PyTorch HUD API
MCP harness for PyTorch HUD API https://hud.pytorch.org/
Installation
Installing for Claude Desktop
Manual Configuration Required
This MCP server requires manual configuration. Run the command below to open your configuration file:
npx mcpbar@latest edit -c claudeThis will open your configuration file where you can add the PyTorch HUD API MCP server manually.
PyTorch HUD API with MCP Support
A Python library and MCP server for interacting with the PyTorch HUD API, providing access to CI/CD data, job logs, and analytics.
Overview
This project provides tools for PyTorch CI/CD analytics including:
- Data access for workflows, jobs, and test runs
 - Efficient log analysis for large CI logs
 - ClickHouse query integration for analytics
 - Resource utilization metrics
 
Usage (for humans)
# Install from GitHub repository
pip install git+https://github.com/izaitsevfb/claude-pytorch-treehugger.git
claude mcp add hud pytorch-hud
Development
# Install dependencies (if not installing with pip)
pip install -r requirements.txt
# Start MCP server
python -m pytorch_hud
Key Features
Data Access
get_commit_summary: Basic commit info without jobsget_job_summary: Aggregated job status countsget_filtered_jobs: Jobs with filtering by status/workflow/nameget_failure_details: Failed jobs with detailed failure infoget_recent_commit_status: Status for recent commits with job statistics
Log Analysis
download_log_to_file: Download logs to local storageextract_log_patterns: Find errors, warnings, etc.extract_test_results: Parse test execution resultsfilter_log_sections: Extract specific log sectionssearch_logs: Search across multiple logs
Development
# Run tests
python -m unittest discover test
# Type checking
mypy -p pytorch_hud -p test
# Linting
ruff check pytorch_hud/ test/
Documentation
- CLAUDE.md: Detailed usage, code style, and implementation notes
 - mcp-guide.md: General MCP protocol information
 
License
MIT
Details:
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