PyTorch HUD
Summary
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.
Available Actions(10)
get_commit_summary
Basic commit info without jobs.
get_job_summary
Aggregated job status counts.
get_filtered_jobs
Jobs with filtering by status, workflow, or name.
get_failure_details
Failed jobs with detailed failure info.
get_recent_commit_status
Status for recent commits with job statistics.
download_log_to_file
Download logs to local storage.
extract_log_patterns
Find errors, warnings, etc.
extract_test_results
Parse test execution results.
filter_log_sections
Extract specific log sections.
search_logs
Search across multiple logs.
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