<?xml version="1.0" encoding="utf-8" standalone="yes"?>
<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/">
  <channel>
    <title>#MCPSecurity on Home</title>
    <link>https://yakinin.com/en/tags/%23mcpsecurity/</link>
    <description>Recent content in #MCPSecurity on Home</description>
    <generator>Hugo -- 0.148.2</generator>
    <language>en</language>
    <lastBuildDate>Wed, 06 Aug 2025 00:00:00 +0000</lastBuildDate>
    <atom:link href="https://yakinin.com/en/tags/%23mcpsecurity/index.xml" rel="self" type="application/rss+xml" />
    <item>
      <title>Why Docker Calls MCP a &#39;Security Nightmare&#39;—And How to Fix It</title>
      <link>https://yakinin.com/en/posts/20250806-docker-warns-mcp-security-risks/</link>
      <pubDate>Wed, 06 Aug 2025 00:00:00 +0000</pubDate>
      <guid>https://yakinin.com/en/posts/20250806-docker-warns-mcp-security-risks/</guid>
      <description>&lt;h1 id=&#34;why-docker-calls-mcp-a-security-nightmareand-how-to-fix-it&#34;&gt;Why Docker Calls MCP a &amp;lsquo;Security Nightmare&amp;rsquo;—And How to Fix It&lt;/h1&gt;
&lt;p&gt;The Model Context Protocol (MCP) was introduced as a universal standard—the &amp;ldquo;USB-C for AI applications&amp;rdquo;—to allow AI agents to seamlessly interact with external tools, APIs, and data. Major players like Microsoft, Google, and OpenAI quickly adopted it, and thousands of MCP server tools emerged. The promise was simple: write an integration once, and any AI agent can use it.&lt;/p&gt;</description>
    </item>
  </channel>
</rss>
