WWebMCP explains: The path to an agent-ready website
WebMCP explained:
The path to an agent-ready website
AI not only changes how people search for information. It also transforms how tasks are performed on the Internet. When AI agents in the future compare products, check appointments, trigger requests, or initiate service processes, they must be able to reliably extract the necessary information and functions from websites. For this, information must be structured and central functions must be reliably usable for systems.
And this is exactly where WebMCP is supposed to help. It is an attempt to establish a standard for how websites can openly and agent-friendly disclose and provide their capabilities. Even though WebMCP is not yet a standard today, companies should already examine the ideas that WebMCP pursues to make their website readable and usable for AI agents.
Why AI is changing the role of websites
Many users already use AI in the early stages of information search. The responses of these AI systems are quick, condensed, and context-related, and are often based on information from websites. They remain a central source for content, services, prices, availability, forms, and processes. The new development is that these informations will not only be read by humans in the future but also increasingly processed by systems that act on behalf of humans.
From AI chat to AI agent
The first AI applications were primarily chat systems that provided dialog-based support to users. They answered questions and provided information. Meanwhile, in addition to chat systems, there are also AI agents that go beyond mere dialogues and increasingly take on tasks independently. Agents break down a goal into steps, use tools, and attempt to actually execute a task. The difference is evident in the application:
AI chats explain how to make an appointment request.
KI chats describe possible rates.
AI agents identify free time slots, fill in missing information, and initiate the request directly.
AI agents compare specific options, systematically categorize differences, and prepare a selection.
This shifts the expectation of many users: away from pure information provision towards the execution of specific tasks.
Why today's websites are only partially suitable for AI agents
Websites today are optimized for human use, not for AI agents. Their interaction logic is based on navigation, visual hierarchy, buttons, forms, and text-based content. This works well for humans, but for AI agents, it often involves considerable interpretation effort. Agents need to read content, interpret interfaces, and identify interactive elements to perform actions on the website. This can work but is prone to errors, often slow and labor-intensive. To avoid errors, content must be structured and described in a way that it can be clearly and machine-readably processed by systems.
How websites become usable for AI agents – MCP and WebMCP
To master this challenge, a new approach is needed. This is where MCP and WebMCP come into play. The MCP (Model Context Protocol) describes how AI applications can standardize interaction with external systems, data sources, and functions. WebMCP applies this principle to websites and web applications in the browser. The goal is to provide functions so that AI agents no longer have to indirectly explore them through the interface but can specifically access clearly defined functions provided by the website. It is important to categorize: WebMCP is currently not yet an established standard, but an early technical proposal.
How WebMCP could work on a website
A possible sequence:
A website provides certain functions as usable tools, such as checking availability, searching for products, creating a request, or creating a support ticket.
The agent recognizes that these functions are available.
The browser checks the required permissions and shows which action to be performed.
The agent calls up the appropriate tool with the necessary information.
The website returns structured results, such as available appointments, hit lists, status information, or error messages.
The result is displayed in the interface and remains traceable for users.
Which technical approaches for WebMCP are currently being discussed
In connection with WebMCP, two approaches are currently being discussed, in particular: Declarative approaches describe standardized actions directly in HTML or in existing interaction elements. This is especially relevant where forms, clearly defined standard procedures, or other predictable interaction patterns are present. In the imperative approach, JavaScript is used to define which functions can be explicitly integrated and utilized. It offers more flexibility and is particularly suitable for dynamic applications, individual workflows, and more complex interactions.
Possible applications of WebMCP
WebMCP could become particularly relevant where websites provide clearly defined functions in addition to content. This particularly concerns processes where users want to search, compare, check, request, or trigger something.
Typical fields of application would be, for example:
the structured search for products or services,
the checking of availabilities and appointments,
filling out and submitting requests,
the accompaniment of support and self-service processes,
as well as access to documents, status information, or results.
Conclusion: What role WebMCP might play in the future
When AI agents act on behalf of users, websites must be understandable and usable not only for humans but also for systems. Therefore, in addition to content and performance, structured information and clearly accessible functions are gaining importance. It is apparent that AI systems particularly prefer websites whose information and processes can be processed efficiently and reliably. WebMCP provides a potential foundation for this, even though this approach is currently still in its early stages. However, WebMCP is not the only approach. Currently, various protocols are emerging that address different aspects of agent-based systems. For example, the Universal Commerce Protocol (UCP), driven by Shopify and Google, aims at standardized commerce processes, such as purchase or booking transactions. Another approach is the Agent Communication Protocol (ACP), which is being developed in the Open-AI environment to enable structured communication between agents. Both approaches are interesting and particularly relevant where standardized products or bookable services are concerned.
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