As we transfer into 2026 and replicate on the promise of AI automation and Large Language Models (LLMs), many companies are confronting a extra sobering actuality. In 2024 and 2025, we noticed a proliferation of and pleasure round primary chat interfaces and easy immediate primarily based automation, however extra optimistic and superior agentic workflow experiments bought a bit caught, hardly ever reaching the maturity required to roll out effectivity enhancements enterprise vast.
This bottleneck nonetheless is much less concerning the capabilities of the underlying fashions themselves, however extra concerning the problem of getting these fashions to speak with the remainder of the enterprise.
That is the place the Mannequin Context Protocol (MCP) is available in; a standardised common connector that’s reaching an adoption level which is now permitting a change from chat-based prompting to extra energetic agentic workflows.
Why earlier AI workflows stalled
Regardless of billions in funding worldwide, a number of research equivalent to McKinsey’s 2025 ‘State of AI’ and the viral MIT NANDA ‘The GenAI Divide’ revealed solely a small proportion of organisations are seeing significant ROI from their AI initiatives, with the vast majority of respondents not but scaling AI throughout their office.
Somewhat than AI itself being damaged, the analysis factors to the under key obstacles:
- Customized integration prices. Constructing bespoke middleware, customized connections or APIs to hyperlink platforms and LLMs is each costly and laborious to take care of.
- UX friction. AI is usually carried out as a standalone or bolt on instrument to completely different processes, forcing staff to change between completely different AI instruments and subsequently extra prone to result in abandonment.
- Safety and knowledge safety. Granting an LLM entry to delicate knowledge by way of third celebration integrations with no safe protocol and different guardrails is seen as dangerous.
- Restricted context and constraints. Most AI experiments are restricted to learn solely interactions: nice at summarising paperwork however not capable of take actions equivalent to triggering an motion in one other software.
Why MCP adjustments issues
The MCP protocol is an open customary, initially dropped at market by Anthropic (the creators of Claude), that has quickly develop into the business benchmark. It makes use of a structured JSON-based communication customary that permits instruments equivalent to LLM fashions to work together with exterior knowledge sources instantly. Querying MCP servers will return supported actions like ‘get_screenshot’ or ‘run_report’ with significant descriptions that may be understood by AI brokers.
MCP is constructed with enterprise-grade safety at its core, utilising sturdy authentication requirements (equivalent to OAuth 2.1) to make sure that when an AI agent accesses your Analytics or CRM knowledge for instance, it does so inside a strictly ruled sandbox. Plus the likes of Google Gemini (Enterprise) and Anthropic (Claude for Business) don’t use chat or coding classes to coach their fashions stopping knowledge leakage.
Crucially, MCP helps each ‘learn’ and ‘write’ capabilities, which means an AI agent can transcend discovering and summarise data, and may truly carry out actions like producing a technical report in a brand new doc or updating a Slack channel.
Chances are high that any given instrument in your MarTech stack already has an MCP server.
This proliferation of MCP help, which is now being adopted by the massive LLM platforms, will enable us to convey all our instruments and software program collectively for use together with the most recent AI fashions for constructing far more superior workflows.
The battle for agentic orchestration
Whereas the MCP protocol was first developed again in November 2024 by Anthropic, adoption has actually gathered tempo in latest months and most notably amongst a few of the greatest gamers within the house: Google Gemini, Anthropic (Claude) and Microsoft + OpenAI.
Anthropic, the quick and first mover
Though Anthropic have been pivotal within the creation of MCP late 2024, they donated the protocol to the Linux Foundation on 9 Dec 2025 to make sure it stays a impartial and open customary. This removes competitor obstacles and ensures builders and platform builders can use the protocol freely and indefinitely.
Whereas different platforms have been busy rolling out MCP help, in Jan 26 Claude went one step additional, introducing support for MCP Apps, an extension of the MCP protocol that pulls in UI previews and interactive components direct from third celebration platforms like Figma and Slack. Claude now has a listing of over 75 official connectors, serving to to determine itself because the connector-of-all-things.
Notably, Google and different office merchandise are absent from Claude’s library and whereas Microsoft 365 has a connector, it’s restricted to learn solely. This could possibly be a significant disadvantage for any enterprise eager to convey AI automation throughout office-based software program.
Google and the ecosystem benefit
The day after Anthropic donated MCP to the Linux Basis, Google announced MCP support and rollout throughout the Google and Gemini ecosystem promising to convey extra agent primarily based performance throughout companies by supporting integration of third celebration instruments. At the moment there’s tight integration with Google Workspace merchandise; Gmail, Google Meets, Calendar, Docs, Slides, Sheets and many others and rollout throughout 2026 will imply many MCP enabled platforms ought to quickly be obtainable to hook as much as Gemini and Gemini Enterprise.
In Gemini Enterprise, Google has an early stage Agent Designer, which shall be enhanced to incorporate MCP help in addition to different integration sorts. It might at present be utilised to help extra superior ranges of automation together with scheduling and the setup sub brokers that may each learn, and (in some instances), write to merchandise throughout Google Workspace in addition to different third celebration supported connectors or customized brokers constructed with the Agent Improvement Equipment.
To assist guarantee accuracy, the likes of Gemini will use a ‘grounding’ strategy the place techniques are particularly instructed to solely use supplied knowledge to reply or execute a immediate, mixed with code execution the place the mannequin would possibly write a python script or SQL question to calculate and validate responses.
Whereas Google appears to be enjoying catch up in some areas equivalent to availability of out of the box apps and connectors, it has an enormous aggressive benefit by having equivalent to tight integration with all it’s Workspace software program. For organisations already invested within the Google stack, this could possibly be vital now that Gemini can begin bringing collectively firm knowledge.
OpenAI and Microsoft’s built-in Copilot
Microsoft, which has it’s personal in-house fashions in addition to permitting builders to utilise OpenAI fashions in its Copilot ecosystem, additionally introduced it was embracing the protocol in May 2025. It counseled the light-weight, open and safe nature of the protocol and continues to lean into GitHub Copilot for coding and M365 integrations within the office that help connections to non MS platforms.
OpenAI launched help for remote MCP servers in May 2025 and in December 2025 opened up it’s App Directory (Beta) to builders and MCP primarily based app submissions which is rising shortly. Apps will be toggled on and authenticated inside a minute or two and interacted with utilizing ‘@’ in prompts e.g. ‘@Figma’. Connections to some apps do nonetheless seem patchy, with the Beta nonetheless seeming very very similar to work in progress.
It must be clear now that the intent of the massive AI gamers; Google’s Gemini, Anthropic’s Claude, and OpenAIs ChatGPT is to develop into the one supply of AI orchestration and agent automation for the office, by way of premium subscriptions.
As rollout continues throughout 2026, it should develop into more and more doable to setup superior agentic workflows utilizing highly effective and person pleasant interfaces to determine and authenticate connections to not solely pull knowledge from, however ship actions to. Whereas there are nonetheless prone to be various use instances with MCP enabled apps outdoors of a centralised orchestrator, the transfer in the direction of centralisation will collect tempo throughout 2026 because it solves the issues of UX friction throughout a mess of AI instruments and avoids the necessity for customized coded integrations that held again many initiatives in 2025.
MCP in motion: design to growth
To see the worth MCP can already convey, we solely want to have a look at how the developer workflow is quickly evolving. In late 2025, Figma rolled out native MCP server integration permitting builders to hook Figma on to in style brokers and code editors equivalent to VS Code with GitHub Copilot or Cursor with a couple of clicks.
A workflow for constructing a newly designed web site part for instance can contain:
- Present an agent (equivalent to GitHub Copilot) a immediate and Figma hyperlink for a particular layer, choosing the popular mannequin equivalent to Claude 4.5 Opus which is great for extra complicated coding duties.
- The agent then sends the AI mannequin as a lot context as it may possibly from the Figma MCP server together with CSS, font references, color palette and a screenshot of the chosen layer.
- Native environmental context can also be despatched to the AI mannequin equivalent to open recordsdata, hooked up recordsdata, mission construction, coding requirements used and many others.
- In a single multistep ‘agentic’ movement proven under, the agent generates production-ready code, saves vital belongings to a folder and even proactively takes unprompted steps equivalent to including micro-animations.
- The developer then corrects or cleans up any points. Completely positioned content material inside Figma layers for instance doesn’t at present translate very effectively.
Whereas we’re nonetheless in early levels of totally embedding this workflow in our course of at Hallam, experimentation thus far convinces us that these sort of workflows will deal with a lot of the extra day-to-day points of web site builds quicker, permitting us to focus our time and efforts and creating even higher experiences. These multistep potentialities will begin to develop into extra commonplace throughout completely different disciplines over 2026 by way of numerous particular person or centralised platforms.
Agentic potentialities by way of MCP
Securely linking collectively key instruments from a enterprise managed by highly effective AI brokers will begin to unlock many alternatives, particularly when contemplating the real-time learn and write capabilities of MCP. Listed here are just some small examples of the sort of implementations we must always begin to see.
Firm vast oracles. A standard problem for a lot of organisations is the fragmentation of communications and knowledge in numerous places. Emails. Slack. Groups. Intranet. Shared Drives. Venture Administration Instruments. Assembly Notes. Think about how far more productive we are able to develop into just by discovering and summarising data shortly from a number of places by way of a single immediate primarily based interface. Brokers will have the ability to ship us each day or weekly summaries, motion factors and we’ll more and more belief them to begin drafting responses primarily based on our tone of voice.
Era of artistic belongings. The capabilities of generative AI for photos is bettering on a regular basis however we are able to now transcend primary prompting. For instance, pointing a instrument like Nano Banana (Gemini’s picture generator) to model tips, a web site, a short, a present artistic idea, or a mixture of all of this, to rollout a artistic ideas throughout completely different platforms, dimensions and codecs. Maybe it will likely be doable hyperlink up present advert campaigns from Fb Adverts for instance, or ship preliminary generated photos to design instruments like Figma Make or PhotoShop for clear up.
Auditing and knowledge evaluation. It can quickly straightforward to hook our Gross sales & Advertising knowledge from our CRM platforms from the likes of HubSpot or Salesforce, alongside analytics knowledge from VWO or GA4 to assist spot patterns and tendencies. We’ll have the ability to use browser primarily based brokers equivalent to Computer Use from Gemini for brokers to browse and work together with web sites instantly, pulling screenshots and code to assist us with audits and optimise conversion journeys, producing draft experiences to be used to make use of in slide decks and spreadsheets.
In a couple of months, presumably mid 2026, I predict the likes of Gemini will enable us to construct superior agentic multistep workflows throughout the vast majority of any enterprise tech and martec stack, utilizing scheduled or logical triggers by way of in-built and simple to make use of UI interfaces.
Automating responsibly
As we transfer into 2026 and past primary chat interfaces, we are going to begin connecting siloed knowledge and begin shifting the dialog from “what can this LLM say?” to “what can this AI agent do?”. MCP acts as a catalyst for this evolution, permitting us to maneuver previous bespoke and infrequently siloed integrations in the direction of a extra common and unified plug-and-play connector that permits AI fashions to work together instantly with your enterprise stack with enterprise-grade safety.
On a extra private stage as a developer, seeing how workflows are quick evolving from the coding perspective, my fascination for the know-how can also be tempered by a way of delicate doom. I’ve chosen, and I believe companies extra broadly, ought to select to embrace these agentic workflows to focus extra on automating the mundane and elevating the human.
By handing over a few of the extra repetitive day-to-day duties to AI, we enable our groups to give attention to increased stage downside fixing, strategic pondering and artistic execution required to construct higher merchandise and experiences. We must be viewing AI as a strong instrument to ship with out it changing the important pondering that can all the time be wanted to make sure a excessive customary, serving to add significant innovation, long run worth and progress.
This can be a sentiment I hope we are going to see extra within the UK as an entire. A recent study by Morgan Stanley in Jan 2026 reveals that whereas each US and UK corporations are reporting comparable productiveness boosts of ~11.5%, UK corporations usually tend to make job cuts as a result of AI alongside wider financial pressures. In the meantime, US corporations are broadly re-purposing the time AI saves into R&D and the creation of recent roles.
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