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    <title>InfoQ - Model Context Protocol (MCP)</title>
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    <description>InfoQ Model Context Protocol (MCP) feed</description>
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      <title>GitLab 19.5 Makes Agentic Development a Governed Part of the DevOps Platform</title>
      <link>https://www.infoq.com/news/2026/11/gitlab-19-5-agentic-platform/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Model+Context+Protocol+%28MCP%29</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/11/gitlab-19-5-agentic-platform/en/headerimage/generatedHeaderImage-1793095997884.jpg"/&gt;&lt;p&gt;GitLab 19.5, released on October 15, puts agentic software development and governance at the centre of the platform, making its GitLab MCP server generally available while expanding how external AI agents can interact with GitLab.&lt;/p&gt; &lt;i&gt;By Craig Risi&lt;/i&gt;</description>
      <category>GitLab</category>
      <category>AI coding agents</category>
      <category>Model Context Protocol (MCP)</category>
      <category>Agents</category>
      <category>Agentic Development Lifecycle</category>
      <category>DevOps</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>news</category>
      <pubDate>Fri, 06 Nov 2026 12:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/11/gitlab-19-5-agentic-platform/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Model+Context+Protocol+%28MCP%29</guid>
      <dc:creator>Craig Risi</dc:creator>
      <dc:date>2026-11-06T12:00:00Z</dc:date>
      <dc:identifier>/news/2026/11/gitlab-19-5-agentic-platform/en</dc:identifier>
    </item>
    <item>
      <title>Edera's Object Capability Bounded Authority Promises to Isolate Credentials From AI Agent Workloads</title>
      <link>https://www.infoq.com/news/2026/11/ai-credentials-isolation/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Model+Context+Protocol+%28MCP%29</link>
      <description>&lt;img src="https://res.infoq.com/news/2026/11/ai-credentials-isolation/en/headerimage/generatedHeaderImage-1793853184587.jpg"/&gt;&lt;p&gt;Edera announced Object Capability Bounded Authority, a security model that separates an AI agent's or MCP server's required authority from the credentials behind it. Hypervisor-enforced capabilities limit agents to specific actions without storing secrets in the workload. Initial releases cover scoped command execution and workload identity; credential-brokered API access will follow.&lt;/p&gt; &lt;i&gt;By Olimpiu Pop&lt;/i&gt;</description>
      <category>Information Security</category>
      <category>AI Security</category>
      <category>Model Context Protocol (MCP)</category>
      <category>Containers</category>
      <category>Development</category>
      <category>DevOps</category>
      <category>news</category>
      <pubDate>Fri, 06 Nov 2026 06:06:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/11/ai-credentials-isolation/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Model+Context+Protocol+%28MCP%29</guid>
      <dc:creator>Olimpiu Pop</dc:creator>
      <dc:date>2026-11-06T06:06:00Z</dc:date>
      <dc:identifier>/news/2026/11/ai-credentials-isolation/en</dc:identifier>
    </item>
    <item>
      <title>Uber Builds MCP Gateway to Govern Access to 800+ Servers and 5,000+ AI Agent Tools</title>
      <link>https://www.infoq.com/news/2026/11/uber-mcp-gateway-ai-agents/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Model+Context+Protocol+%28MCP%29</link>
      <description>&lt;img src="https://www.infoq.com/styles/static/images/logo/logo_bigger.jpg"/&gt;&lt;p&gt;Uber has built an MCP Gateway to standardize how AI agents discover and invoke internal services across more than 800 MCP servers and 5,000 tools. The gateway separates tool registration from runtime execution and includes automated API discovery, access controls, sensitive data redaction, incremental tool discovery through Omni MCP, and response filtering.&lt;/p&gt; &lt;i&gt;By Leela Kumili&lt;/i&gt;</description>
      <category>gRPC</category>
      <category>Thrift</category>
      <category>REST</category>
      <category>Service Discovery</category>
      <category>API Gateway</category>
      <category>Model Context Protocol (MCP)</category>
      <category>Distributed Systems</category>
      <category>Microservices</category>
      <category>Infrastructure</category>
      <category>Agents</category>
      <category>Architecture &amp; Design</category>
      <category>Development</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>news</category>
      <pubDate>Mon, 02 Nov 2026 13:53:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/11/uber-mcp-gateway-ai-agents/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Model+Context+Protocol+%28MCP%29</guid>
      <dc:creator>Leela Kumili</dc:creator>
      <dc:date>2026-11-02T13:53:00Z</dc:date>
      <dc:identifier>/news/2026/11/uber-mcp-gateway-ai-agents/en</dc:identifier>
    </item>
    <item>
      <title>DoorDash Cuts Grocery Reorder Latency from 16 to 2 Seconds with AI Agents</title>
      <link>https://www.infoq.com/news/2026/10/doordash-ai-grocery-reorder/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Model+Context+Protocol+%28MCP%29</link>
      <description>&lt;img src="https://www.infoq.com/styles/static/images/logo/logo_bigger.jpg"/&gt;&lt;p&gt;DoorDash reduced grocery reorder latency from 16 to 2 seconds by precomputing recurring purchase needs using batch LLM inference and deterministic validation. Live catalog resolution keeps product selections current, while an editable shopping interface avoids unnecessary model calls. The company reports that shopping list views doubled and the flow’s order rate increased by approximately 34%&lt;/p&gt; &lt;i&gt;By Leela Kumili&lt;/i&gt;</description>
      <category>Agentic AI Architecture</category>
      <category>Orchestration</category>
      <category>API Gateway</category>
      <category>Model Context Protocol (MCP)</category>
      <category>AI Architecture</category>
      <category>Data Catalog</category>
      <category>Model Inference</category>
      <category>Low Latency</category>
      <category>Agents</category>
      <category>Large language models</category>
      <category>Architecture &amp; Design</category>
      <category>Development</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>news</category>
      <pubDate>Fri, 30 Oct 2026 13:31:00 GMT</pubDate>
      <guid>https://www.infoq.com/news/2026/10/doordash-ai-grocery-reorder/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Model+Context+Protocol+%28MCP%29</guid>
      <dc:creator>Leela Kumili</dc:creator>
      <dc:date>2026-10-30T13:31:00Z</dc:date>
      <dc:identifier>/news/2026/10/doordash-ai-grocery-reorder/en</dc:identifier>
    </item>
    <item>
      <title>Article: InfoQ AI, ML and Data Engineering Trends Report - 2026</title>
      <link>https://www.infoq.com/articles/ai-ml-data-engineering-trends-2026/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Model+Context+Protocol+%28MCP%29</link>
      <description>&lt;img src="https://res.infoq.com/articles/ai-ml-data-engineering-trends-2026/en/headerimage/ai-ml-de-graph-2026-1793191771570.jpg"/&gt;&lt;p&gt;This InfoQ Trends Report offers readers a comprehensive overview of emerging trends and technologies in the areas of AI, ML, and Data Engineering. This report summarizes the InfoQ editorial team’s and external guests' view on the current trends in AI and ML technologies and what to look out for in the next 12 months.&lt;/p&gt; &lt;i&gt;By Srini Penchikala, Chip Huyen, Daniel Dominguez, Hien Luu, Arthur Casals&lt;/i&gt;</description>
      <category>InfoQ Trends Report 2026</category>
      <category>Robotics</category>
      <category>AI coding agents</category>
      <category>Agent2Agent</category>
      <category>Model Context Protocol (MCP)</category>
      <category>Artificial Intelligence</category>
      <category>InfoQ Trends Report</category>
      <category>Large language models</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>article</category>
      <pubDate>Fri, 30 Oct 2026 09:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/articles/ai-ml-data-engineering-trends-2026/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Model+Context+Protocol+%28MCP%29</guid>
      <dc:creator>Srini Penchikala, Chip Huyen, Daniel Dominguez, Hien Luu, Arthur Casals</dc:creator>
      <dc:date>2026-10-30T09:00:00Z</dc:date>
      <dc:identifier>/articles/ai-ml-data-engineering-trends-2026/en</dc:identifier>
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    <item>
      <title>Podcast: AI, ML, and Data Engineering InfoQ Trends Report 2026</title>
      <link>https://www.infoq.com/podcasts/ai-ml-data-engineering-trends-2026/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Model+Context+Protocol+%28MCP%29</link>
      <description>&lt;img src="https://res.infoq.com/podcasts/ai-ml-data-engineering-trends-2026/en/smallimage/trend-reports-thumbnail-1793181579584.jpg"/&gt;&lt;p&gt;In this episode, members of the InfoQ AI and ML editorial staff and friends of InfoQ discuss the current trends in the domain of AI, ML and Data Engineering. One of the regular features of InfoQ are the trends reports, which each focus on a different aspect of software dev. These reports provide the InfoQ readers and listeners with a high-level overview of the topics to pay attention to this year.&lt;/p&gt; &lt;i&gt;By Chip Huyen, Daniel Dominguez, Hien Luu, Arthur Casals&lt;/i&gt;</description>
      <category>The InfoQ Podcast</category>
      <category>InfoQ Trends Report 2026</category>
      <category>Multi-Model Databases</category>
      <category>Model Context Protocol (MCP)</category>
      <category>Artificial Intelligence</category>
      <category>Spec Driven Development</category>
      <category>Robotics</category>
      <category>Agent2Agent</category>
      <category>AI Harness</category>
      <category>Context Engineering</category>
      <category>InfoQ Trends Report</category>
      <category>Frontier Model</category>
      <category>Large language models</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>podcast</category>
      <pubDate>Fri, 30 Oct 2026 09:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/podcasts/ai-ml-data-engineering-trends-2026/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=Model+Context+Protocol+%28MCP%29</guid>
      <dc:creator>Chip Huyen, Daniel Dominguez, Hien Luu, Arthur Casals</dc:creator>
      <dc:date>2026-10-30T09:00:00Z</dc:date>
      <dc:identifier>/podcasts/ai-ml-data-engineering-trends-2026/en</dc:identifier>
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