OCT. 14, 2026 (英语).
去年12月，我们在Apigee对 MCP 支持的宣布预览：将您已经拥有的 API 转换、 安全化、 管理和编目为 AI agents 能够发现和调用的工具的能力，不写入代码或站立您自己的 MCP 服务器。 客户的回答是立即的，第一个问题是：“我的跑步时间到底住在哪里？”
对于许多Apigee 客户来说，运行时间并非偶然生活在Google管理的基础设施上。 它住在他们自己的数据中心里，在一个合用设施里，或者在另一个公共云里，因为一个调节器需要它，因为记录系统离三个架子很远，或者因为一个多云产业只是企业的现实。 客户并没有问他们是否想要代理进入他们的API. 他们问他们能不能不动跑步时间就拿到它
现在他们可以了。 与Apigee杂交1.17.0，发布于2026年9月14日，模型背景协议支持在Apigee杂交，MCP数据平面运行在你自己的Kubernetes集群内。
概念模型是我们在阿皮吉运送的，没有改变。 您用 OpenAPI 3. 0.x 的规格描述您的 API，并从中创建 MCP 发现代理。 光谱中的每个操作都成为MCP工具。 Agents在JSON-RPC上与端点交谈，使用工具/列表来发现可用的，并使用工具/呼叫来引用它，Apigeee处理协议和转码。 您不写入 MCP 服务器代码，也不将 MCP 服务器作为单独的软件块运行，并且有自己的生命周期。
混合体的变化是工作发生的地方。 在Apigee混合体中，MCP数据平面运行在自己的Kubernetes集群内。 Apigee 控制平面从您的 OpenAPI 规格生成 MCP 工具配置，您的集群定期获取配置，MCP 请求流量不会离开集群。 显示以下的图，MCP数据平面在每个部署模型中运行。
该建筑的两种特性值得直言，因为它们是你安全审查小组要问的。
MCP请求交通停留在您的集群。 兹Q 1Z的工具/呼叫请求完全在自己的基础设施内接收，授权和代理到你的后端。 无MCP请求或响应在请求时间跨越边界到Google云。
配置被拉动，而不是按住。 与 MCP 数据平面并列的侧车( 从您的集群内) 伸展到获取从您的光谱中得出的工具配置。 Apigee控制平面(在Google Cloud)从未启动连接到你的集群，这意味着MCP不需要从Google进入您的网络的进入路径。
- 代理端点运行你的API已经运行。 Apigee 杂交已经允许您在您选择的 Kubernetes 平台上托管运行时间，MCP 继承了它。 MCP侧车重新使用已有的阿比盖-观察器身份。 没有新的Google服务账户可以创建，也没有新的IAM角色可以授予。 每一个组织一个控制飞机赠款以及你已经拥有的身份其余的都是
- 数据存储和主权状态延续。 Apigee混合式的MCP供订阅和评价组织使用，包括数据居住(由组织设置)支持的组织。 在混合式上，配置是从您的控制平面位置获取的，运行时请求路径通过构建留在您的集群中。 对于受到"请求不得离开这个管辖范围，这个设施，或这个VPC"约束的团队，这种约束得到了架构的支持，而不是一个设置的支持。
- 你已经写的治理适用于agents。 MCP端点是Apigee代理，因此它们继承了平台：OAuth 2.0和OpenID Connect,API密钥验证以及Apigee的内置政策库。 工具级控制来自您已经使用的概念，API产品。 您列出客户端有权获得的特定工具操作，可选用每个工具配额，Apigeee 执行它。 它还会自动过滤发现。 当客户端调用工具/列表时，响应中只包含该客户端API产品中的工具。 agent 如果从未被允许看到，则不能调用删除账户。
- 你的代理流量显示在你的API流量。 部署的 MCP 发现代理自动被摄入Appigee API 中枢，将 MCP API 样式及其操作映射到单个工具上，这是开发者可以用自然语言查询的可搜索目录，而不是一个端点的电子表格。 在API的洞察力中，两个滤波器，API风格和MCP工具名称允许您从普通的REST流量中分离出代理流量，并查看一个跨越API性能，错误分析，耐久性和目标性能仪表板的单一工具。 可以看到发现与执行的比例，除了后端时间之外，还可以分辨代理管理费用。
MCP是Apigee杂交中的可选功能，默认不能启用。 启用它是一个已经在运行 Apigeee 混合1.17.0 的集群上的 Helm 操作。 这样做的步骤如下。
设置顶级启用McpServer：您的覆盖中的真实密钥。 雅姆尔，然后首先升级Apigee-operator图，第二升级Apigee-org图。 令诸有情。 操作员图拥有新MCP资源的计划，并按错误的顺序升级，以没有MCP的吊舱产生成功的升级。 还有一个一次性的，每个组织给予的，新增的apigee-watcher身份给您的组织控制飞机进入，所以侧车可以检索配置。 默认是明智的出框。 2台MCP复制机，自动升级为10台。 回滚是同一个场设置为假的，是单一的图表升级。
在你安排改变之前做一些计划使MCP能够或丧失功能，触发一个舞台金丝雀释放运行时的吊舱，所以在经过批准的维护窗口中运行。 这里的公开文献描述了如何在现有的Apigee混合组中启用MCP.
您的 MCP 代理被曝光为单个端点。 每个agent请求，无论它引用何种工具，都到达相同的/mcp路径。 Apigee 标记了其中每个请求，名称是被调用的工具，因此 API 洞察力可以通过工具破解一个端点，并显示您 agents 实际使用的哪些工具，频率和期限。 显示 API洞察力下方的截图，包括向MCP代理(mcp)提出的请求，还可以看到单个工具(作为API代理mcp-保健，mcp-petstore,mcp-statuscode)响应时间和tps. 参见关于监控和分析mcp流量的公开文献，这里和这里都有关于如何使用API透视仪表板的Apigee API的见解。
我们还在下面的API见解中看到工具在工具性能标签中被调用。
MCP工具调用过一个AI客户端，Apigee和你的后端。 问询平台团队实际上问“时间去了哪里？
下面的片段是一个来自AI客户端的mcp工具调用请求的例子。 下面的卷曲请求允许结束对请求的跟踪，当在Apigee与OTEL一起启用分布的跟踪时。
卷曲 - X POST "https://xxxxx.xxx.net/mcp" \
-H"Content-Type：应用程序/json"\?
-H "MCP-Protocol-Version: 2025-11-25" \
-d '{
"jsonrpc":"2.0" (中文(简体) ).
"id": 321 (英语).
"方法":"工具/调用"
"段落":{
"名字":"创造奖"
"论语":{
"资治通鉴":123
},
"_meta": {
"追踪父母":"00-3ad8012d970b3971cb16cda653a1a370-df3047d1d0830dc0-01".
}
}
}'
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与在 Google CloudTrace 显示中分发的微量数据所安排的相同在一个全局视图中，这些调用是完整的。 (Asumption是链式报告给同一Google CloudTrace中的所有服务(Apigee/Non-Apigee)).
MCP客户端在JSON-RPC meta字段内承载了W3C痕量上下文，一个常规的REST后端不知道如何阅读。 Apigee将其提取出来并转发为普通的痕母和痕母头，因此下游的仪器服务在没有代码更改的情况下加入了痕母。 接下来有三件事：一个跨越AI客户端，Apigeee代理和后端执行的单一痕量ID；没有重新编码和较少噪音参与的后端，因为网关可以在过路模式中转发上下文，而不是排放自身基础设施的跨度，这些跨度也会对摄入成本进行修剪。
生态系统正与同一想法趋同。 SEP-2028是MCP社区的一个开放建议，旨在将MCP服务器的W3C痕量上下文标准行为标准化 meta-对头转发。
搭载W3C微量上下文的OpenTeleometry路径今天在Apigee可以找到。
MCP支援目前可用Apigee混合1.1.7. 从Apigee总体架构中的MCP开始，为Helm程序启用Apigee混合式的MCP，以及MCP快速启动，以获得第一个响应agent的工具。
本文由 AI图鉴自动抓取并翻译，版权归原作者所有；如需查看原文请点下方链接。
OCT. 14, 2026
Last December, we announced preview of MCP support in Apigee: the ability to turn the APIs you already have, secured, governed and cataloged into tools that AI agents can discover and call, without writing code or standing up MCP servers of your own. The response from customers was immediate and so was the first question back: “can I have this where my runtime actually lives?”
For many Apigee customers, the runtime does not live on Google-managed infrastructure by accident. It lives in their own data center, in a colocation facility, or in another public cloud because a regulator requires it, because the systems of record are three racks away, or because a multi-cloud estate is simply the reality of the business. Those customers were not asking whether they wanted agentic access to their APIs. They were asking whether they could get it without moving the runtime.
And now they can. With Apigee hybrid 1.17.0, released on September 14, 2026, Model Context Protocol support is available in Apigee hybrid and the MCP data plane runs inside your own Kubernetes cluster.
The conceptual model is the one we shipped on Apigee, unchanged. You describe your API with an OpenAPI 3.0.x specification and create an MCP Discovery Proxy from it. Every operation in that spec becomes an MCP tool. Agents talk to the endpoint over JSON-RPC using tools/list to discover what is available and tools/call to invoke it and Apigee handles the protocol and the transcoding. You do not write MCP server code and you do not operate an MCP server as a separate piece of software with its own lifecycle.
What changes in hybrid is where the work happens. In Apigee hybrid, the MCP data plane runs inside your own Kubernetes cluster. The Apigee control plane generates MCP tool configuration from your OpenAPI Specification, your cluster fetches that configuration periodically and MCP request traffic never leaves the cluster. The diagram below shows where the MCP data plane runs in each deployment model.
Two properties of that architecture are worth stating plainly because they are the ones your security review team will ask about.
MCP request traffic stays inside your cluster. An agent's tools/call request is received, authorized and proxied to your backend entirely within your own infrastructure. No MCP request or response crosses the boundary to Google Cloud at request time.
Configuration is pulled, not pushed. A sidecar alongside the MCP data plane (from within your cluster) reaches out to fetch the tool configuration derived from your spec. The Apigee control plane (in Google Cloud) never initiates a connection into your cluster, which means MCP requires no inbound path from Google into your network.
- Agentic endpoints run where your APIs already run. Apigee hybrid already lets you host the runtime on the Kubernetes platform of your choice and MCP inherits that. The MCP sidecar reuses the existing apigee-watcher identity. There is no new Google service account to create and no new IAM role to grant. One control-plane grant per organization and the identity you already have does the rest.
- Data residency and sovereignty posture carry over. MCP in Apigee hybrid is available for Subscription and Evaluation organizations, including Data Residency–enabled organizations (configured at organization setup). On hybrid, configuration is fetched from your control plane location and the runtime request path stays in your cluster by construction. For teams whose constraint is "the request may not leave this jurisdiction, this facility, or this VPC," that constraint is supported by the architecture rather than by a setting.
- The governance you already wrote applies to agents. MCP endpoints are Apigee proxies, so they inherit the platform: OAuth 2.0 and OpenID Connect, API key verification as well as Apigee's built-in policy library. Tool-level control comes from a concept you already use, the API product. You list the specific tool operations a client is entitled to, optionally with a per-tool quota and Apigee enforces it. It also filters discovery automatically. When a client calls tools/list, the response contains only the tools in that client's API product. An agent cannot call delete_account if it was never allowed to see it.
- Your agentic traffic shows up where your API traffic does. Deployed MCP Discovery Proxies are automatically ingested into Apigee API hub, assigned the MCP API style and their operations mapped to individual tools a searchable catalog that developers can query in natural language rather than a spreadsheet of endpoints. In API insights, two filters, API style and MCP tool name let you isolate agentic traffic from ordinary REST traffic and look at a single tool across the API performance, error analysis, latency and target performance dashboards. You can see the ratio of discovery to execution and you can tell proxy overhead apart from backend time.
MCP is an optional feature in Apigee hybrid and is not enabled by default. Enabling it is a Helm operation on a cluster already running Apigee hybrid 1.17.0 or later. Steps to do this are as follows.
Set the top-level enableMcpServer: true key in your overrides.yaml, then upgrade the apigee-operator chart first and the apigee-org chart second. The order matters. The operator chart owns the schema for the new MCP resources and upgrading in the wrong order produces a successful upgrade with no MCP pods. There is also a one-time, per-organization grant that adds the apigee-watcher identity to your organization's control plane access, so the sidecar can retrieve configuration. Defaults are sensible out of the box. Two MCP replicas, autoscaling to ten. Rolling back is the same field set to false and a single chart upgrade.
A few things to plan for before you schedule the change. Enabling or disabling MCP triggers a staged canary release of runtime pods, so run it in an approved maintenance window. The public documentation here describes how to enable MCP in an existing Apigee hybrid cluster.
Your MCP proxy is exposed as a single endpoint. Every agent request, whatever tool it invokes, arrives at the same /mcp path. Apigee tags each of those requests with the name of the tool that was called, so API insights can break that one endpoint out by tool and show which tools your agents actually used, how often and over what period. The screenshot below shows API insights, including requests to the MCP proxy (mcp) and also see individual tools (as API proxies mcp-healthcare, mcp-petstore, mcp-statuscode) response time and tps. See public documentation on monitoring and analyzing mcp traffic with Apigee API insights here and here on how to use the API insights dashboard.
We also have a view of tools being called in the tool performance tab within API insights below.
An MCP tool call crosses an AI client, Apigee and your backend. Today each of those is its own island of logs, so the question platform teams actually ask “where did the time go?” has no single answer.
The snippet below is an example mcp tools call request from an AI client. The curl request below allows for end to end tracking of the request, when distributed trace is enabled in Apigee with OTEL.
curl -X POST "https://xxx.xxx.xxx.net/mcp" \
-H "Content-Type: application/json" \
-H "MCP-Protocol-Version: 2025-11-25" \
-d '{
"jsonrpc": "2.0",
"id": 321,
"method": "tools/call",
"params": {
"name": "createReward",
"arguments": {
"reward": "123"
},
"_meta": {
"traceparent": "00-3ad8012d970b3971cb16cda653a1a370-df3047d1d0830dc0-01"
}
}
}'
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The same call as orchestrated by distributed trace in Google CloudTrace shows the calls in its entirety in one global view. (Assumption is all services (Apigee/Non-Apigee) in the chain report to the same Google CloudTrace)
MCP clients carry W3C trace context inside the JSON-RPC _meta field, which a conventional REST backend has no idea how to read. Apigee extracts it and forwards it as ordinary traceparent and tracestate headers, so instrumented services downstream join the trace without code changes. Three things follow: a single trace ID spanning the AI client, the Apigee proxies and backend execution; backends that participate without recoding and less noise, because the gateway can forward context in passthrough mode rather than emitting infrastructure spans of its own which also trims trace ingestion cost.
The ecosystem is converging on the same idea. SEP-2028, an open proposal in the MCP community, aims to standardize _meta-to-header forwarding of W3C trace context standard behavior for MCP servers.
The OpenTelemetry path that carries W3C trace context is available in Apigee today.
MCP support is available now in Apigee hybrid 1.17.0. Start with the MCP in Apigee overview for the architecture, Enable MCP in Apigee hybrid for the Helm procedure and the MCP quickstart to get a first tool answering an agent.
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