MCP, A2A and DNS-AID: The Standards Behind Connected AI Systems

During the early adoption of generative AI, most systems operated as isolated chat interfaces. A user entered a question, the model produced an answer, and the interaction ended within a single conversation.

Development is now moving towards AI applications and agents that can use company data, call tools, complete specific tasks, and collaborate with other specialised systems. Supporting this without building a different integration for every combination of product and provider requires shared connection rules.

This is where Model Context Protocol (MCP), Agent-to-Agent Protocol (A2A) and DNS for AI Discovery (DNS-AID) appear. They do not solve the same problem and should not be viewed as competitors. Each occupies a different layer in the architecture of a connected AI system.

Three different layers in one environment

The easiest way to understand the three technologies is through three practical questions:

• MCP: How does an AI application use a specific tool or data source?
• A2A: How does one independent AI agent delegate a task to another and receive a result?
• DNS-AID: How can an organisation publish where its agent or MCP service is located and which protocol it supports?

In a connected business architecture, the three layers can work in sequence. DNS-AID helps discover an appropriate endpoint. A2A manages communication and tasks between independent agents. The agent completing the task can then use MCP to reach authorised tools, documents and APIs.

Discovery, agent communication and tool access are separate responsibilities. This separation makes the architecture easier to understand and allows each layer to be secured and developed independently.

What is MCP?

Model Context Protocol is an open protocol for standardised connections between AI applications and external capabilities. An MCP server can provide resources, tools and reusable prompt templates, while a client discovers and uses only the declared and authorised features.

Instead of every AI application building a separate integration for file storage, calendars, CRM platforms, databases or internal APIs, a system can expose clearly described capabilities through MCP.

An internal business platform might expose tools for:

• finding a customer through permitted fields;
• retrieving documents from a specific project;
• checking available appointments;
• creating a draft task;
• retrieving summarised business indicators.

The official MCP architecture follows a host–client–server model. The host controls connections and access decisions, while each client maintains a separate session with one MCP server. This helps keep servers isolated and limits the context supplied to each operation.

MCP does not automatically make an integration secure. The application must still enforce identity, permissions, least-privilege access, input and output validation, and human confirmation for sensitive actions.

What is A2A?

Agent-to-Agent Protocol focuses on communication between independent AI agents. They may be built by different organisations, use different models and frameworks, and still delegate tasks through a shared protocol.

An A2A agent does not need to reveal its internal memory, prompts or tools. It publishes capabilities, receives a task and returns status updates, messages or completed results. The protocol also supports longer-running operations that cannot be completed through a single immediate response.

For example, a primary business agent preparing a management report could delegate:

• financial indicators to a specialised finance agent;
• project completion data to a project agent;
• customer communication summaries to a CRM agent;
• final document preparation to a reporting agent.

A2A defines how the agents exchange tasks and results. Each agent may internally use MCP to connect to its own tools.

What does DNS-AID add?

Before two agents can communicate, one needs to know where the other is located and which protocol it supports. A central registry can solve this problem, but it introduces dependency on a particular operator and is not inherently linked to the organisation’s domain identity.

DNS-AID proposes a different approach: organisations publish information about agent services inside their own DNS namespace. The project uses existing DNS mechanisms and structured names through which a client can discover an endpoint, a supported protocol and related metadata.

The idea resembles the way domains already direct clients to websites, email services and other internet resources. The organisation controls records under its domain, while the established DNS infrastructure provides distributed discovery and caching.

DNSSEC can provide cryptographic assurance that a DNS response was not altered in transit. It does not mean the discovered agent is automatically trustworthy or that the client is authorised to use its capabilities.

As of 28 August 2026, DNS-AID should be treated as an evolving technology. It has been announced as a Linux Foundation project, while its technical proposal is published as an IETF Internet-Draft. Its format and implementation practices may change before any future standardisation.

How the three technologies work together

Consider a company using a primary AI assistant for customer and internal operations.

1. The assistant needs an external agent capable of checking a delivery status.
2. DNS-AID helps discover a published service and its supported protocol.
3. A2A is used to send a task to the delivery agent and receive a task identifier and status.
4. The delivery agent uses its own MCP client to call an authorised logistics tool.
5. The result is returned through A2A to the primary assistant.
6. The business platform displays the information or asks an employee to approve any further action.

This structure allows systems to remain independent. The delivery agent does not need to expose its database or internal logic, and the primary assistant does not need to understand the implementation details of every external service.

Why open protocols matter to businesses

Without shared standards, every integration becomes a custom connection between two specific systems. As the number of tools and agents grows, the number of connections increases, and maintenance becomes more expensive.

Shared protocols can provide several practical benefits:

• reduced supplier dependency – components can be replaced when they support the same contract;
• faster addition of capabilities – every connection does not need to begin from zero;
• clear boundaries – tools, agents and discovery have separate roles;
• better observability – requests and tasks can be traced at defined points;
• gradual adoption – a company may begin with one MCP integration and add A2A or DNS-based discovery only when justified.

A protocol does not replace security

Interoperability does not equal trust. A published endpoint may be discoverable, but access must still be protected by suitable authentication and authorisation. MCP, A2A and DNS-AID do not remove the need for standard security controls.

A production deployment must define:

• which agents and clients are permitted;
• which tools and data each one may access;
• how permissions are granted, limited and revoked;
• which operations require human approval;
• how received results are validated;
• how tasks and tool calls are recorded;
• how the system responds to a compromised endpoint or supplier.

The official MCP specification includes an OAuth-based model for HTTP authorisation and requires access tokens to be bound to the intended resource. A2A also defines authentication, capability descriptions and controlled interaction. DNSSEC may verify the integrity of a DNS response, but it does not replace application-level authorisation.

Does every business need these technologies?

Not every business system needs multiple agents and public DNS discovery. For an application using one AI model and a few internal functions, a well-protected private API may be entirely sufficient.

MCP becomes valuable when several AI applications need consistent access to the same tools. A2A is useful when independent agents with different responsibilities must coordinate complex or long-running tasks. DNS-AID is relevant to cross-system or cross-organisation discovery, particularly where a central registry is undesirable.

Technology should follow the actual business process. Introducing an agent architecture simply because it is fashionable may create more complexity than value.

The connected future of AI systems

MCP, A2A and DNS-AID show the direction of the ecosystem: away from isolated AI chats and towards modular systems in which models, tools and agents can collaborate through shared contracts.

MCP provides standardised access to specific capabilities. A2A enables coordination between independent agents. DNS-AID explores a decentralised method for publishing and discovering these services through infrastructure the internet already uses.

The goal is not to connect an agent to as many systems as possible. Every connection should have a clear purpose, minimal permissions, traceable actions, and measurable business value.