MCP Design Patterns: 6 Architectures for AI Tool Servers
Six practical MCP server architectures: API wrapper, composite service, resource-oriented, agent-backed, event-driven, and gateway patterns explained.
As the Model Context Protocol becomes ubiquitous, the architecture behind MCP servers gets far less attention than the protocol itself. A thin API wrapper, a local resource server, and an orchestration layer for long-running jobs all expose capabilities through MCP, but none of them should be built the same way.
Six recurring patterns are outlined as a practical decision aid: the direct API wrapper for stable, low-risk endpoints; the composite service that aggregates multiple backend calls into one task-level tool; the resource-oriented server that exposes read-only context instead of actions; the agent-backed tool that delegates subtasks to a specialized model or reasoning component; the event-driven control surface for asynchronous, long-running operations; and the gateway or federated MCP that centralizes auth, routing, and policy across multiple domain servers.
For each pattern, the analysis covers when it fits, when it doesn't, typical use cases, and the main risks — from tool bloat and overexposure to ambiguous job state and loss of traceability across agent hops. The core takeaway for engineers: an MCP server is a boundary carrying data, behavior, permissions, and risk, not just a bag of callable functions — choosing the wrong abstraction level makes integrations fragile.