mcp

This command runs an MCP (Model Context Protocol) server so AI agents and automation tools can query KernelCI results and drive Maestro jobs.

MCP support is an optional extra:

pip install kci-dev[mcp]

Read-only dashboard query tools (trees, builds, boots, tests, hardware, known issues) are always available and need no configuration. Maestro node lookup tools are enabled when the configured instance has an api URL, and job retry/checkout trigger tools when it also has a pipeline URL and a token. See the config file documentation. Use the top-level --instance option (kci-dev --instance staging mcp) to select which configured instance the server uses.

Run with the default stdio transport for local agents:

kci-dev mcp

Example Claude Code registration:

claude mcp add kernelci -- kci-dev mcp

Run as an HTTP server (streamable HTTP transport):

kci-dev mcp --transport http --host 127.0.0.1 --port 8000

The HTTP transport has no authentication layer: anyone who can reach the port can call the exposed tools, including the job-triggering ones, using the token from your configuration. Keep it bound to 127.0.0.1, prefer the stdio transport for local use, and do not expose the port beyond hosts you trust.

Tools that change state (retry_job, trigger_checkout) are annotated as non-read-only so MCP clients can ask for confirmation before calling them.

Responses are sized for context-limited clients: get_summary returns compact aggregates unless detail=true is passed, and the list tools paginate (default limit of 20) and accept a fields list to return only the named keys per entry. Prefer status/arch filters, small limits and field projection when exploring large trees.