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title: 'MCP: lifecycle, capabilities, and trust boundaries'
seo_title: 'MCP: lifecycle, capabilities, and trust boundaries — video'
description: MCP separates host, clients, and servers; capability discovery does not remove authorization, validation, or trust boundaries.
keywords: MCP, Model Context Protocol, host, client, server, tools, resources, prompts, trust boundaries, authorization, lifecycle
date: '2026-09-12T00:00:00+00:00'
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    <h1>MCP: lifecycle, capabilities, and trust boundaries</h1><p>MCP separates host, clients, and servers; capability discovery does not remove authorization, validation, or trust boundaries.</p>
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    <div class="s5-video-watch__snippet-grid"><article><span>01</span><h2>1. Start with ownership: host, client, and server are not synonyms</h2><p>The MCP architecture defines three distinct roles.[^mcp-architecture]</p></article>
<article><span>02</span><h2>Host</h2><p>The host is the AI application: an IDE, desktop app, chat interface, internal agent, or another product that embeds the model experience.</p></article>
<article><span>03</span><h2>Client</h2><p>An MCP client lives inside the host and has a 1:1 relationship with one particular server.[^mcp-architecture]</p></article></div>
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<li><a href="?t=12" data-s5-video-seek="12"><time>0:12</time><span>Discovering capabilities does not authorize them</span></a></li>
<li><a href="?t=24" data-s5-video-seek="24"><time>0:24</time><span>Remote data does not inherit authority</span></a></li></ol></section>
  
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  <section class="s5-video-watch__related" aria-labelledby="related-videos-title"><div class="s5-video-watch__section-head"><span class="s5-eyebrow">Next step</span><h2 id="related-videos-title">Related videos</h2></div><div class="s5-video-watch__related-grid"><article><a href="https://5sigmas.com/en/videos/series/evaluating-ai-systems-production/06-observability-failure-taxonomies-production-eval-repair-feedback-loops/"><img src="https://5sigmas.com/en/series/evaluating-ai-systems-production/06-observability-failure-taxonomies-production-eval-repair-feedback-loops.jpg" alt="" loading="lazy" width="1280" height="720"><span>Other topics · 0:36</span><strong>Observability, failure taxonomies, and feedback loops</strong></a></article>
<article><a href="https://5sigmas.com/en/videos/series/evaluating-ai-systems-production/05-online-evaluation-shadow-canary-ab-guardrails-regression-gates/"><img src="https://5sigmas.com/en/series/evaluating-ai-systems-production/05-online-evaluation-shadow-canary-ab-guardrails-regression-gates.jpg" alt="" loading="lazy" width="1280" height="720"><span>Other topics · 0:36</span><strong>Online evaluation: shadow, canary, A/B, and regression gates</strong></a></article>
<article><a href="https://5sigmas.com/en/videos/series/evaluating-ai-systems-production/04-evaluacion-trayectorias-agentes-tools-exito-eficiencia-recuperacion-policy/"><img src="https://5sigmas.com/en/series/evaluating-ai-systems-production/04-evaluacion-trayectorias-agentes-tools-exito-eficiencia-recuperacion-policy.jpg" alt="" loading="lazy" width="1280" height="720"><span>Other topics · 0:36</span><strong>Agent trajectories: success, efficiency, recovery, and policy</strong></a></article></div></section>
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