How Memory Works In Agent-To-Agent Protocols

A2A, an open Agent-to-Agent protocol published by Google in 2025 and contributed to the Linux Foundation, standardizes agent discovery and task collaboration through AgentCards, task lifecycles, and transport bindings such as JSON-RPC, gRPC, and REST, but it does not automatically transfer an agent’s accumulated context. Unlike MCP, which connects an individual agent to tools and data sources, A2A governs communication among agents, leaving receiving agents dependent on whatever context is explicitly included in a task payload. Multi-agent systems consequently face isolated per-agent context, information loss during task handoffs, and cross-session amnesia, while simply attaching more history to delegated tasks creates growing payloads, latency, incomplete records, and orchestration bottlenecks. The proposed alternative is a shared memory layer, such as Mem0, where every agent retrieves relevant user-specific context at the start of work and stores outcomes afterward, enabling continuity across agents and sessions without transferring full histories in every task. However, shared memory also introduces risks including concurrent-write conflicts, incorrect information spreading across the network, and stale preferences, so agents should validate stored memories against current requests and systems may need write coordination.

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