--- 格式版本: 2 标题: "MCP server – Plugins | OpenAI Developers" 原文链接: "https://developers.openai.com/plugins/concepts/mcp-server" 发布日期: "2026-09-04" 发布时间校准状态: "found" 发布时间需复核: "否" 发布时间来源: "rule:local:strict_original_body" 发布时间证据: "Published Time: Fri, 04 Sep 2026 04:44:12 GMT" 发布时间校准原因: "规则确认唯一严格发布时间，来源 local:strict_original_body" 发布时间校准置信度: "high" 发布时间候选数量: 4 发布时间严格候选数量: 1 发布时间原页读取状态: "source template page reused from URL open" 发布时间未找到原因: "" 发布时间校准时间: "2026-09-04T16:28:52+08:00" 发布时间仲裁状态: "skipped" 发布时间仲裁尝试次数: 0 发布时间仲裁耗时毫秒: 0 发现时间: "2026-09-04T16:24:00+08:00" 入库时间: "2026-09-04T08:28:52.257Z" 来源平台: "固定入口" 搜索渠道: "fixed_url" 搜索词: "https://developers.openai.com/blog" 匹配关键词: - "deployment" - "performance" - "latency" - "throughput" - "AI" 相关厂家: - "OpenAI" - "Microsoft" - "AWS" - "Google" - "Oracle" 相关专家: [] 内容类型: "网页" 抓取工具: "Jina Reader" 清洗工具: "Jina Reader Markdown + Defuddle/Readability 正文提取" 原始附件: [] AI优质: "否" AI打分: 33 AI分档: "非优质" AI质检状态: "不通过" AI打分理由: "正文为OpenAI官方开发者文档，介绍MCP服务器概念、工具调用流程和传输认证方式，属于AI应用插件开发教程。主题完全不涉及超节点、AI Rack或机架级基础设施，无新架构、标准、量产或部署信号。虽来源权威且页面完整，但命中教程与运维选型否决，整体仅作为通用AI软件开发资料，不进入超节点业务情报库。" AI质检模型: "zj-deepseek-v4-flash" AI质检时间: "2026-09-04T16:39:38+08:00" AI主题相关性: 1 AI来源权威性: 15 AI新颖性: 5 AI技术细节: 5 AI商业部署信号: 0 AI完整性: 7 AI评分提示词版本: "v17-精简生产版" AI评分提示词SHA256: "48fb9777f386026761b4873eaff30807694fb11e9b352d7c69bf2dfde750cc7d" AI评分知识库版本: "knowledge_base_v1-20260819+runtime.87" AI评分知识库SHA256: "0cf9900cb3e9d03b3f4c39f45979aac6e2d5c789a68d1b2802c9dab62cd2710e" AI评分知识库检索词: "[\"OpenAI\",\"https://developers.openai.com/blog\",\"RAS\",\"NPU\",\"Google\",\"Meta\",\"Microsoft\",\"MCP\",\"URL\",\"GMT\",\"HTTPS\",\"HTTP\"]" AI评分知识库命中: "[{\"id\":\"july-correct-0033\",\"title\":\"Microsoft, Alphabet, Meta Pivot from Buy to Build in AI\",\"sourceType\":\"labeled_article\",\"time\":\"2026-07\",\"matchedTerms\":[\"OpenAI\",\"RAS\",\"Google\",\"Meta\",\"Microsoft\",\"URL\",\"HTTPS\",\"HTTP\"],\"rank\":-18.42431063812961},{\"id\":\"july-correct-0001\",\"title\":\"全球首颗2nm GPU来了！苏姿丰甩出“最强AI机架”，CPU性能干翻英伟达 - 智东西\",\"sourceType\":\"labeled_article\",\"time\":\"2026-07\",\"matchedTerms\":[\"OpenAI\",\"RAS\",\"NPU\",\"Meta\",\"HTTPS\",\"HTTP\"],\"rank\":-12.872515030312233},{\"id\":\"july-correct-0018\",\"title\":\"AMD, Cerebras partner on joint Helios rack-scale AI inference platform\",\"sourceType\":\"labeled_article\",\"time\":\"2026-07\",\"matchedTerms\":[\"OpenAI\",\"RAS\",\"Meta\",\"Microsoft\",\"URL\",\"HTTPS\",\"HTTP\"],\"rank\":-12.387315215688663},{\"id\":\"july-correct-0015\",\"title\":\"AMD to join the optical interconnect party with 2027 Instinct GPUs\",\"sourceType\":\"labeled_article\",\"time\":\"2026-07\",\"matchedTerms\":[\"OpenAI\",\"Meta\",\"Microsoft\",\"URL\",\"HTTPS\",\"HTTP\"],\"rank\":-12.267406418970474},{\"id\":\"july-correct-0112\",\"title\":\"超前点映AMD Advancing AI 2026：AMD AI YES？-36氪\",\"sourceType\":\"labeled_article\",\"time\":\"2026-07\",\"matchedTerms\":[\"OpenAI\",\"Meta\",\"Microsoft\",\"URL\",\"HTTPS\",\"HTTP\"],\"rank\":-11.979668620298701}]" 采集批次: "2026年9月4日15点53分07秒" 采集批次ID: "20260904-155307-58ad1755" 去重键: "https://developers.openai.com/plugins/concepts/mcp-server" --- Title: MCP server – Plugins | OpenAI Developers URL Source: https://developers.openai.com/plugins/concepts/mcp-server Published Time: Fri, 04 Sep 2026 04:44:12 GMT Markdown Content: For the complete documentation index, see [llms.txt](https://developers.openai.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to the page URL. 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plugin](https://developers.openai.com/plugins/deploy/connect-chatgpt) * [Submit and publish](https://developers.openai.com/plugins/deploy/submission) * [Submission error reference](https://developers.openai.com/plugins/deploy/submission-errors) ### Conversion specs * [Restaurant reservation spec](https://developers.openai.com/plugins/guides/restaurant-reservation-conversion-spec) * [Get Quote spec](https://developers.openai.com/plugins/guides/local-services-request-quote-conversion-spec) * [Product checkout spec](https://developers.openai.com/plugins/guides/product-checkout-conversion-spec) ### Guides * [UI guidelines](https://developers.openai.com/plugins/concepts/ui-guidelines) * [Optimize Metadata](https://developers.openai.com/plugins/guides/optimize-metadata) * [Submit a Claude Code plugin](https://developers.openai.com/plugins/guides/submit-claude-plugin) * [Security & Privacy](https://developers.openai.com/plugins/guides/security-privacy) * [Troubleshooting](https://developers.openai.com/plugins/deploy/troubleshooting) ### Resources * [Changelog](https://developers.openai.com/plugins/changelog) * [Plugin guidelines](https://developers.openai.com/plugins/app-guidelines) * [MCP server review requirements](https://developers.openai.com/plugins/deploy/app-review) * [Plugin UI reference](https://developers.openai.com/plugins/reference) * [Checkout API reference](https://developers.openai.com/plugins/build/monetization) Copy Page # MCP server Understand how an MCP server gives a plugin tools and access to external systems. Copy Page The [Model Context Protocol](https://modelcontextprotocol.io/) (MCP) is an open specification for connecting AI clients to external tools and data. A plugin can include an MCP server when it needs to read live information, take actions, or integrate with another service. The MCP server is optional. A plugin that only provides instructions and resources can consist of [skills](https://developers.openai.com/plugins/concepts/skills) alone. ## What an MCP server provides An MCP server can expose: * **Tools:** Functions the model can call with structured inputs. * **Resources:** Data or content the client can read. * **Prompts:** Reusable prompt templates. * **Instructions:** Server-wide guidance for using its capabilities. Plugins primarily use tools. Each tool has a name, description, input schema, and optional output schema. These fields help the model decide when to call the tool and how to use its result. ## How tool calls work When a user asks for something that matches a tool: 1. The client discovers the tools exposed by the MCP server. 2. The model selects a tool and supplies arguments that match its input schema. 3. The server validates the request, performs the operation, and returns a result. 4. The model uses the result to continue the conversation. Tool results should work without custom UI. Return concise text or structured content that gives the model enough information to answer the user. An MCP server can also return an optional UI resource for clients that support [MCP Apps](https://developers.openai.com/plugins/build/chatgpt-ui#start-with-mcp-apps). ## Transport and authorization Deploy production MCP servers at stable HTTPS endpoints using the streamable HTTP transport. If tools access private data or perform actions for a user, protect the server with the authorization flow defined by the MCP specification. For protocol details, see the [MCP specification](https://modelcontextprotocol.io/specification). The [Python](https://github.com/modelcontextprotocol/python-sdk) and [TypeScript](https://github.com/modelcontextprotocol/typescript-sdk) software development kits provide server implementations and helpers. ## Next step After defining the tools your plugin needs, [build the MCP server](https://developers.openai.com/plugins/build/mcp-server). [Previous Skills](https://developers.openai.com/plugins/concepts/skills) Ask AI ## Docs agent Loading docs agent...