Example proposal: cookieless analytics with native MCP integration for AI agents

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Valutazione

Difficoltà
5/5
Tempo stimato
Più di una settimana
Idoneità per principianti
35/100
Tipo di issue
Funzionalità
Chiarezza
Abbastanza chiara
Stato di attività
Tranquilla
Stack tecnologico
nextjs, typescript
Ambito
analytics, api, web-dev

Direzione di ricerca

Leggi prima gli esempi correlati solutions/script-component-strategies e solutions/script-component-ad, oltre a framework-boilerplates/xmcp. Conferma se l’esempio debba essere indipendente dal brand, brandizzato o aggiunto a una soluzione esistente prima di iniziare. Il lavoro è completato quando un esempio concordato dimostra il tracker di app/layout.tsx, la configurazione e le query MCP e una funzione Vercel per gli eventi personalizzati.

Scritto dal modello di indicizzazione a partire dal testo della issue.

Descrizione

Proposal

A solutions/ example showing how to integrate cookieless web analytics into a Next.js app, with native MCP so coding agents (Cursor, Claude, Codex, Windsurf) can install + query analytics in one prompt. Would slot in next to script-component-strategies and script-component-ad, which cover related <Script> patterns.

The framework already has framework-boilerplates/xmcp showing how to build an MCP server. This proposal is the complementary case: how to consume an MCP-aware analytics service from a Next.js app, end to end.

What the example would demonstrate

  1. Cookieless tracker installation — one <Script> in app/layout.tsx, gated on NEXT_PUBLIC_GIZMO_KEY. No cookie banner needed under CNIL/EDPB. afterInteractive strategy so the tracker doesn't compete with LCP.
  2. MCP server integration — the AI coding agent connects via the hosted MCP endpoint, OAuth onboarding via dynamic client registration (RFC 7591), and can run setup operations (setup_analytics_for_site, verify_install), workflow operations (summarize_all_sites, explain_traffic_change), and query primitives (filterable breakdowns, time series).
  3. Custom event tracking via Vercel functions — a small API route showing how to fire server-side events alongside the client tracker.

Why this is useful here

  • Vercel's audience increasingly uses AI coding agents — this is the only end-to-end example showing the "talk to your analytics from your editor" workflow.
  • Cookieless analytics is the de-facto choice for any EU-facing Next.js site that doesn't want a consent banner. There's no example covering that pattern today.
  • Builds naturally on script-component-strategies (script loading), which is the closest existing example.

Why I'm raising it as an issue first

I'd build this against Gizmo Analytics since that's the MCP-first analytics service I'm familiar with (free tier, MIT-licensed MCP server, hosted endpoint with full OAuth, official MCP Registry listed). But I don't want to assume a brand-specific example is what you want — wanted to check first.

Three paths I can take, ordered by preference:

  1. Brand-agnostic — solutions/cookieless-analytics-mcp using Gizmo as the concrete provider, with the README explicitly noting it's swappable for any MCP-aware analytics provider that follows the same <Script> + gizmoanalytics.io/mcp-style remote endpoint pattern.
  2. Branded — solutions/gizmo-analytics similar to how solutions/platforms-slate-supabase is brand-specific.
  3. Built into an existing example — fold the integration into one of the existing solutions/ examples (e.g., a blog template) as an opt-in analytics layer.

Happy to build whichever fits your conventions, or skip if it's not a fit. Just looking for a thumbs-up + direction before I spend the time.

Lingua principale
TypeScript
Stelle
5.2k
Fork
1.9k
Merge medio
1h 4m
PR unite (30g)
2

Preparare l'ambiente

  • Nessun Dockerfile né file Docker Compose
  • Ha un modello di pull request
  • Nessuna guida per i contributori

Come iniziare

  1. Leggi tutta la issue e poi la guida ai contributi del progetto.
  2. Commenta sulla issue per dire che te ne occupi tu — evita che due persone facciano lo stesso lavoro.
  3. Fai un fork del repository e lavora su un branch.
  4. Apri una pull request che faccia riferimento al numero della issue.

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