This PyTorch HUD API implementation provides a Python library and MCP server for accessing PyTorch's CI/CD analytics data, enabling developers to investigate build failures and trunk health issues. Built with FastMCP, it offers tools for retrieving workflow and job information, analyzing large log files efficiently, executing ClickHouse queries against CI metrics, and monitoring resource utilization. The server exposes both synchronous and asynchronous functions through a standardized interface, making it valuable for PyTorch contributors debugging CI failures, investigating test flakiness, or analyzing performance trends across the CI infrastructure.
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Highlight AIRetrieve basic commit information without job details.
Get aggregated counts of job statuses.
Retrieve jobs filtered by status, workflow, or name.
Obtain detailed information about failed jobs.
Fetch the status of recent commits along with job statistics.
Download logs to local storage.
Identify errors, warnings, and other patterns in logs.
Parse and retrieve test execution results from logs.
Extract specific sections from logs.
Search for specific terms across multiple logs.
