zoom/zoom-plugin · Archived

choose-zoom-approach

Choose the right Zoom architecture for a use case. Use when deciding between REST API, Webhooks, WebSockets, Meeting SDK, Video SDK, Zoom Apps SDK, Zoom MCP, Phone, Contact Center, or a hybrid approach.

First seen May 11, 2026

Installation

$ npx skills add zoom/zoom-plugin --skill choose-zoom-approach

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More details

Agent compatibility

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Repository health

Stars 5
License LICENSE
Default branch main
Open issues 2
Status Archived

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 1,861 B
  • docs SUMMARY.md 230 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 2 installs

SKILL.md

Choose Zoom Approach

Pick the smallest correct Zoom surface for the job, then layer in only the supporting pieces that are actually required.

Decision Framework

Problem Type Primary Zoom Surface
Deterministic backend automation, account management, reporting, scheduled jobs [rest-api](../rest-api/SKILL.md)
Event delivery to your backend [webhooks](../webhooks/SKILL.md) or [websockets](../websockets/SKILL.md)
Embed Zoom meetings into your app [meeting-sdk](../meeting-sdk/SKILL.md)
Build a fully custom video experience [video-sdk](../video-sdk/SKILL.md)
Build inside the Zoom client [zoom-apps-sdk](../zoom-apps-sdk/SKILL.md)
AI-agent tool workflows over Zoom data [zoom-mcp](../zoom-mcp/SKILL.md)
Real-time media extraction or meeting bots [rtms](../rtms/SKILL.md) plus [meeting-sdk](../meeting-sdk/SKILL.md) when needed
Phone workflows [phone](../phone/SKILL.md)
Contact Center or Virtual Agent flows [contact-center](../contact-center/SKILL.md) or [virtual-agent](../virtual-agent/SKILL.md)

Guardrails

  • Do not recommend Video SDK when the user actually needs Zoom meeting semantics.
  • Do not recommend Meeting SDK when the user needs a fully custom session product.
  • Do not replace deterministic backend automation with MCP-only guidance.
  • Prefer hybrid rest-api + zoom-mcp when the user needs both stable system actions and AI-driven discovery.

What To Produce

  • One recommended path
  • Minimum supporting components
  • Hard constraints and tradeoffs
  • Immediate next implementation step