Two open protocols now shape how agents connect to the rest of the world. Teams are routinely confusing them, or assuming one covers what the other was never designed to do. Getting this wrong wastes weeks of integration work.
A2A and MCP are different protocols that solve different problems. A2A handles agent-to-agent coordination - how one agent delegates work to another across vendor boundaries. MCP handles agent-to-tool access - how a single agent retrieves context from external data systems and tools. That distinction sounds clean on paper. In a real system it takes a while to feel it, because both protocols sit between your agent and "the outside world." The difference is what kind of entity lives on the other side.
What each layer actually does
MCP standardizes the connection between an agent and a tool or data source. A database, a search index, a calendar API - these are resources the agent reads or writes. MCP is an open standard that gives AI models a universal way to connect to external tools, data sources, and services. Introduced in November 2024, it has since become the de facto protocol for connecting AI to the real world, adopted by OpenAI, Google DeepMind, Microsoft, and thousands of development teams. It solves the plumbing problem of getting context into a model without writing a fresh connector for every data source.
A2A was designed for a different moment: when you already have two running agents and you want one to delegate a task to the other without either side knowing how the other was built. The protocol enables AI agents to discover, authenticate, and delegate tasks to other AI agents across different platforms and frameworks. Unlike MCP, which connects agents to tools, A2A connects agents to agents.
The mental model that helps: use MCP when your agent needs to fetch something; use A2A when your agent needs to hand off something.
How A2A coordination actually works
Agents communicate using a structured Task object that represents discrete units of work progressing through defined lifecycle states, including submitted, working, input-required, and completed. Each remote agent publishes an Agent Card - a JSON document at a well-known URL - declaring what tasks it can perform, what inputs it accepts, and what authentication it requires. A2A uses HTTP, Server-Sent Events, and JSON-RPC 2.0 for transport, and Agent Cards for capability advertisement. No proprietary transport layer. If you already know how to call a JSON API, you already know most of the wire protocol.
Agents interact without needing to share internal memory, tools, or proprietary logic, ensuring security and preserving intellectual property. That property matters more than it might seem. A Salesforce-built procurement agent and a ServiceNow-built fulfillment agent can coordinate without either vendor opening up their internals to the other.
A2A was originally launched by Google in April 2025. By June 2025, Google donated it to the Linux Foundation, where it now sits under neutral governance with support from more than 150 organizations.
The Linux Foundation announced the A2A project in June 2025 as an open protocol created by Google for secure agent-to-agent communication. It was developed to address the challenges of scaling AI agents across enterprise environments and empowers developers to build agents that seamlessly interoperate, regardless of platform, vendor, or framework.
Where the hype runs ahead of reality
A2A launched in April 2025, making it relatively new with limited production evidence. The spec is solid and the SDKs exist in Python, Go, JavaScript, Java, and .NET, but most teams adopting it are still in the evaluation or early integration phase. The task lifecycle - submitted, working, input-required, completed, failed - reads cleanly in a diagram. In production, practical deployments quickly expose gaps that matter for automation at scale.
One gap worth knowing about before you build: the security model. Enterprise analyses of MCP implementations demonstrate that without rigorous zero-trust controls, attackers may exploit unsecured tool endpoints or manipulate context payloads. A2A and MCP provide the plumbing for agent interoperability, but they do not yet enforce the fine-grained confidentiality, integrity, and consent guarantees required for sensitive data exchange. The protocols assume you will add that layer yourself. If your agents will touch financial data, health records, or anything regulated, that is a gap to close before go-live, not after.
A second gap: context consistency. Both protocols are transport mechanisms. They move tasks and context around; they do not create governed, consistent context. Two agents can coordinate perfectly via A2A and still return contradictory results if they are drawing on different definitions of the same business concept. The protocol cannot fix that; your data layer has to.
A2A and MCP are complementary standards: MCP provides agent-to-tool communication, standardizing how an agent connects to its tools, APIs, and resources to get information. Most production multi-agent systems will use both.
What this means for a team building today
The practical question is where you draw your integration boundaries. If you are building a single agent that needs access to a set of tools and data - your Jira instance, a SQL database, a knowledge base - MCP is the right layer. Beagle, for example, connects to the tools in your Slack or Teams workspace through exactly this kind of integration.
If you are building a system where a coordinator agent needs to delegate sub-tasks to specialist agents - a research agent, a scheduling agent, a compliance-check agent - that is where A2A earns its place. In a multi-agent system, you often have a coordinator agent managing the work and specialist agents executing specific tasks. Without a shared protocol, that coordination requires bespoke integration - the coordinator has to know exactly how each specialist works, what inputs it accepts, and how to parse its outputs. A2A standardizes that contract.
Most teams working on multi-agent systems right now will find they need to solve MCP before they need to solve A2A. Get stable, governed tool access working first. Then, as your system grows to include agents owned by different teams - or different vendors - A2A gives you a standard way to wire the seams.
The Linux Foundation move is the signal that the protocol is settling into long-term infrastructure. It is not production-hardened for every scenario yet. But the direction is clear, the wire format is boring and familiar, and the conceptual model is genuinely useful. That is a reasonable foundation to start building against.