for indexing problems	Site URL, list of URLs
get_sitemaps	Lists all sitemaps for a site	Site URL
list_sitemaps_enhanced	Detailed sitemap info including errors and warnings	Site URL
manage_sitemaps	Submit or delete sitemaps	Site URL, action
reauthenticate	Re-run the OAuth browser login (switch accounts)	Nothing

Ask your AI assistant to "call get_capabilities" for the full list of all 20 tools.

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Getting Started

Step 1 — Set Up Google API Credentials

You need credentials before configuring any client. Pick one method:

Option A — OAuth (Recommended — uses your own Google account)

1. Go to Google Cloud Console and create or select a project
2. Enable the Search Console API
3. Go to Credentials → Create Credentials → OAuth client ID
4. Configure the OAuth consent screen, select Desktop app, click Create
5. Download the JSON file — save it somewhere permanent (e.g. ~/Documents/client_secrets.json)

On first use, a browser window will open asking you to sign in to your Google account. After that, the token is saved and no browser interaction is needed again.

Option B — Service Account (For automation or team use)

1. Go to Google Cloud Console and create or select a project
2. Enable the Search Console API
3. Go to Credentials → Create Credentials → Service Account
4. Go to the Keys tab → Add Key → Create new key → JSON → Download
5. Save the file somewhere permanent (e.g. ~/Documents/service_account.json)
6. Add the service account email to your GSC property: Search Console → Settings → Users and permissions → Add user → Full access

🎥 Watch the step-by-step setup tutorial for this section

Updated 2026 — covers the full installation process using the new uvx method, from setting up your Google credentials to your first successful query.

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Step 2 — Installation

Option A — uvx (Recommended)

No cloning, no Python installation, no virtual environments. uvx downloads and runs the server automatically and keeps it up to date.

Install uv — open Terminal and run all three commands in order:

# 1. Download and install
curl -LsSf https://astral.sh/uv/install.sh | sh

# 2. Activate in the current Terminal session
source $HOME/.local/bin/env

# 3. Make it permanent for all future sessions
echo 'source $HOME/.local/bin/env' >> ~/.zshrc

Verify:

uv --version

Why all three commands? The installer puts uv in ~/.local/bin, but your already-open Terminal session doesn't know about that folder yet. Step 2 activates it immediately. Step 3 ensures every future Terminal window has it automatically.

Now configure your AI client:

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Claude Desktop

Config file: ~/Library/Application Support/Claude/claude_desktop_config.json

OAuth:

{
  "mcpServers": {
    "gscServer": {
      "command": "/FULL/PATH/TO/uvx",
      "args": ["mcp-search-console"],
      "env": {
        "GSC_OAUTH_CLIENT_SECRETS_FILE": "/full/path/to/client_secrets.json"
      }
    }
  }
}

Service Account:

{
  "mcpServers": {
    "gscServer": {
      "command": "/FULL/PATH/TO/uvx",
      "args": ["mcp-search-console"],
      "env": {
        "GSC_CREDENTIALS_PATH": "/full/path/to/service_account.json",
        "GSC_SKIP_OAUTH": "true"
      }
    }
  }
}

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Cursor

Config file: ~/.cursor/mcp.json

OAuth:

{
  "mcpServers": {
    "gscServer": {
      "command": "/FULL/PATH/TO/uvx",
      "args": ["mcp-search-console"],
      "env": {
        "GSC_OAUTH_CLIENT_SECRETS_FILE": "/full/path/to/client_secrets.json"
      }
    }
  }
}

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Codex CLI

Config file: ~/.codex/config.toml

OAuth:

[mcp_servers.gscServer]
command = "/FULL/PATH/TO/uvx"
args = ["mcp-search-console"]
enabled = true
env = { GSC_OAUTH_CLIENT_SECRETS_FILE = "/full/path/to/client_secrets.json" }

Service Account:

[mcp_servers.gscServer]
command = "/FULL/PATH/TO/uvx"
args = ["mcp-search-console"]
enabled = true
env = { GSC_CREDENTIALS_PATH = "/full/path/to/service_account.json", GSC_SKIP_OAUTH = "true" }

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Finding your uvx path: On macOS/Linux run which uvx in Terminal after installing uv (typically /Users/YOUR_NAME/.local/bin/uvx). On Windows, run Get-Command uvx | Select-Object -ExpandProperty Source in PowerShell (or where uvx in cmd) — it's usually C:\Users\YOUR_NAME\.local\bin\uvx.exe. Replace /FULL/PATH/TO/uvx in the configs above with that path.

Why the full path? GUI apps like Claude Desktop and Cursor launch without reading your shell config (~/.zshrc), so they don't know about ~/.local/bin. Using the full path guarantees it works regardless of how the app is launched. If you see a spawn uvx ENOENT error, this is the fix.

After saving the config, fully quit the app (Cmd+Q) and reopen it.

For OAuth: on first use, a browser window will open automatically for login. After that, the token is cached and you won't be asked again.

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Option B — Clone (Advanced)

Prefer a video walkthrough for this method? The tutorial below covers the clone install path step by step — virtual environment setup, dependencies, and config:

Use this if you want to modify the code or run a specific local version. This method uses the video tutorial above for the credential setup steps.

Requires Python 3.11+. This server will not start on Python 3.10 or older — and when it's launched by a GUI client like Claude Desktop, it fails silently (no tools appear and no log file is written). Check your version with python --version. If it's below 3.11, install Python 3.11 or newer and recreate your virtual environment. The uvx method (Option A) avoids this entirely by managing the Python version for you, so it's the recommended path on Windows.

Clone the repo:

git clone https://github.com/AminForou/mcp-gsc.git
cd mcp-gsc

Or download the ZIP from the green Code button at the top of this page and unzip it.

Set up the environment:

uv venv .venv
uv pip install -r requirements.txt

Configure your AI client (Claude Desktop example):

OAuth:

{
  "mcpServers": {
    "gscServer": {
      "command": "/full/path/to/mcp-gsc/.venv/bin/python",
      "args": ["/full/path/to/mcp-gsc/gsc_server.py"],
      "env": {
        "GSC_OAUTH_CLIENT_SECRETS_FILE": "/full/path/to/client_secrets.json"
      }
    }
  }
}

Service Account: