Our clients often ask us whether we use MCP or A2A when developing generative applications. In reality, these are complementary paradigms, where A2A handles communication between agents and MCP connects each agent with its tools.
MCP acts as a universal adapter that standardises the way AI models access external data and tools. Its purpose is to enable agents to use available resources, whether local or remote, without the need for custom integrations.
For its part, A2A is an open standard that facilitates communication between agents through a discovery mechanism, where each agent exposes its capabilities, versions, and access points. This approach allows agents to be coordinated dynamically according to the task to be performed, activating them based on natural language instructions.
At WayOps, we combine MCP and A2A in multi-agent applications for fraud detection, where a first agent uses MCP to evaluate transactions in real time with an ML model and notifies a second agent of any suspicious transactions using A2A. The second agent then accesses the customer’s history to assess whether this is normal behaviour. If it is not, we notify a third agent who blocks the transaction and access to the account.
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