Axiom MCP

Axiom is an event data platform that ingests logs, traces, and other high volume telemetry, stores it cheaply, and queries it with Axiom Processing Language, a pipe based query syntax. The Axiom MCP server gives an AI assistant a direct line to that data, so questions about production behavior get answered from real events instead of from guesses. The server keeps a small, well scoped tool surface. An agent can list the datasets available to the account, fetch the schema of a dataset to learn which fields exist and what types they hold, and then run an APL query against it. It can also read saved and starred queries the team has already written, list configured monitors, and pull monitor run history to see when alerts fired. Schema discovery is the part that matters most in practice, because without it a model invents field names, and with it the query it writes is grounded in the real shape of the data. The common workflow is incident triage. An engineer describes a symptom, the assistant inspects the schema, writes an aggregation over the relevant time window, and returns grouped counts or error clusters rather than a raw log dump. The exposed tools are read oriented and authenticated with an Axiom API token, so the blast radius stays limited to whatever that token is allowed to see.