Usage: mlr mcp [options]
Runs a Model Context Protocol (MCP) server exposing Miller to AI agents.

The server speaks JSON-RPC over stdin/stdout (MCP "stdio" transport); it is
meant to be spawned by an MCP client rather than run interactively. Example
registration, for Claude Code:

  claude mcp add miller -- mlr mcp

Tools exposed:
  list_capabilities  the mlr help --as-json catalog/index, filterable
  which              intent -> ranked matching verbs/functions/flags/keywords
  validate_dsl       parse/type-check a put/filter expression without running it
  describe_data      field names/types/cardinality/values of input data
  run                run an mlr command line

Also exposed: an agent playbook, as MCP prompt "miller-playbook" and MCP
resource "miller://playbook", encoding the discover -> constrain -> validate
-> run loop.

Commands started by the run/validate_dsl/describe_data tools are run with
MLR_NO_SHELL=1 -- the DSL system/exec functions, piped redirects, and
--prepipe/--prepipex fail cleanly -- and with MLR_ERRORS_JSON=1 so errors
come back structured.

Options:
 --allow-shell           Do not set MLR_NO_SHELL=1 on subprocesses, re-enabling
                         the DSL system/exec functions for agent-run commands.
 --timeout {seconds}     Default wall-clock limit for the run tool (default 60).
 --max-output-bytes {n}  Cap captured stdout/stderr per command (default 1048576).
 -h or --help            Show this message.