Concept comparison

Agent control plane vs MCP: connection is not governance

MCP standardizes how an AI application discovers and calls tools. An agent control plane governs which agents can call which tools, under what policy, with which credentials, and with what audit trail.

What MCP solves

MCP gives tools and resources a consistent interface. It reduces bespoke integration work and makes capability discovery portable across compatible clients and servers.

Design principle

Centralize the decision and evidence. Keep agent execution loosely coupled from any single model, framework, or tool protocol.

What the control plane solves

The control plane owns workload identity, policy, credential delivery, approval, budgets, telemetry, evaluations, tenancy, and lifecycle. It can govern MCP tools as well as native APIs, queues, databases, and model endpoints.

The useful mental model

Treat MCP as a capability protocol inside the governed data path. Let the control plane decide access and issue scoped credentials; let MCP carry the authorized tool interaction.

Generate a system-specific version

Use the interactive builder to translate these principles into layers and controls for your fleet size, framework, model set, tools, identity, and data requirements.

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