The interoperability stack

Three layers connect agents to everything else: WebMCP for structured web access, MCP for tools and data, A2A for colleagues across boundaries. Without them every integration is bespoke and lock-in is guaranteed. MCP gives an agent capabilities; A2A gives an agent colleagues.

The stack at working resolution: what each layer standardizes, and why both protocols living at the Linux Foundation matters. The question is whether you are building on the standard stack or accumulating integration debt.

Two protocols, two problems

Without standardized connection layers, every integration is bespoke, every agent-to-agent handoff is custom code and vendor lock-in is all but guaranteed. Two protocols address two distinct problems.

MCP (Model Context Protocol) is the de facto agent-to-tool protocol in 2026. It standardizes how an agent connects to external tools, data sources and services. A2A (Agent-to-Agent) standardizes how agents discover, communicate and delegate work to each other across organizational and framework boundaries. Put simply, MCP gives an agent capabilities and A2A gives an agent colleagues.

The three-layer stack

A three-layer protocol stack appears to be emerging as the most effective architecture. The stack comprises WebMCP, which is structured web access for agents providing machine-readable sitemaps and other artifacts for agent consumption. MCP, which provides the agent with access to tools and data. And A2A, which helps agents coordinate, delegate and discover each other across boundaries.

Above the protocols: the mesh

At the enterprise scale, McKinsey describes an architecture paradigm that sits on top of these protocols: a composable, distributed, vendor-agnostic mesh with five design principles (composability, distributed intelligence, layered decoupling, vendor neutrality, governed autonomy) and seven capabilities (agent discovery, asset registry, observability, authentication, evaluations, feedback management, compliance). It is important to note that according to McKinsey this approach cannot be bolted onto existing Gen AI stacks. It requires a fundamental shift from static, LLM-centric infrastructure to a dynamic, agent-based one.

Alignment, and what it buys

The fact that the Linux Foundation has become the permanent home for both MCP and A2A, while both enjoy broad enterprise backing, demonstrates a level of industry alignment on open standards that is at the very least unusual. The interoperability problem, it seems, is close to solved or at least converging rapidly to that point. As such the question soon will become whether we are building on the standard stack or accumulating integration debt.

The framework question

A question that naturally follows protocol selection is framework selection. The landscape of agent frameworks (LangChain, CrewAI, Autogen, Semantic Kernel and others) is evolving rapidly with no clear consolidation yet. The selection criteria are organization-specific: existing technology stack, team expertise, deployment constraints and vendor relationships. What matters more than which framework is chosen is whether the choice preserves governed autonomy, harness-first design and adherence to open interoperability standards. A framework that locks the organization into proprietary orchestration patterns or bypasses the governance layers will create more problems than it solves, regardless of its benchmarks.