MCP as Observability Interface: Connecting AI Agents to Kernel Tracepoints

Model Context Protocol (MCP) is emerging as the critical interface layer between AI agents and infrastructure observability, with major vendors like Datadog already shipping MCP servers while security risks around authentication and data access are surfacing. IT leaders face a strategic choice between wrapping existing observability platforms with MCP adapters versus building MCP-native observability that provides raw kernel-level telemetry for root-cause analysis—the latter enabling AI agents to solve complex infrastructure problems that aggregate metrics cannot surface. This shift fundamentally changes the architecture of observability stacks and introduces new security considerations around AI agent access to sensitive system telemetry, positioning MCP as a primary control point for infrastructure automation and governance.