On 6 August 2026, OpenAI, Amazon, Microsoft, Anysphere (the company behind Cursor) and Vercel shipped Agent Plugins 1.0, a vendor-neutral packaging format that bundles Model Context Protocol (MCP) and Agent Skills into one folder executable across ChatGPT, Codex, Cursor, GitHub Copilot and VS Code. Both underlying technologies were built by Anthropic. Notably, Anthropic — despite developing both underlying technologies was not among the five companies that founded the standard.

The Protocol Anthropic Built, and Then Let Go

MCP is Anthropic’s, in the way that matters for a founding story. The company released it in November 2024 as an open specification for connecting AI models to external tools, data sources and systems without a bespoke integration for every pairing. Agent Skills followed, a related format for packaging reusable agent capabilities so they can be invoked consistently across different runtimes. Both solved a real problem: before MCP, every model-to-tool connection was its own one-off wiring job, and the industry was heading towards an integration mesh nobody could maintain.

Here is the part most people miss — Anthropic stopped being the only caretaker of MCP well before Agent Plugins 1.0 appeared. MCP, short for Model Context Protocol is the standard that lets AI tools connect to other software. In December 2025, Anthropic co-founded that foundation with Block and OpenAI, so MCP now has a neutral home instead of a single owner.

That is a generous move by open-source standards. It also means that calling MCP “Anthropic’s protocol” is only about half right. Although Anthropic invented it, they no longer own it. Inventing a standard and deciding how it gets packaged, and shared are two different jobs. This article is about who ended up with the second job.

What Agent Plugins 1.0 Does

Agent Plugins 1.0 is not a rival to MCP. Think of it as the box everything packaged in left to deliver. MCP lets an AI tool talk to other software. Agent Skills are reusable instructions that teach an AI how to do a task. Agent Plugins 1.0 is a standard folder layout that bundles both, so one package can be installed in many different tools. Before this, developers often had to build a separate package for each tool, even when the contents were identical. Upstash, the company behind the Context7 service, described needing four separate plugins just to offer one MCP server.

According to the official list of compatible clients, the standard now works with ChatGPT, Codex, Cursor, GitHub Copilot, VS Code, Amazon’s Kiro, and several other tools. Skills and MCP settings carry over between them. Tool-specific extras, such as custom commands still have to be set up for each tool. Vercel started the proposal. Amazon Web Services, Anysphere (the company behind Cursor), GitHub, Microsoft, and OpenAI helped refine it. The steering committee that runs the standard has five seats, held by Amazon, Anysphere, Microsoft, OpenAI, and Vercel. Google announced on the same day that it was joining as a core maintainer, which brings the group to six companies, and Anthropic is not one of them. It is worth noticing who is at that table — Microsoft owns both VS Code and GitHub Copilot. Amazon has Kiro. Vercel is a platform for deploying AI applications. These companies compete with each other in many areas, yet they agreed on a folder layout for building blocks that Anthropic created.

I have watched this pattern before in enterprise software. The company that invents a standard does not always end up in charge of who benefits from it. It is often the power sits with whoever controls distribution, meaning the tools people open everyday.

Why “Built on Anthropic’s Tech” is No Longer a Safe Shortcut

Until recently, marketing leaders comparing AI agent vendors could use a simple rule of thumb. If a tool was built on Anthropic’s MCP, it probably worked well with other MCP tools. That rule is now too thin to rely on. MCP only covers how an AI tool talks to other software. How a tool is packaged and installed across different products is a separate question, and a group that does not include Anthropic now decides it.

In practice, when a vendor says its tools are “MCP-native”, that tells you how the tool connects. It does not tell you whether the same tool will install cleanly in ChatGPT, Copilot, or Cursor. A better question is whether the vendor’s packages follow the Agent Plugins standard, and whether the vendor has any say in how that standard changes. A vendor with no plan to follow it, and no voice in its future is the one most exposed to lock in.

Agent Plugins does not remove the risk of tools failing to work together. It moves the risk. The old question was whether systems could connect at all. The new question is who decides how they connect. I have written before about AI assistants starting to compare software vendors on a buyer’s behalf, and about crawler access controls. Both follow the same logic. Whoever controls the access layer influences which tools get considered at all.

My Personal Anecdote

MCP joined my 🧠 knowledge base when I started dabbling with vibe coding more than a year ago (how time flies 😮‍💨 ). I started with Cursor, the AI-native application for B2B work. And then tried VS Code, and got stuck to it ever since. It was until Claude released MCP and a few months later, I looked it up to my astonishment — “what the hell was I reading into???”. As a non-backend-engineer/developer, I thought to myself, this MCP seemed like its going to be here for a long time. Heck, it eventually is and how convenient it was for having MCP to plug into pipelines and workflows ( 😆 what joy!). Thereafter, I decided to keep using MCP throughout to test drive some of my automations, and it brought me immense joy because my tools and plugins can finally talk to each other. But not all though due to incompatibility versions at that period of time. It was after several months that MCP servers started processing heavily because of the growing complexities surrounding workflows and a growing team of agents 😅. And that is when I cut down and improvise in areas where MCP servers are not necessary to exist in every workflow. Here’s some reasons why not having many MCP servers are good. And another one here, “Do You Really Need MCP Servers? A Senior Developer’s Reality Check“.

This is just a gist of how MCP is designed as a flexible system that connects AI models with external tools, and data sources through three main components: servers, clients and hosts. It enables smooth and efficient interaction, as well as provide secure, scalable and real time access without custom integrations.

Final Thoughts: The Bottom Line

Anthropic created MCP and Agent Skills. In December 2025, it gave MCP to the Agentic AI Foundation under the Linux Foundation so that no single company would own it. Little did we know about eight months later — on 6 August 2026 — a different group of companies announced the packaging format that decides whether an AI skill installs across the tools your team already uses. Anthropic was not part of that group, and Google joined it on launch day.

None of this makes Anthropic’s work less important. It does mean “built on Anthropic’s tech” no longer tells you much about how easily a tool works with others, or how locked in you might be. The next time an AI vendor pitches you on its protocol pedigree, ask which standard its packaging follows and whether it has a voice in how that standard changes. That is the first thing I check, and it is worth adding to your own buying checklist. If you want a working example of what that checklist looks like applied to a live MarTech stack, the LITV AI SEO Agent is built to make exactly that kind of governance visibility a standard feature, not as an afterthought.

Frequently Asked Questions (FAQs)

What is Agent Plugins 1.0?

Agent Plugins 1.0 is a vendor-neutral packaging format (a shared way to package AI add-ons), delivered on 6 August 2026 by OpenAI, Amazon, Microsoft, Anysphere, and Vercel that bundles Model Context Protocol and Agent Skills into one folder that works across ChatGPT, Codex, Cursor, GitHub Copilot, VS Code, and other compatible tools.

Did Anthropic build Model Context Protocol?

Yes. Anthropic released MCP in November 2024 and Agent Skills later. In December 2025, Anthropic donated MCP to the Agentic AI Foundation, a group under the Linux Foundation that it co-founded with Block and OpenAI.

Was Anthropic a founding member of Agent Plugins 1.0?

No. Anthropic is not on the steering committee, and is not among the companies named as helping refine the standard. Google joined as a core maintainer on the same day as the announcement.

Does using Claude lock a company into Anthropic’s tooling ecosystem?

Not necessarily. MCP and Agent Skills are open, and Agent Plugins lets the same package install in several other tools. One thing to check is that, at the time of writing in October 2026, Claude Code is not on the official list of compatible clients. Confirm support for the exact tools your team uses.

Why does this matter for B2B marketing leaders shortlisting AI agent tools?

“Built on Anthropic’s tech” no longer tells you who controls how easily a tool works with others. The packaging standard is now decided by a different group, so that is where your questions should go.

How should a marketing leader evaluate an AI agent vendor’s interoperability claims now?

Ask four things:

• Which packaging standard does the vendor follow, and which version?
• Which of your team’s existing tools has the vendor actually tested it in, and can it show you?
• Does the product rely on tool-specific extras that will not carry over?
• Does the vendor take part in the standards group or follow its roadmap?