The 'USB-C' for Agents: As MCP and Persistent Memory Spread, the New Risk Is Context Fragility

In 2026, AI agents are no longer standalone boxes; they are an ecosystem that connects to each other and to external systems. Two protocols now standardize that connection: MCP (Model Context Protocol) for tool access and A2A (Agent2Agent) for agent-to-agent coordination.

MCP: the USB-C of AI

By standardizing how models securely request and receive data from external systems, MCP has become 'the USB-C cable for AI'. Major cloud providers, including Google Cloud, natively support the protocol, cutting the need to write custom glue code for every integration.

Why persistent memory matters

Context windows are ephemeral; once a session ends, the agent forgets everything. Memory systems create a durable, structured information layer so agents stay useful over time. MCP memory servers expose the same memory to multiple agents in multi-agent workflows without duplicating logic.

Risks that emerge as it spreads

• Context fragility: as the window fills with complex JSON schemas, the model's attention dilutes — it picks the wrong tool or hallucinates tool arguments.
• Competing standards: fragmentation risk between Anthropic's MCP, Google's A2A and OpenAI's approach.
• Security: every tool opened to an external system is a new attack surface and a potential data-leak path.
• Authorization and policy: controlling which agent may call which tool, with which data.

The remot angle

remot brings MCP and agent protocols into an enterprise orchestration layer: it routes tool calls from a single place, enforces policy on which agent may use which tool and data, and measures the cost and trace of every call. That way interoperability becomes a governed, auditable layer rather than an uncontrolled pile of tools.