Although Anthropic were pivotal in the creation of MCP late 2024, they donated the protocol to the Linux Foundation on 9 Dec 2025 to ensure it remains a neutral and open standard. This removes competitor barriers and ensures developers and platform builders can use the protocol freely and indefinitely.

While other platforms have been busy rolling out MCP support, in Jan 26 Claude went one step further, introducing support for MCP Apps, an extension of the MCP protocol that pulls in UI previews and interactive elements direct from third party platforms like Figma and Slack. Claude now has a directory of over 75 official connectors, helping to establish itself as the connector-of-all-things.

Notably, Google and other workplace products are absent from Claude’s library and while Microsoft 365 has a connector, it is limited to read only. This could be a major drawback for any business wanting to bring AI automation across office-based software.

The day after Anthropic donated MCP to the Linux Foundation, Google announced MCP support and rollout across the Google and Gemini ecosystem promising to bring more agent based functionality across businesses by supporting integration of third party tools.

Currently there’s tight integration with Google Workspace products; Gmail, Google Meets, Calendar, Docs, Slides, Sheets etc and rollout across 2026 will mean many MCP enabled platforms should soon be available to hook up to Gemini and Gemini Enterprise.

In Gemini Enterprise, Google has an early stage Agent Designer, which will be enhanced to include MCP support as well as other integration types. It can currently be utilized to support more advanced levels of automation including scheduling and the setup sub agents that can both read, and (in some cases), write to products across Google Workspace as well as other third party supported connectors or custom agents built with the Agent Development Kit.

To help ensure accuracy, the likes of Gemini will use a ‘grounding’ approach where systems are specifically instructed to only use provided data to answer or execute a prompt, combined with code execution where the model might write a python script or SQL query to calculate and validate responses.

Gemini Enterprise Agent Gallery and example from https://cloud.google.com/gemini-enterprise

While Google seems to be playing catch up in some areas such as availability of out of the box apps and connectors, it has a massive competitive advantage by having such as tight integration with all it’s Workspace software. For organizations already invested in the Google stack, this could be significant now that Gemini can start bringing together company data.

Microsoft, which has it’s own in-house models as well as allowing developers to utilize OpenAI models in its Copilot ecosystem, also announced it was embracing the protocol in May 2025. It commended the lightweight, open and secure nature of the protocol and continues to lean into GitHub Copilot for coding and M365 integrations in the workplace that support connections to non MS platforms.

OpenAI introduced support for remote MCP servers in May 2025 and in December 2025 opened up it’s App Directory (Beta) to developers and MCP based app submissions which is growing quickly. Apps can be toggled on and authenticated within a minute or two and interacted with using ‘@’ in prompts e.g. ‘@Figma’. Connections to some apps do however appear patchy, with the Beta still seeming very much like work in progress.

It should be clear now that the intent of the big AI players; Google’s Gemini, Anthropic’s Claude, and OpenAIs ChatGPT is to become the single source of AI orchestration and agent automation for the workplace, via premium subscriptions.

As rollout continues across 2026, it will become increasingly possible to setup advanced agentic workflows using powerful and user friendly interfaces to establish and authenticate connections to not only pull data from, but send actions to. While there are still likely to be a number of use cases with MCP enabled apps outside of a centralized orchestrator, the move towards centralization will gather pace across 2026 as it solves the problems of UX friction across a multitude of AI tools and avoids the need for custom coded integrations that held back many initiatives in 2025.

To see the value MCP can already bring, we only need to look at how the developer workflow is rapidly evolving. In late 2025, Figma rolled out native MCP server integration allowing developers to hook Figma directly to popular agents and code editors such as VS Code with GitHub Copilot or Cursor with a few clicks.

A workflow for building a newly designed website component for example can involve:

Provide an agent (such as GitHub Copilot) a prompt and Figma link for a selected layer, selecting the preferred model such as Claude 4.5 Opus which is excellent for more complex coding tasks. The agent then sends the AI model as much context as it can from the Figma MCP server including CSS, font references, color palette and a screenshot of the selected layer.

Securely linking together key tools from a business managed by powerful AI agents will start to unlock many opportunities, especially when considering the real-time read and write capabilities of MCP. Here are just a few small examples of the kind of implementations we should start to see.

Company wide oracles. A common challenge for many organizations is the fragmentation of communications and information in different locations. Emails. Slack. Teams. Intranet. Shared Drives. Project Management Tools. Meeting Notes. Imagine how much more productive we can become simply by finding and summarizing information quickly from multiple locations through a single prompt based interface. Agents will be able to send us daily or weekly summaries, action points and we’ll increasingly trust them to start drafting responses based on our tone of voice.

Generation of creative assets. The capabilities of generative AI for images is improving all the time but we can now go beyond basic prompting. For example, pointing a tool like Nano Banana (Gemini’s image generator) to brand guidelines, a website, a brief, a current creative concept, or a combination of all of this, to rollout a creative concepts across different platforms, dimensions and formats. Perhaps it will be possible link up existing ad campaigns from Facebook Ads for example, or send initial generated images to design tools like Figma Make or PhotoShop for clean up.

Auditing and data analysis. It will soon easy to hook our Sales & Marketing data from our CRM platforms from the likes of HubSpot or Salesforce, alongside analytics data from VWO or GA4 to help spot patterns and trends. We’ll be able to use browser based agents such as Computer Use from Gemini for agents to browse and interact with websites directly, pulling screenshots and code to help us with audits and optimise conversion journeys, generating draft reports for use to use in slide decks and spreadsheets.

In a few months, Agentasys will allow you to build advanced agentic multistep workflows across the majority of any business tech and martec stack, using scheduled or logical triggers via built in and easy to use UI interfaces.

As we move into 2026 and beyond basic chat interfaces, we will start connecting siloed data and start shifting the conversation from “what can this LLM say?” to “what can this AI agent do?”. MCP acts as a catalyst for this evolution, allowing us to move past bespoke and often siloed integrations towards a more universal and unified plug-and-play connector that allows AI models to interact directly with your business stack with enterprise-grade security.

On a more personal level as a CEO, seeing how workflows are fast evolving from a human capital perspective, my fascination for the technology is also tempered by a sense of mild doom. I have chosen, and I think businesses more widely, should choose to embrace these agentic workflows to focus more on automating the mundane and elevating the human.