How do agents talk to each other?
Two standards compared. Switch protocol and press "Send message" to see who talks to whom, and how.
For an AI agent to be truly useful, it must be able to access business data and tools and, increasingly, collaborate with other agents. Until recently, every integration required bespoke development — costly and fragile. Today, two standards are changing the rules of the game: the Model Context Protocol (MCP) and the Agent-to-Agent (A2A) protocol. These are the technical foundations of the internet of agents, and understanding them is strategically important for anyone who wants to automate business processes without becoming locked into proprietary solutions. In this article we explain what MCP and A2A are, how they complement each other, and why they matter for your business.
The Problem: Isolated Agents
A Large Language Model, on its own, is isolated: it has no real-time access to business data, cannot perform actions on management systems, and cannot communicate with other agents. For years, connecting an agent to a CRM, a database, or an API has required custom integrations — one for every combination of model and tool. The result: high costs, complex maintenance, and technological lock-in. Interoperability standards are designed precisely to solve this problem.
What Is the Model Context Protocol (MCP)?
The Model Context Protocol is an open-source standard that addresses the fundamental limitation of LLMs: their isolation from external data and systems. MCP defines a standardised way to connect AI agents to tools, databases, APIs, and business applications. It is, in essence, the "vertical layer" that connects the agent to its tools.
The Adoption of MCP
MCP experienced remarkable adoption in 2025–2026:
- Over 97 million downloads and adoption by Anthropic, OpenAI, Google, and Microsoft.
- Built-in support in tools such as Claude, Cursor, and Gemini, and in the leading cloud providers.
- In practice, MCP has "won" the agent-to-tool connection layer, becoming the de facto standard.
What Is the A2A (Agent-to-Agent) Protocol?
If MCP connects the agent to tools, the A2A (Agent-to-Agent) protocol, promoted by Google, solves a complementary problem: enabling agents to communicate with one another, even across organisational boundaries. It is the first widely adopted standard for inter-agent communication — the "horizontal layer" that allows agents to exchange information and coordinate activities dynamically.
The Two-Level Stack: MCP + A2A
The combination of the two standards is becoming the default architecture for enterprise AI agent deployments:
- MCP — vertical integration: connects each agent to its tools, data, and APIs in a standardised manner.
- A2A — horizontal coordination: enables agents to communicate, delegate, and collaborate with one another.
Together, MCP and A2A constitute the foundations of multi-agent systems: MCP gives each agent the hands to act, A2A gives them the voice to coordinate.
Why These Standards Matter for Your Business
Interoperability standards have concrete practical implications for businesses:
Reduction of Integration Costs
With MCP, an integration built once works with any compatible agent, eliminating repeated custom development and driving down costs.
No Technological Lock-In
Adopting open standards means not being held captive by a single vendor. You can change model or platform without having to rebuild all your integrations, protecting your investments.
Scalability and Composability
Standards make it straightforward to add new agents and tools, building composable ecosystems that grow with the business.
Future-Readiness
With Gartner predicting that 40% of enterprise applications will feature AI agents by the end of 2026, and a growing share of B2B transactions being mediated by agents, adopting interoperability standards today means being prepared for the agent economy of tomorrow.
How to Approach Interoperability
- Prioritise MCP-compatible tools when choosing automation platforms.
- Design API-first: expose your systems through standardised, well-documented interfaces.
- Think in composable terms: build reusable integrations rather than monolithic solutions.
- Monitor the evolution of standards (MCP, A2A, ACP) to align your architectural choices accordingly.
Conclusion
MCP and A2A are the protocols building the internet of AI agents: the former connects agents to tools, the latter enables them to collaborate with one another. For businesses, understanding and adopting these standards means reducing integration costs, avoiding lock-in, and preparing for a future in which AI agents are everywhere. This is not merely a technical matter for specialists, but a strategic choice that determines future flexibility and competitiveness. If you want to build an interoperable, future-proof automation architecture, contact us for specialised technical consultancy.
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