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analytics-mcp

Free

Unified web-analytics MCP server — GA4, Cloudflare, Vercel and Search Console behind one normalized tool surface, with the discrepancies between them explained rather than hidden. OAuth 2.1 for Claude web, stdio for l...

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Related by shared tags and keywordsvibe-curatorwriting-craftislamqa-org-mcp
ai-toolsanalyticsclaudecloudflare-analyticsga4aiai assistantautomation

Overview

analytics-mcp is a Model Context Protocol server that puts GA4, Cloudflare Web Analytics, Vercel Analytics and Google Search Console behind one normalized tool surface. It is built to teach the model what the numbers mean, with each metric carrying a plain-language meaning and the server knowing which discrepancies between trackers are structural. It can be deployed remotely using StreamableHTTP and OAuth 2.1 on Vercel, or run locally over stdio for Claude Code, Cursor, and Claude Desktop. The server exposes read-only tools such as list_sites, list_sources, get_schema, query, query_raw, explain_discrepancy, validate_query, seo_opportunities, explain_ctr_gap, ai_referrals, inspect_page, and page_changes. Canonical metrics include pageviews, sessions, visitors, clicks, impressions, ctr, and position, each mapped to native names per source. Search analysis computes a click-through curve from the user's own Search Console rows, and AI visibility reports sessions arriving from AI assistants by engine while stating that arrivals are not citations. inspect_page fetches a page and reports mechanical findings such as title length, missing description, duplicate headings, canonical, noindex, and non-200 status. page_changes records page state only when a content hash moves, and the store is optional. Setup requires Node 20+ and pnpm, with SITES_CONFIG describing sites and credentials configured per source.

Pricing

Free

Detailed plans have not been confirmed in our catalog. Check the official website for current limits and billing terms.

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Prices and limits may change. Confirm the currency, billing period, seat minimum and usage caps on the official website.

Use Cases

  • Teams use analytics-mcp to ask one question and get answers from every tracker bound to a site.
  • Teams use explain_discrepancy to determine whether a gap between two trackers is normal.
  • Teams use seo_opportunities to rank cheapest search wins by estimated missed clicks.
  • Teams use ai_referrals to see traffic arriving from AI assistants by engine.
  • Teams use inspect_page to see what one page says about itself, including title, description, canonical, headings, and status.
  • Teams use page_changes to see what changed on a page and when, with search numbers either side.
  • Teams use validate_query to dry-run unsupported metrics, truncated ranges, and bad comparisons.
  • Teams use query_raw as an escape hatch to send a native payload to one source.

Features

AI assistant

Natural language interface

Workflow automation

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