Claude Pytorch Treehugger
What is Claude Pytorch Treehugger
claude-pytorch-treehugger is a Python library and MCP server designed for interacting with the PyTorch HUD API, enabling access to CI/CD data, job logs, and analytics.
Use cases
Use cases include analyzing CI/CD data, extracting job logs, monitoring resource utilization, and performing detailed log analysis to identify errors and warnings.
How to use
To use claude-pytorch-treehugger, install it via pip from the GitHub repository with the command pip install git+https://github.com/izaitsevfb/claude-pytorch-treehugger.git. After installation, you can add the MCP server using claude mcp add hud pytorch-hud.
Key features
Key features include data access for workflows and jobs, efficient log analysis for large CI logs, ClickHouse query integration for analytics, and resource utilization metrics.
Where to use
claude-pytorch-treehugger can be used in software development environments that utilize CI/CD pipelines, particularly those that leverage PyTorch for machine learning projects.
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Overview
What is Claude Pytorch Treehugger
claude-pytorch-treehugger is a Python library and MCP server designed for interacting with the PyTorch HUD API, enabling access to CI/CD data, job logs, and analytics.
Use cases
Use cases include analyzing CI/CD data, extracting job logs, monitoring resource utilization, and performing detailed log analysis to identify errors and warnings.
How to use
To use claude-pytorch-treehugger, install it via pip from the GitHub repository with the command pip install git+https://github.com/izaitsevfb/claude-pytorch-treehugger.git. After installation, you can add the MCP server using claude mcp add hud pytorch-hud.
Key features
Key features include data access for workflows and jobs, efficient log analysis for large CI logs, ClickHouse query integration for analytics, and resource utilization metrics.
Where to use
claude-pytorch-treehugger can be used in software development environments that utilize CI/CD pipelines, particularly those that leverage PyTorch for machine learning projects.
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Content
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
Dev Tools Supporting MCP
The following are the main code editors that support the Model Context Protocol. Click the link to visit the official website for more information.
