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  3. Gizmoanalytics MCP
Gizmoanalytics MCP logo
Health: ActiveRecent health check succeeded.Last checked 9/11/2026, 7:31:33 PM

Gizmoanalytics MCP

User RatingsBe the first to rate and review this MCP server!
View Repository1 GitHub StarsTotal stargazers on GitHub for the source repository (1 stars).Visit Website
web-analyticsmonitoringmcpdeveloper-tools

Hosted MCP endpoint for installing and querying cookieless Gizmo Analytics across supported web frameworks.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β€” or use 1-click editor setup below.

Add to CursorAdd to VS Code
Manual Client & Custom JSON ConfigExpand JSON β–Ύ

Client Config & Setup

Remote HTTP
Choose your client or environment
Target File:~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "sudomichael-gizmoanalytics-mcp": {
      "url": "https://gizmoanalytics.io/mcp"
    }
  }
}

πŸ’‘ Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Install Tool Schemas (5) Directory Badge Claim listing AlternativesπŸ“Š More in Monitoring

Overview

The sudomichael/gizmoanalytics-mcp MCP server connects AI coding agents to Gizmo Analytics for cookieless website measurement. It provides 28 tools covering framework-aware installation, site setup, traffic queries, summaries, anomaly detection, and traffic-change explanations. The service runs at a hosted MCP endpoint and uses OAuth discovery or an admin bearer key rather than a local process. Reach for it when an agent needs to add analytics to a site or investigate traffic across one or more sites.

Use cases

β€’Install analytics in a Next.js site
β€’Query traffic by country and device
β€’Summarize performance across sites
β€’Investigate a sudden traffic change
β€’Verify that a tracking script loads

Key features

β€’Cookieless web analytics access
β€’Framework-aware installation workflows
β€’Cross-site traffic summaries
β€’Filterable traffic and event queries
β€’Anomaly and traffic-change analysis
β€’OAuth and admin-key authentication

Capabilities & Tool Schemas (5) ~22 tokensApproximate context cost of this server’s tool schemas (~4 chars/token), before any tool is called. Actual usage depends on your client and model.Self-reported Self-reportedParsed from the repository README, not verified against a live server β€” may be incomplete or out of date.

Inspect callable tools, capabilities, and parameters exposed to AI agents by Gizmoanalytics MCP.

create_site

Callable MCP tool function

get_install_snippet

Callable MCP tool function

summarize_all_sites

Callable MCP tool function

get_workspace_overview

Callable MCP tool function

get_site_traffic

Callable MCP tool function

How Gizmoanalytics MCP works

What sudomichael/gizmoanalytics-mcp MCP server does

The sudomichael/gizmoanalytics-mcp MCP server exposes Gizmo Analytics operations to AI coding agents through MCP. Gizmo Analytics is a cookieless web analytics service, so the server is intended for adding tracking to websites and querying the resulting data.

Its 28-tool surface covers two main areas. Installation and administration tools can create a site, produce an installation snippet, configure event tracking, add site tags, and work with goals or funnels. Analysis tools can summarize multiple sites, show workspace information, inspect site traffic, rank sites by growth, identify inactive sites, detect anomalies, explain traffic changes, and query dimensions such as pages, referrers, countries, devices, browsers, channels, cities, and AI sources.

How it works

The sudomichael/gizmoanalytics-mcp MCP server is hosted by Gizmo Analytics at https://gizmoanalytics.io/mcp; the repository documents the public MCP listing and does not provide a local runtime. An MCP-compatible client connects to that URL and discovers the available tools.

OAuth-aware clients can discover the authorization service through RFC 9728 metadata, open a browser consent flow, and store the resulting token. Clients without OAuth-aware discovery can send an Authorization: Bearer header containing an admin key. Tool requests then operate against the authenticated Gizmo Analytics workspace.

The installation workflow can combine site creation, a framework-specific tracking snippet, a suggested file location, and next steps. A verification operation checks whether the script is loading by fetching the site homepage. Query operations support custom date ranges and stacked filters, including combinations such as country and device filters.

Setup and configuration

To use the sudomichael/gizmoanalytics-mcp MCP server, add the hosted URL as an MCP server in the client’s MCP settings. Cursor, Claude Desktop, and Windsurf are named as clients that can use automatic discovery. No local package installation or local server process is required.

For manual configuration, place the hosted URL in the client’s MCP server configuration and provide a bearer token containing an admin key. The README directs users to the Gizmo Analytics dashboard’s keys page to obtain that key. OAuth is the preferred setup when the client supports MCP authorization discovery.

Tools and capabilities

Representative tools include:

  • create_site for adding a site.
  • get_install_snippet for retrieving tracking code.
  • summarize_all_sites for a cross-site summary.
  • get_workspace_overview for workspace-level information.
  • get_site_traffic for site traffic data.
  • setup_analytics_for_site for a combined installation workflow.
  • verify_install for checking whether tracking loads.

The broader inventory also includes event and badge snippets, site tags, goals, funnels, time-series queries, event queries, property breakdowns, top-page and referrer queries, and workflow tools for growth, anomalies, and traffic changes. Framework-aware installation is described for Next.js, Remix, SvelteKit, Nuxt, Astro, Vite, React, and plain HTML.

Limitations and notes

This repository is not a local MCP implementation that can be started from the checkout. It identifies and documents the hosted service, so use the hosted endpoint rather than looking for a local launch command. Authentication is required through OAuth or an admin bearer key. The provided material does not specify service pricing, data retention, rate limits, or detailed query schemas.

Read the full README β†’View source on GitHub β†’

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Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks β€” not a rating.

GitHub stars
1
Stargazers on the source repository.
Last commit
2mo ago
Most recent push to the default branch.
Tools exposed
5
Callable tools this server registers over MCP.
Directory activity
3 views
Config copies, upvotes, and views on AllMCPs.

Reviews

No reviews yet β€” be the first to share how this listing worked for you.

Frequently Asked Questions about Gizmoanalytics MCP

Add https://gizmoanalytics.io/mcp to an MCP-compatible client. The repository states that there is nothing to install or run locally.

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Technical Specs & Signals

CategoryπŸ“ŠMonitoring
PricingPaid
More technical detailsExpand β–Ύ
TransportSSE (Remote)
AuthOAuth
LicenseMIT
ClientsClaude Desktop, Cursor, Windsurf
Last updatedSep 7, 2026
9/10 checks healthy over the last 32d
Views3
Unique ViewsTotal visits recorded for this listing page on AllMCPs.
Installs0
Installs & Copy ActionsTotal times users copied install commands or configuration snippets for this server.
GitHub stars1
GitHub Star CountTotal stargazers on GitHub representing community popularity (1 stars).
Last commit2mo ago
Last Repository CommitThe most recent commit or push recorded for this server's GitHub repository.Last commit on Jun 19, 2026
56Quality signal: Good Β· 56/100How this signal is calculated β–Ύ
Server availabilityNot measured

Not scored for repo-hosted servers β€” we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20
Documentation & tools29/30
Adoption & activity3/15
Community engagement0/10

A guidance signal from public completeness & health data β€” not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

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