Is there one official AI agent protocol?

No. There is no single official standard for AI agents. Several protocols exist at different layers — MCP for tools and context, A2A for agent-to-agent communication, and the Agent Protocol REST spec for API-style access. Which is 'right' depends on what you're connecting.

Do MCP, A2A and Agent Protocol compete?

Not directly. They operate at different layers and are often combined. An agent might use MCP to access tools, expose an Agent Protocol REST API to its clients, and use A2A to delegate work to other agents.

Are AI agent protocols production-ready?

It varies by protocol and by use case. Some have growing real-world adoption; others are earlier drafts. Because the space is evolving, validate maturity against official docs and your own testing before depending on any single spec.

Do I need a protocol at all?

For a single agent calling one or two internal tools, a custom integration may be simpler. Protocols pay off as the number of tools, agents or external integrations grows, or when you need interoperability across vendors.

Is there one official AI agent protocol?

No. There is no single official standard for AI agents. Several protocols exist at different layers — MCP for tools and context, A2A for agent-to-agent communication, and the Agent Protocol REST spec for API-style access. Which is 'right' depends on what you're connecting.

Do MCP, A2A and Agent Protocol compete?

Not directly. They operate at different layers and are often combined. An agent might use MCP to access tools, expose an Agent Protocol REST API to its clients, and use A2A to delegate work to other agents.

Are AI agent protocols production-ready?

It varies by protocol and by use case. Some have growing real-world adoption; others are earlier drafts. Because the space is evolving, validate maturity against official docs and your own testing before depending on any single spec.

Do I need a protocol at all?

For a single agent calling one or two internal tools, a custom integration may be simpler. Protocols pay off as the number of tools, agents or external integrations grows, or when you need interoperability across vendors.

AI agent protocol: a beginner-friendly guide

What is an AI agent protocol?

An AI agent protocol is an agreed way for AI agents to exchange information. Instead of every agent, tool and platform inventing its own custom integration, a protocol defines a common message format and set of expectations that any compliant component can follow.

The word “protocol” is doing the same work here it does elsewhere in computing: HTTP lets any browser talk to any web server; SMTP lets any mail client reach any mail server. An agent protocol aims to do the same for AI agents — turning a tangle of one-off connections into an interoperable ecosystem.

Two meanings of the phrase

“Agent protocol” is used both generically (any protocol for agents) and as the proper name of a specific community REST specification. We cover the general idea here and the specific spec in the section below.

Why AI agent protocols matter

As soon as you connect an agent to more than one tool, or let more than one agent cooperate, integration cost explodes. Ten agents and ten tools can require up to a hundred bespoke connectors. A shared protocol collapses that to a single interface each component implements once.

Less glue code. Describe a tool or capability once and reuse it everywhere.
Interoperability. Components from different vendors cooperate without prior coordination.
Portability. Swap models, frameworks or vendors without rewriting every integration.
Composability. Protocols at different layers combine — an agent can use MCP for tools and A2A to delegate to peers.

The main AI agent protocols

Three standards come up most often. They are not direct competitors — each addresses a different layer of the problem.

At a glance	MCPModel Context Protocol	A2AAgent2Agent	Agent ProtocolREST spec
Connects	Agent ↔ tools & data	Agent ↔ agent	Client ↔ agent
Transport	JSON-RPC 2.0	HTTP + JSON-RPC / SSE	REST / HTTP
Best for	Tool & context access	Multi-agent delegation	API-style agent access

Model Context Protocol (MCP)

MCP standardises how an agent connects to tools, data and context — file systems, databases, APIs and more — through a client–server model. Reach for it when the question is “how does my agent use this tool?” See the MCP guide.

Agent2Agent (A2A)

A2A standardises how independent agents talk to each other — advertising capabilities, delegating tasks and exchanging messages, potentially across vendors. Reach for it for multi-agent systems. See the A2A guide.

Agent Protocol (the REST spec)

The Agent Protocol is a framework-agnostic REST API specification for driving an autonomous agent through runs, tasks, steps and artifacts. It gives any client a consistent, API-style way to start work and collect results — regardless of how the agent is built internally.

start-a-run.http

http

POST /ap/v1/agent/tasks
Content-Type: application/json

{
  "input": "Summarise the attached report and list action items."
}

# → 200 OK
# {
#   "task_id": "e5f1...",
#   "input": "Summarise the attached report...",
#   "artifacts": []
# }

The standards are still evolving

These specifications are young and moving quickly. Adoption, transports and even names change between versions. Treat version numbers and status labels on this site as orientation, and confirm details against each protocol's official documentation before you build.

Which protocol should you use?

It depends on the layer you're working at — and many systems use more than one. If you want a guided answer, try the protocol selector, or read the full MCP vs A2A vs Agent Protocol comparison.