Using the MCP Server¶

This guide covers interacting with Stargazer through the MCP server.

Running a Task (Ad-hoc)¶

Use run_task for experimentation. Provide filters to select assets and inputs for scalar parameters:

run_task(
    task="align_with_bwa",
    filters={"build": "GRCh38", "sample_id": "NA12878", "asset": ["reference", "r1", "r2"]},
    inputs={}
)

The server calls assemble(**filters), matches assets to task parameters by _asset_key, and executes the task.

Use run_workflow for production pipelines. Pass only scalar inputs — the workflow handles its own assembly:

run_workflow(
    workflow="germline_single_sample",
    inputs={"build": "GRCh38", "sample_id": "NA12878"}
)

Tool	Use
`query_files(keyvalues={"asset": "reference", "build": "GRCh38"})`	Find files by metadata
`upload_file(path="/data/ref.fa", keyvalues={"asset": "reference", "build": "GRCh38"})`	Upload with metadata
`download_file(file_id="abc123")`	Download to local cache
`delete_file(file_id="abc123")`	Remove a file

MCP resources provide read-only context: