The Web Is Growing an Agent Layer: What A2A, MCP and WebMCP Actually Mean

The Web Is Growing an Agent Layer: What A2A, MCP and WebMCP Actually Mean

For years, business websites have mainly been designed for two audiences: people using browsers and search engines indexing pages.

That is changing.

AI systems are increasingly able to use tools, retrieve information and complete multi-step tasks. As that develops, a new technical layer is emerging around the web. Three terms appear frequently in this conversation:

• A2A
• MCP
• WebMCP

They are related, but they are not interchangeable.

The short version

MCP helps an AI application use tools and external resources.

A2A helps independent AI agents communicate and collaborate.

WebMCP is a proposed web standard for exposing structured website tools to agents.

The broader phrase agentic web describes the direction of travel, rather than one specific protocol.

Understanding that distinction matters. Businesses should not assume that adding a chatbot, structured data or an llms.txt file automatically makes a website agent-ready.

What is A2A?

A2A means Agent2Agent.

The A2A Protocol is an open standard designed to let independent AI agent systems communicate and collaborate, even when they were built by different vendors, using different frameworks or programming languages.

An A2A interaction might involve one agent delegating part of a complex task to another agent. For example, a customer-service agent might need to collaborate with a billing agent or a delivery-status agent.

A2A is designed around:

• capability discovery;
• exchanging messages and structured information;
• managing longer-running tasks;
• supporting different interaction formats;
• collaboration without exposing an agent’s private memory, internal reasoning or tools.

A central part of A2A discovery is the Agent Card. This describes an agent’s identity, capabilities, endpoint, supported skills and authentication requirements.

A public A2A service may make its Agent Card available at:

``text https://example.com/.well-known/agent-card.json ``

But an ordinary business website does not become an A2A agent automatically. It would need an exposed service, a defined capability set, suitable security controls and a discovery mechanism.

What is MCP?

MCP means Model Context Protocol.

The official MCP documentation describes it as an open standard for connecting AI applications to external systems. These systems might include:

• databases;
• local files;
• search tools;
• calendars;
• APIs;
• business workflows;
• specialist software.

MCP is primarily about the relationship between an AI application and the tools or resources it can access.

A simple example would be an AI assistant using an MCP server to query a company’s product database or retrieve appointment availability.

This is different from A2A.

A calculator, database or booking API is generally a tool or resource. MCP helps an AI application use it.

Another autonomous agent is a collaborating system. A2A helps agents communicate with it.

The two protocols may be used together. An agent could use MCP to access its own tools while using A2A to delegate work to another agent.

What is WebMCP?

WebMCP is a separate and newer proposal.

Chrome’s developer documentation describes WebMCP as a proposed web standard intended to help websites expose structured tools for AI agents. It can use JavaScript and annotated HTML form elements to describe how page features should be used.

The goal is to make agent interaction more reliable than asking an agent to interpret every button, field and page layout visually.

For example, instead of an agent guessing how to complete a booking form, a website could expose a structured tool with defined inputs and actions.

However, WebMCP is not a universal web capability today. Chrome’s documentation identifies it with an origin trial and an active “Intent to Experiment” status.

That means businesses should treat it as an emerging technology to monitor and test carefully, not as a finished requirement for every website.

Why this matters to businesses

The practical question is not “Which buzzword should we add to our homepage?”

The better questions are:

1. Can an AI system understand what the business offers?
2. Can it identify the right service, product or next step?
3. If it is allowed to take action, are the boundaries clear and secure?
4. Can a human take over when the situation requires judgement?

A business preparing for the agentic web should begin with fundamentals:

• clear service and product descriptions;
• consistent business identity and contact details;
• answer-focused page structure;
• clearly defined processes;
• secure forms and APIs;
• explicit permissions;
• human handover routes;
• accurate statements about what is and is not automated.

The technical protocols may develop quickly, but these foundations remain useful regardless of which standard becomes dominant.

The security problem cannot be ignored

An agent that can retrieve information is one thing.

An agent that can change an order, issue a refund, access customer data or make a purchase is something else entirely.

NIST’s 2026 concept paper on software and AI agent identity and authorisation highlights the importance of identification, authentication, authorisation, delegation and least-privilege controls.

That is a useful reminder that agent readiness is not only a content or SEO issue. It is also an operational and security issue.

Businesses should not expose actions simply because an AI system can technically call them.

What these technologies do not prove

A2A does not mean that all websites will soon have invisible conversations with one another.

MCP does not expose a company’s systems unless someone deliberately builds and secures the connection.

WebMCP does not currently represent a universal browser requirement.

Structured data, machine-readable pages and clear answer blocks can help systems understand a business. They do not guarantee ranking, citation, recommendation or successful agent interaction.

The practical conclusion

The web is gaining more ways for AI systems to discover information, use tools and coordinate work.

But A2A, MCP and WebMCP represent different parts of that development:

• MCP: AI applications using tools and resources.
• A2A: agents collaborating with other agents.
• WebMCP: websites exposing structured tools to agents.
• Agentic web: the broader ecosystem around these capabilities.

For most small businesses, the sensible starting point is not to rush into every emerging protocol.

It is to make the existing website clear, trustworthy, machine-readable and operationally safe. Then identify the specific customer tasks where controlled agent assistance could create real value.

That is a more durable strategy than chasing terminology before the underlying use case is clear.