Inspektor Gadget MCP Server

Example Use Cases

• 1

  Autonomously select and run kernel-level observability gadgets for troubleshooting.

• 2

  Correlate and analyze low-level telemetry data to identify root causes in Kubernetes clusters.

• 3

  Manage the lifecycle of Inspektor Gadget tools and retrieve enriched telemetry results.

Description

The Inspektor Gadget MCP Server enables AI agents to autonomously deploy and run eBPF-powered gadgets that collect low-level kernel telemetry such as DNS traces, TCP connections, and process executions. It transforms raw telemetry into structured JSON data that LLMs can analyze to perform confident, data-driven root cause analysis directly from IDEs or chat interfaces. This server supports flexible deployment modes, dynamic tool registration, and both foreground and background gadget operation, enhancing Kubernetes troubleshooting with AI-powered observability.