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PyTorch HUD MCP Server

by izaitsevfb
GitHub
Python
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hybrid server

The server is able to function both locally and remotely, depending on the configuration or use case.

Integrations

  • Provides ClickHouse query integration for analytics of PyTorch CI/CD data

  • Provides access to PyTorch CI/CD data, job logs, and analytics

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 jobs
  • get_job_summary: Aggregated job status counts
  • get_filtered_jobs: Jobs with filtering by status/workflow/name
  • get_failure_details: Failed jobs with detailed failure info
  • get_recent_commit_status: Status for recent commits with job statistics

Log Analysis

  • 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

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

This server cannot be installed

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Provides access to PyTorch CI/CD analytics data including workflows, jobs, test runs, and log analysis through an MCP interface.

  1. Overview
    1. Usage (for humans)
      1. Development
        1. Key Features
          1. Data Access
            1. Log Analysis
            2. Development
              1. Documentation
                1. License

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