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      <title>MCP 协议实战：给 AI Agent 接上运维工具</title>
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      <pubDate>Fri, 27 Feb 2026 09:52:00 +0800</pubDate>
      <author>17691281867@163.com (Wenzhuo Huang)</author>
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      <description>Model Context Protocol 让 AI 能够标准化地调用外部工具。本文用 Python 实现一个运维 MCP Server，接入 kubectl、Prometheus、Loki，让 AI 直接查集群状态。</description>
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      <title>LangGraph 工作流编排：构建有状态的 AI 应用</title>
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      <pubDate>Sun, 15 Feb 2026 12:44:00 +0800</pubDate>
      <author>17691281867@163.com (Wenzhuo Huang)</author>
      <guid>https://socake.github.io/posts/langgraph-workflow-orchestration/</guid>
      <description>从LangChain Chain的局限出发，讲清楚LangGraph的状态机模型、Graph/Node/Edge的设计方式，以及条件分支、循环、人工介入、Checkpoint持久化的工程实现，最后用一个运维诊断工作流串起来所有概念。</description>
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      <title>AI Agent 设计模式：从单步到复杂工作流</title>
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      <pubDate>Thu, 29 Jan 2026 09:17:00 +0800</pubDate>
      <author>17691281867@163.com (Wenzhuo Huang)</author>
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      <description>Agent不是更智能的ChatGPT调用，它是一个能自主规划和执行多步骤任务的循环系统。本文拆解ReAct推理循环、Tool调用设计原则、Multi-Agent协作模式、Human-in-the-loop设计，以及告警分析Agent和巡检Agent的实战实现。</description>
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