gsc-mcp

gsc-mcp

Turns Google Search Console into an SEO copilot by enabling natural language queries for search analytics, URL inspection, sitemap management, and opportunity discovery.

Category
Visit Server

README

<div align="center">

Searchlight

Technical SEO that fixes itself.

An autonomous technical-SEO and analytics agent, delivered as a Model Context Protocol (MCP) server. Point it at your site: it finds what's broken, explains it in plain language, fixes it in your repository, deploys, and verifies the fix is live.

Website · The /searchlight skill · Quickstart · Tools

License: MIT  Model Context Protocol  Node

</div>


The loop

Most SEO tools stop at the diagnosis. Searchlight runs the whole loop and proves the last step.

Step What it does
Detect Reads your Search Console and Analytics data, crawls key pages, finds indexing, canonical, redirect, sitemap, speed and on-page issues.
Explain Triages every finding in plain language with a worry-level: fix now, worth improving, or normal and safe to ignore.
Fix Edits your repository, framework-aware: canonical and host conflicts, redirect loops, sitemaps, metadata, structured data, the analytics tag.
Deploy Commits and ships through your existing pipeline. Edits only count once they are live.
Verify Re-audits the live site and confirms the fix in a real browser: the redirect resolves, the tag fires, the canonical agrees.

Proof

A live run on zawaaj.in (a custom Next.js site with a host and canonical conflict and missing analytics) went from audit 90 → 98 — canonical set, host redirect aligned (www → apex), meta trimmed, GA4 installed and verified firing, sitemap submitted — in about 50 minutes (≈25 minutes active; the rest idle waiting on a redeploy), versus a 4–6 hour manual baseline for a skilled developer. The full annotated run is on the website.

Searchlight automates the diagnosis and the fix. It does not design your ecommerce event-tracking plan — that part is still a human's job.


Quickstart

1. Add it to your MCP client (Claude Code shown; works in any MCP client):

claude mcp add searchlight -- npx -y @ajmalaksar/searchlight serve --setup

Or, in a generic client config:

{
  "mcpServers": {
    "searchlight": { "command": "npx", "args": ["-y", "@ajmalaksar/searchlight", "serve"] }
  }
}

2. Sign in with Google (one local OAuth sign-in for Search Console and Analytics; the token is stored only on your machine):

npx -y @ajmalaksar/searchlight login --setup

3. Install the /searchlight skill so your agent runs the whole loop with one command:

npx -y @ajmalaksar/searchlight skill install

4. Ask:

/searchlight audit zawaaj.in

First time on Google Cloud? The bundled client lets most users skip setup. To bring your own (Tier 0), create a Desktop app OAuth client (enable the Google Search Console API and PageSpeed Insights API, add yourself as a test user) and pass SEARCHLIGHT_OAUTH_CLIENT_ID / SEARCHLIGHT_OAUTH_CLIENT_SECRET to login.

Renamed from gsc-mcp: the legacy ~/.gsc-mcp directory and GSC_* environment variables still resolve, so an existing install keeps working without re-authenticating.


The /searchlight skill

skill install drops a skill into your AI client so the agent orchestrates the full loop instead of you calling raw tools. It routes on the first word:

Command Does
/searchlight audit [site] Read-only diagnosis: detect + explain, triaged. No changes.
/searchlight setup [site] The full guided loop: interview → detect → confirm → provision → fix → deploy → verify.
/searchlight fix [site] Already audited? Go straight to plan → confirm → fix → deploy → verify.

It always confirms before any provisioning, code edit, sitemap submit, or deploy.


Tools

auth_status, auth_login, list_sites, use_site, get_active_site, set_default_site, account_overview, gsc_deep_link, query_search_analytics, top_queries, top_pages, find_opportunities, compare_periods, inspect_url, coverage_report, refresh_coverage, get_pages_in_bucket, diagnose_site, snapshot_baseline, list_snapshots, progress_report, ga_list_properties, ga_measurement_id, ga_traffic, ga_top_pages, ga_report, list_sitemaps, get_sitemap. With --write / --setup: submit_sitemap, delete_sitemap, and the GA4 / verification provisioning tools.

Coverage report reconstructs the "Page indexing" report the GSC API won't export in bulk: it gathers candidate URLs from sitemaps and analytics, inspects them within the 2,000/day per-property quota (resumable), caches the results under ~/.searchlight/sites/, and buckets them by index status.

Baseline & progress (snapshot_baseline → … fix … → snapshot_baselineprogress_report) freeze a site's health on a given day, then diff two days into a plain-English before→after of what improved — which issues resolved, which are new, and how score and traffic moved.


Local-first & private

Searchlight runs as a local server. You sign in with your own Google account; the token is stored only on your device. There is no hosted backend and no data warehouse — each person runs their own. Read-only by default; write and provisioning scopes are opt-in, requested only when you start a setup action. Open source and MIT licensed. See the Privacy Policy.


CLI

searchlight login            Sign in with Google (opens a browser)
searchlight logout           Remove the stored token
searchlight status           Authentication + onboarding status
searchlight setup            Guided first-run
searchlight sites …          Manage the property registry (list / add / remove / default)
searchlight skill install    Install the /searchlight skill into your AI client (--here for this project)
searchlight serve            Start the MCP server over stdio (default)

Develop

npm install
npm run build
npm test

The server is a tool registry. To add a capability, create src/tools/<group>.ts exporting register: ToolModule, then add it to MODULES in src/tools/index.ts. See SPEC.md for the architecture.

License

MIT © Ajmal Aksar

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured