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amplitude Claude Code Plugin

Category
Monitoring
Topics
Monitoring & Observability · Data Engineering & Analytics · Sales, Marketing & Business Ops
License
MIT(opens in a new tab)
Version
not stated (updated per commit) · Details
First cataloged
2026-07-09 (UTC)
Explanation last updated
2026-10-16 (UTC)
Source (GitHub) last updated
2026-10-30 (UTC) (5 days ago)

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

This plugin connects Claude Code, Cursor, or Claude CLI to Amplitude's MCP server, giving Claude a set of skills for working with Amplitude's product-analytics data as an analyst and instrumentation assistant. According to the README, it can create and analyze charts and dashboards, review and monitor experiments, synthesize customer feedback, and assess account health. It also supports engineering-facing workflows such as inspecting code diffs, discovering tracking patterns, planning new event instrumentation, and auditing stale tracking events for cleanup. It produces daily and weekly briefings and can surface prioritized product opportunities from combined analytics, experiment, and feedback data. Using it requires an MCP-compatible client, Node.js, and an Amplitude account with API access.

About the service

Amplitude is a product analytics platform that, per its homepage, offers product and marketing analytics, session replay, heatmaps, feature and web experimentation, feature management, and AI-driven agent tools for analyzing user and product behavior data.

What you can do with amplitude

  • Review B2B account usage, engagement, and risk signals
  • Investigate trends and anomalies within a specific chart
  • Turn a dashboard's data into a concise summary with key concerns
  • Design or evaluate A/B experiments with statistical interpretation
  • Group customer feedback into themes such as requests, bugs, or praise
  • Build new charts from a plain-language description
  • Assemble a dashboard from stated goals or requirements
  • Generate daily and weekly briefings covering metrics, experiments, and feedback
  • Translate a code diff or feature request into an event-tracking plan
  • Inspect a codebase's existing tracking conventions before adding events
  • Identify candidate deletion targets for outdated tracking events and properties
  • Monitor running and recently finished experiments and flag the most important ones
  • Surface and prioritize product opportunities using RICE scoring across data sources

Sources

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