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      <title>Article: Building a Least-Privilege AI Agent Gateway for Infrastructure Automation with MCP, OPA, and Ephemeral Runners</title>
      <link>https://www.infoq.com/articles/building-ai-agent-gateway-mcp/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering-articles</link>
      <description>&lt;img src="https://res.infoq.com/articles/building-ai-agent-gateway-mcp/en/headerimage/building-ai-agent-gateway-mcp-header-1771417896950.jpg"/&gt;&lt;p&gt;This article presents a least-privilege AI Agent Gateway that places clear controls between AI agents and infrastructure. Agents do not access infrastructure APIs directly. Instead, every request is validated, authorized using policy as code with Open Policy Agent (OPA), and executed in short-lived, isolated environments, with built-in observability using OpenTelemetry.&lt;/p&gt; &lt;i&gt;By Nabin Debnath&lt;/i&gt;</description>
      <category>AIOps</category>
      <category>Agents</category>
      <category>AI Development</category>
      <category>Model Context Protocol (MCP)</category>
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      <pubDate>Mon, 23 Feb 2026 11:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/articles/building-ai-agent-gateway-mcp/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering-articles</guid>
      <dc:creator>Nabin Debnath</dc:creator>
      <dc:date>2026-02-23T11:00:00Z</dc:date>
      <dc:identifier>/articles/building-ai-agent-gateway-mcp/en</dc:identifier>
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      <title>Article: Architecting Agentic MLOps: a Layered Protocol Strategy with A2A and MCP</title>
      <link>https://www.infoq.com/articles/architecting-agentic-mlops-a2a-mcp/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering-articles</link>
      <description>&lt;img src="https://res.infoq.com/articles/architecting-agentic-mlops-a2a-mcp/en/headerimage/architecting-agentic-mlops-a2a-mcp-header-1770303550343.jpg"/&gt;&lt;p&gt;In this article, the authors outline protocols for building extensible multi-agent MLOps systems. The core architecture deliberately decouples orchestration from execution, allowing teams to incrementally add capabilities via discovery and evolve operations from static pipelines toward intelligent, adaptive coordination.&lt;/p&gt; &lt;i&gt;By Shashank Kapoor, Sanjay Surendranath Girija, Lakshit Arora&lt;/i&gt;</description>
      <category>MLOps</category>
      <category>Agents</category>
      <category>Agent2Agent</category>
      <category>Artificial Intelligence</category>
      <category>Development</category>
      <category>DevOps</category>
      <category>AI, ML &amp; Data Engineering</category>
      <category>article</category>
      <pubDate>Mon, 16 Feb 2026 09:00:00 GMT</pubDate>
      <guid>https://www.infoq.com/articles/architecting-agentic-mlops-a2a-mcp/?utm_campaign=infoq_content&amp;utm_source=infoq&amp;utm_medium=feed&amp;utm_term=AI%2C+ML+%26+Data+Engineering-articles</guid>
      <dc:creator>Shashank Kapoor, Sanjay Surendranath Girija, Lakshit Arora</dc:creator>
      <dc:date>2026-02-16T09:00:00Z</dc:date>
      <dc:identifier>/articles/architecting-agentic-mlops-a2a-mcp/en</dc:identifier>
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