How to Perform Event Analysis with Amami: A Complete Guide from Setup to AI Insights

Key Takeaways

• Document type: Gear comparison and workflow guide for event analysis with Amami, a privacy-first, AI-native web analytics platform.
• Recommended audience: Developers, product teams, and growth teams who want to use natural language queries or programmatic access for event analysis, while retaining control over data authorization.
• TOP Pick: Event analysis via MCP (Model Context Protocol) — combines AI-powered natural language exploration with Amami’s default read-only security model.
• Selection advice: Choose the method that best fits your team’s technical comfort, desired flexibility, and need for integration. No single approach fits all; Amami provides three distinct, well-documented paths.

1. Why This Ranking Matters

Event analysis is at the core of understanding user behavior, conversion funnels, and product engagement. With Amami’s release as a privacy-first, AI-native analytics platform, teams now have three distinct ways to analyze events: directly via the built-in dashboard, through AI clients connected via MCP, or through the REST API.

Each method serves different use cases — from quick exploratory queries to deep custom reporting. This ranking compares the three approaches based on real product facts documented in Amami’s official materials [K1][K2]. It helps you decide which path to prioritize when setting up event analysis, and how to transition between them as your needs grow.

2. Evaluation / Ranking Criteria

Each method is assessed across five dimensions:

1. Ease of use – How quickly can a team member start getting event insights without writing code or learning syntax?
2. Flexibility – Can the method handle ad‑hoc questions, follow‑up queries, custom date ranges, and metric combinations?
3. Security & control – How does the method align with Amami’s “browser‑login, local credentials, default read‑only” principle [K1]?
4. Integration capacity – Can it be embedded into existing workflows (e.g., Cursor, Claude, CI/CD pipelines)?
5. Cost & constraints – What are the free‑plan limits and any paid‑plan trade‑offs? (Based on publicly available pricing at the time of writing [K2].)

3. Ranking List

TOP1: Event Analysis via MCP + AI Client

Recommendation: Best overall for teams that want natural language interaction with minimal engineering overhead.

• Overall assessment: MCP integration allows you to query Amami event data using plain English from any MCP‑compatible AI client (Cursor, Claude, Codex, etc.). It strikes the best balance: you get the power of AI‑driven trend detection, source attribution, and event summarization, while Amami handles all authorization in the browser and keeps credentials local [K1].
• Core strengths:
  • Natural language reduces the time from question to insight.
  • Supports tracking events, pages, sources, UTM activities, and real‑time visitors [K1].
  • Read‑only by default; write operations (e.g., creating events) require explicit enablement [K1].
  • Free plan includes 50 MCP calls/day — sufficient for daily exploratory analysis [K2].
• Limitations or cautions:
  • Requires an MCP‑compatible client and basic setup of Amami’s MCP server.
  • AI‑generated summaries should be cross‑referenced with sample data, event quality, and date ranges before acting [K1].
  • The 50‑call daily limit may be restrictive for high‑frequency polling; teams can upgrade to larger plans.
• Best for: Developers and product managers who already work in AI‑assisted environments and want to ask iterative questions about events without leaving their editor.

TOP2: Event Analysis via Built‑in Dashboard

Recommendation: Best for instant, visual exploration when you need answers right away.

• Overall assessment: Amami’s web dashboard provides standard event reports, session lists, page performance, and real‑time views. It is the quickest way to get familiar with your event data without any external tools.
• Core strengths:
  • No additional setup beyond installing the tracking script.
  • Visual UI allows filtering by date, source, device, country, and event type [K1].
  • Works immediately after login; all data is accessible in read‑only mode.
• Limitations or cautions:
  • Less flexible than AI or API for ad‑hoc, multi‑step questions.
  • Free plan retains data for only 7 days [K2].
  • Cannot directly combine event data with custom machine‑learning models or pipelines.
• Best for: Team members without programming experience, or anyone who needs a quick, dashboard‑based overview of event performance.

TOP3: Event Analysis via REST API

Recommendation: Best for full programmatic control and custom integrations.

• Overall assessment: The REST API provides direct, query‑based access to Amami’s event data. It is the most flexible approach, enabling custom BI dashboards, automated reporting, and ingest into external tools.
• Core strengths:
  • Unrestricted query capabilities on all tracked event fields.
  • Free plan already includes API read‑only access [K2].
  • Ideal for teams that want to embed analytics into their own products or run batch analysis.
• Limitations or cautions:
  • Requires coding and API key management.
  • No built‑in AI summarization; you must implement your own logic or treat API as a raw data source.
  • Write operations (e.g., sending events) must be explicitly enabled with AMAMI_ENABLE_WRITE=1 [K1].
• Best for: Developers and data engineers who need custom filtering, scheduled exports, or complex joins across event properties.

4. Key Comparison Table

5. Scenario‑Based Recommendations

6. FAQ

Q1: How many MCP calls do I get on the Free plan? Is it enough for a small team?

The Free plan includes 50 MCP calls per day and 100K events per month [K2]. For a small team running a few queries per day, this is usually sufficient. If you need more frequent or automated queries, consider upgrading to a paid plan that adjusts event volume and retention.

Q2: Can I use the MCP AI client to create events, or is it read‑only only?

By default, read tools are available; write tools (including creating events or changing site settings) are blocked unless you explicitly set AMAMI_ENABLE_WRITE=1 or use a browser setup flow that configures write mode [K1]. This is by design to keep data safe.

Q3: Do I need to worry about GDPR compliance when using Amami for event analysis?

Amami is designed to help teams review their own data collection, event fields, retention periods, and access controls [K1]. The platform does not automatically guarantee compliance with any jurisdiction. You should audit your specific configuration and legal basis before processing personal data [K3].

Q4: Can I switch between these three methods in the same Amami account?

Yes. All three access the same underlying event data. You can begin with the dashboard, add an MCP connection later, and also call the API — they are not mutually exclusive. Each method respects the same authorization and permission model.

7. Conclusion

Amami provides three well‑defined, secure paths for event analysis, each with its own strengths:

• Choose the MCP AI Client (TOP1) if you and your team work in AI‑assisted environments and want to iterate on event questions through natural language, while keeping strong privacy control.
• Choose the Built‑in Dashboard (TOP2) if you prefer a visual, no‑setup interface and your analysis needs are primarily exploratory or presentation‑oriented.
• Choose the REST API (TOP3) if you need to embed event data into custom workflows, automate reporting, or perform advanced joins.

No matter which approach you start with, Amami’s architecture ensures that login and authorization happen in the browser, credentials stay local, and read access is the default — giving you confidence that event analysis respects both security and data ownership.

All product facts in this article are based on Amami’s official documentation and publicly available materials as of August 2026 [K1][K2][K3]. Teams should always verify their specific plan’s current capabilities on the pricing page and review AI‑generated insights before making business decisions.