Language:JapaneseEnglish

amplitude Claude Code Plugin

Category
Monitoring
Topics
Monitoring & Observability · Data Engineering & Analytics · Sales, Marketing & Business Ops
First cataloged
2026-07-09 (UTC)
Explanation last updated
2026-09-02 (UTC)
Source (GitHub) last updated
2026-09-04 (UTC) (yesterday)

The explanation below is AI-generated. Please verify it against the sources.

This plugin adds a set of Amplitude-focused skills to Claude Code, Cursor, or Claude CLI by connecting to the Amplitude MCP server. It lets users create and analyze charts and dashboards, design and monitor experiments, synthesize customer feedback, and assess account health directly through natural-language requests. It also supports generating daily and weekly briefings and mining analytics, experiments, and feedback to surface prioritized product opportunities. Additionally, it can inspect code diffs and existing tracking patterns to plan and carry out analytics instrumentation work. According to the README, it requires an MCP-compatible client, Node.js, and an Amplitude account with API access.

About the service

Amplitude is a product analytics platform, described on its homepage as covering product analytics, session replay, heatmaps, feature and web experimentation, feature management, and related data tooling, used here as the data source the plugin's skills query and act on.

What you can do with amplitude

  • Analyze existing charts or dashboards to explain trends, anomalies, or talking points
  • Create new charts and dashboards from natural-language descriptions
  • Design, monitor, and evaluate A/B experiments, including ship/no-ship recommendations
  • Synthesize customer feedback into grouped themes with supporting quotes
  • Summarize B2B account health, usage trends, and risk or expansion signals
  • Receive daily or weekly briefings covering metric changes, experiments, feedback, and deployments
  • Discover and prioritize product opportunities scored using the RICE framework
  • Inspect code diffs and existing tracking conventions to plan and implement analytics instrumentation

Sources

Back to list