Agent Protocol Fragmentation: Designing for A2A, MCP, and What Comes Next

Most teams picking an agent protocol are actually making three separate decisions at once — and treating them as one is why so many integrations break the moment a second framework enters the picture.

The three decisions are: how your agent talks to tools and data (vertical integration), how your agent collaborates with other agents (horizontal coordination), and how your agent surfaces state to a human interface (interaction layer). Google's A2A, Anthropic's MCP, and OpenAPI-based REST solve for different layers of this stack. When engineers conflate them, they either over-engineer a single-agent setup with multi-agent machinery, or under-engineer a multi-agent workflow with single-agent tooling. Both failures are expensive to refactor once in production.

The Three Layers That Protocols Actually Solve

Before comparing protocols, you need a mental model of what the agent interface stack looks like.

The tool integration layer is where an agent reaches outward to databases, APIs, and external services. This is the domain of MCP. An agent needs to read from a vector store, call a weather API, or invoke a code interpreter — MCP defines the client-server contract for that. The architecture is fundamentally vertical: one agent, many tools.

The agent coordination layer is where agents reach sideways to other agents. This is the domain of A2A. A planner agent dispatches work to a specialized code-writing agent or a document-summarization agent, tracks task lifecycle, and collects results. The architecture is fundamentally horizontal: many agents, peer relationships.

The interaction layer is where an agent surfaces state to a user interface — streams intermediate results, renders structured components, handles back-and-forth clarification. This is the domain of newer projects like AG-UI, still early in standardization.

Getting confused about which problem you're solving sends you down the wrong protocol path. An engineer who treats A2A as a replacement for MCP will end up writing agent coordination code for what is essentially a single-agent tool invocation problem.

What MCP Actually Optimizes For

MCP, released by Anthropic in November 2024, reached 97 million monthly SDK downloads by early 2026 — a number that tells you something about how badly the ecosystem needed a tool integration standard.

The core bet MCP makes is that tool access control matters more than agent identity. Its trust model is centralized: the host application (the thing running the LLM) is the authority. When an agent wants to call a tool, the host mediates that call, enforces user consent, and controls what data the server can access. Servers are trusted only to the extent the host grants them.

This design works extremely well for single-agent setups — a coding assistant that reads files and executes shell commands, a customer service bot that queries a CRM. It works less well when multiple agents need to share a tool server, because the trust model doesn't cleanly handle the question of which agent's permissions apply. Some teams work around this with per-agent server instances, which is functional but operationally heavy.

MCP's transport stack (JSON-RPC 2.0 over stdio, HTTP, or SSE) is deliberately simple. The November 2025 spec update added asynchronous operations and stateless server support, which extended its reach to higher-latency tool backends. The tradeoff is that MCP has no concept of task lifecycle — it handles discrete calls, not long-running delegated work.

What A2A Actually Optimizes For

Google launched A2A in April 2025 with 50+ partner organizations and reached v1.0 in early 2026, now governed by the Linux Foundation under the Agentic AI Foundation alongside MCP.

The core bet A2A makes is that agent identity matters more than tool access control. Its trust model is distributed: agents advertise their capabilities via JSON-based "Agent Cards," negotiate what protocols they support, and authenticate with each other without relying on a central host. This is peer-to-peer identity, not client-server authorization.

A2A is designed for scenarios where you can't see inside the other agent. When your planner dispatches a task to a third-party agent at a different company, you don't know what framework that agent runs on, what tools it has, or how it handles errors internally. A2A handles this opacity by design — it specifies task lifecycle states (submitted, working, completed, failed), capability discovery, and user experience negotiation, all without requiring the remote agent to expose internals.

IBM launched a competing REST-based protocol called ACP in March 2025, which merged into A2A under the Linux Foundation in August 2025. This merger is worth noting because it shows the industry converging toward A2A as the canonical answer for the horizontal coordination layer — the fragmentation that seemed inevitable in early 2025 didn't materialize at the protocol level.

OpenAPI: The Lingua Franca That Predates Both

OpenAPI (now at v3.2.0) was not designed for agents, but it has become load-bearing infrastructure for the protocol stack in ways neither A2A nor MCP anticipated.

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