SEO Monster

Don't learn another SEO dashboard. Just ask.

The open-source SEO analyst that lives inside the AI assistant you already use — working from your own Search Console, Analytics, and PageSpeed data, on your machine.

You don't open a new tool — you just ask, in plain English, inside Claude (or Cursor / Cline / Codex):

You *"What should I write about next?"*

🦖 SEOMonster Pulls your Search Console and surfaces three topics you're *almost* ranking for — positions 8–20 with real demand — ranked by opportunity. Say the word and it drafts the brief.

70 tools across Search Console, GA4, PageSpeed, Cloudflare, AI-citation tracking, keyword discovery, and technical SEO — every one returning the same JSON result envelope, every one driven by your own credentials. No new dashboard to learn; you chat with the assistant you already use.

[!NOTE]

Published on PyPI as `seo-monster` (so the command is uvx seo-monster). The import package is seo_mcp; seo-mcp is a dev/local alias. The package ships zero secrets — every credential is resolved at runtime from your own environment or config file.

• Your data, your machine. User-credential-driven; nothing is sent to any third party.
• Read-first, safe by default. Reads always work; the two routine writes (sitemap submit, indexing request) are on by default; the Cloudflare write tools (cache purge, redirects, settings, managed robots.txt) are gated behind SEO_MCP_ALLOW_DESTRUCTIVE, and the riskier ones also need a per-call confirm token.
• Lean. Standard library + the mcp SDK + the Google client libraries; PageSpeed and Cloudflare ride on urllib, no extra HTTP dependency.

Local evidence workbench

SEOmonster Workbench is a separately installed local companion for preserving source evidence, inspecting recommendation calculations, drafting action plans and comparing later observations. Its CLI stores project records in SQLite and supports portable exports, backup/restore and deterministic replay. The optional MCP interface exposes 17 tools for one configured project. Plans and recorded approvals remain separate from execution; the workbench has no external executor.

Start with the offline fixture workflow. The CLI needs no provider credentials or paid data. SDK 2 capture requires SEOmonster 0.10.0 or later, the first engine release on MCP SDK 2. The Workbench itself installs from source; it is not published on PyPI.

Quickstart

[!TIP]

Fastest path: the one-click install buttons above. Or add it to any MCP client by hand:

{

"mcpServers": { "seomonster": { "command": "uvx", "args": ["seo-monster"] } } }

Run the one-time Google sign-in once — uvx --from seo-monster seo-monster auth — then ask your assistant to call `system_status` to confirm what's connected. Full per-client setup and credentials are in Install and Auth.

How it works

Provider requests and local records

Selected tools contact Google Search Console, Indexing, GA4 Data/Admin, Google Ads, PageSpeed Insights, CrUX, Cloudflare or IndexNow. Optional research uses DataForSEO, Open PageRank, Perplexity, OpenAI, Anthropic or Gemini. Technical checks fetch the requested websites and related robots, sitemap, redirect or verification URLs. Providers receive the arguments and credentials needed for the selected request; optional paid calls can incur provider charges. These calls do not add maintainer telemetry.

The engine does not keep a query/result history. The separately installed local Workbench stores user-owned evidence and decision records in SQLite and creates exports only when requested. Your MCP host controls its own transcripts and logs. See Privacy for destinations and persistence scopes.

flowchart LR

U["You — plain English"] --> H["Claude · Cursor · Cline · Codex"] H -- "MCP · stdio" --> S["SEOMonster 70 tools"] S --> GSC["Search Console · GA4"] S --> PSI["PageSpeed · CrUX"] S --> CF["Cloudflare · IndexNow"] S --> AI["AI engines · SERP (optional)"] S -. "your creds · your machine" .-> U

SEOMonster is a stdio MCP server: your AI host launches it, it calls Google / Cloudflare / the AI engines with *your* credentials, and returns a consistent JSON envelope the assistant reads back to you in plain language.

Requirements

For the `.mcpb` bundle path (Claude Desktop): just Claude Desktop on macOS or Windows. The bundle declares Python 3.11+ as a runtime; Claude Desktop materializes the environment for you. No prior uv install needed.

For the `uvx` path (Cursor, Cline, Codex, advanced Claude Desktop): Python 3.11 or newer plus uv (which provides uvx). Find the absolute path to uvx with which uvx; GUI hosts do not read your shell profile, so MCP configs need the full path.

Tools

70 tools, grouped by service. All return the same result envelope (see Result envelope). Call system_status first if unsure what is configured. The server also publishes thirteen named workflow prompts.

Cross-service

• system_status - which services are configured/reachable, the Google auth method and scopes, whether destructive mode is on, the full tool catalog, and the list of registered prompts.

📂 Browse all 70 tools — grouped by service (GSC · GA4 · AI/GEO · keyword discovery · content · PageSpeed/CrUX · Cloudflare · IndexNow · technical · schema). Click to expand.

Google Search Console (18)

*Workhorses*

• gsc_list_properties - properties the credentials can see, with permission level and a derived writable flag (true for siteOwner / siteFullUser).
• gsc_search_analytics - the workhorse: clicks/impressions/CTR/position by dimensions, date range, filters, and data_state.
• gsc_top_queries / gsc_top_pages - convenience top-N wrappers.
• gsc_compare_periods - current vs prior window with per-key deltas. v0.2.0 added sort_by, sort_dir, min_delta_clicks / _impressions / _position, anomalies_only + sigma_threshold, and top for one-call movers / losers / outliers reporting.
• gsc_inspect_url - URL Inspection (index verdict, coverage, canonicals).
• gsc_batch_inspect_urls - inspect up to 25 URLs, per-URL failures collected.
• gsc_list_sitemaps - registered sitemaps and their status.
• gsc_submit_sitemap - submit a sitemap (write, un-gated; needs the writable scope). Accepts either sitemap_url (friendly) or feedpath (raw API field).
• gsc_request_indexing - request (re)crawl via the Indexing API (write, un-gated). Accepts singular url or urls.

*Query intelligence (v0.2.0)*

• gsc_query_opportunities - queries already ranking top N with below-target CTR. Title and meta optimization candidates.
• gsc_query_gaps - queries that draw impressions but barely any clicks. Content opportunity signal.
• gsc_new_queries - queries appearing in the current window with no prior impressions. Emerging topics.
• gsc_top_pages_by_query - which pages rank for a specific query. The cannibalization audit input.

*Multi-property + lifecycle (v0.5.0)*

• gsc_portfolio_summary(days, include?, exclude?) - multi-property fleet view. Per-property one-row summary (clicks, impressions, CTR, position) for the last N days, plus a portfolio-level rollup. Honors optional include / exclude filters. The single fastest answer to "how is the whole portfolio doing?" across agency or multi-brand setups.
• gsc_trending_pages(days, limit) - pages whose impressions grew most over the last N days vs the prior N days. Wrapper on gsc_compare_periods with dimensions=["page"], sort_by="delta_impressions", sort_dir="desc".
• gsc_decaying_pages(days, limit) - same wrapper, ascending sort. Pages to rescue.
• gsc_coverage_audit(urls, site_url?) - heuristic coverage audit. The GSC Index Coverage report is not exposed in the API; this tool takes a user- supplied URL list (typically pulled from a sitemap) and bulk-inspects each, then rolls up verdicts (PASS / PARTIAL / FAIL) and coverage_state frequencies.

Content intelligence (4)

• content_opportunities(site_url?, days?, count?, impressions_min?) - ranks data-grounded content topics from your own Search Console data: fuses CTR-vs-expected gap (curve self-calibrated from your own per-position CTR), striking-distance position, demand, and momentum into a transparent opportunity score; flags cannibalization. If a GA4 property is configured, it also weights each topic by the organic conversions its top page already drives (up to +50%), so topics that convert rank higher; filters_applied.ga4_value_status reports whether that ran and why (applied / no_ga4_property / ga4_unreachable / no_conversions). Prioritizes demand you already have; does not