AojdevStudio/microsoft-mcp

GitHub Actions CI/CD Pipeline

This directory contains comprehensive GitHub Actions workflows for the Microsoft MCP project, providing automated testing, security scanning, releases, and maintenance.

🚀 Workflow Overview

Core Workflows

1. CI Pipeline (ci.yml)

Triggers: Push to main/develop/feature branches, Pull Requests Duration: ~15-20 minutes Purpose: Comprehensive testing and quality assurance

Jobs:

• Code Quality & Security: Linting (ruff), formatting, type checking (mypy), security audit
• Tests: Multi-platform testing (Ubuntu, macOS, Windows) with Python 3.12/3.13
• Email Framework Tests: Specialized testing for email template system
• Build: Package building and validation
• Deployment Check: Version bump validation for main branch

Key Features:

• ✅ Multi-OS and multi-Python version testing
• ✅ Comprehensive caching strategy for dependencies
• ✅ Security scanning with pip-audit
• ✅ Code coverage reporting with Codecov integration
• ✅ Artifact uploads for debugging and analysis

2. Release Pipeline (release.yml)

Triggers: Git tags (v*.*.*), Manual dispatch Duration: ~20-30 minutes Purpose: Automated version releases and publishing

Jobs:

• Validate Release: Version format and conditions validation
• Pre-Release Tests: Full CI pipeline execution before release
• Build Release: Package building with changelog generation
• GitHub Release: Automated GitHub release creation
• PyPI Publishing: Automated package publishing to PyPI
• Post-Release: Development version preparation and notifications

Key Features:

• ✅ Semantic version validation
• ✅ Automated changelog generation
• ✅ PyPI publishing with trusted publishing (OIDC)
• ✅ Pre-release vs stable release handling
• ✅ Automatic development version bumping

3. Security Scanning (security.yml)

Triggers: Daily schedule, Push to main, Pull Requests, Manual Duration: ~15-25 minutes Purpose: Comprehensive security analysis

Jobs:

• Dependency Scan: pip-audit and Safety vulnerability checking
• SAST Analysis: Bandit security linting and Semgrep analysis
• CodeQL Analysis: GitHub's semantic code analysis
• Secret Scanning: TruffleHog and gitleaks secret detection
• License Check: License compatibility verification
• Security Summary: Consolidated security status reporting

Key Features:

• ✅ Multiple security scanning tools integration
• ✅ SARIF report uploads for GitHub Security tab
• ✅ License compliance checking
• ✅ Automated vulnerability reporting

4. Maintenance & Updates (maintenance.yml)

Triggers: Weekly schedule (Sunday 3 AM UTC), Manual dispatch Duration: ~10-20 minutes Purpose: Automated repository maintenance

Jobs:

• Dependency Updates: Automated dependency version updates
• Actions Updates: GitHub Actions version updates
• Cache Cleanup: Old cache cleanup for storage optimization
• Health Check: Repository health assessment and metrics

Key Features:

• ✅ Automated PR creation for updates
• ✅ Compatibility testing before updates
• ✅ Repository health monitoring
• ✅ Maintenance recommendations

Specialized Workflows

5. Pull Request Validation (pr-validation.yml)

Triggers: Pull Request events Duration: ~10-15 minutes Purpose: PR quality validation and automation

Features:

• ✅ PR structure validation (title format, description quality)
• ✅ Changed files analysis and categorization
• ✅ Automated labeling and size assessment
• ✅ Code quality quick checks
• ✅ Breaking changes detection
• ✅ Security quick scan for potential secrets

6. Notifications & Status (notifications.yml)

Triggers: Workflow completions, Issues, PRs, Releases Duration: ~2-5 minutes Purpose: Status tracking and notifications

Features:

• ✅ Workflow status notifications
• ✅ PR lifecycle tracking
• ✅ Issue auto-triaging and labeling
• ✅ Release announcements
• ✅ Daily status summaries

🔧 Configuration Details

Environment Variables

PYTHON_VERSION: "3.12"        # Primary Python version
CACHE_VERSION: "v1"           # Cache invalidation control

Required Secrets

# GitHub (automatically provided)
GITHUB_TOKEN: <automatic>     # Repository access

# PyPI Publishing (for releases)
# Configure at: https://pypi.org/manage/account/publishing/
# Uses OIDC trusted publishing - no manual token needed

# Optional: External integrations
SLACK_WEBHOOK_URL: <optional> # Slack notifications
CODECOV_TOKEN: <optional>     # Enhanced Codecov integration

Cache Strategy

The workflows implement a sophisticated caching strategy:

• UV Dependencies: Cached by OS, Python version, and lock file hash
• Multi-level Cache Keys: Primary + fallback restore keys
• Job-specific Caches: Different cache keys for build, test, security jobs
• Automatic Cleanup: Weekly cache cleanup to optimize storage

Security Measures

• Minimal Permissions: Each workflow uses least-privilege permissions
• Token Security: OIDC trusted publishing for PyPI (no long-lived tokens)
• Secret Scanning: Multiple tools for detecting leaked credentials
• SARIF Integration: Security results integrate with GitHub Security tab
• Dependency Auditing: Regular vulnerability scanning

📊 Monitoring & Insights

Status Badges

Add these badges to your README for visibility:

[![CI Pipeline](https://github.com/elyxlz/microsoft-mcp/workflows/CI%20Pipeline/badge.svg)](https://github.com/elyxlz/microsoft-mcp/actions/workflows/ci.yml)
[![Security Scanning](https://github.com/elyxlz/microsoft-mcp/workflows/Security%20Scanning/badge.svg)](https://github.com/elyxlz/microsoft-mcp/actions/workflows/security.yml)
[![codecov](https://codecov.io/gh/elyxlz/microsoft-mcp/branch/main/graph/badge.svg)](https://codecov.io/gh/elyxlz/microsoft-mcp)

Workflow Analytics

• Actions Usage: Monitor workflow run times and costs
• Success Rates: Track workflow reliability
• Security Alerts: Review security tab regularly
• Artifact Storage: Monitor artifact storage usage

🚦 Workflow Triggers Summary

🔄 Release Process

Automated Release (Recommended)

1. Merge to main: All changes go through PR validation
2. Version bump: Update version in pyproject.toml
3. Create tag: git tag v1.2.3 && git push origin v1.2.3
4. Automated pipeline: Release workflow handles the rest

Manual Release

1. Go to Actions → Release Pipeline
2. Click Run workflow
3. Enter version number (e.g., 1.2.3)
4. Choose if it's a pre-release
5. Click Run workflow

Release Artifacts

• GitHub Release: Changelog and source archives
• PyPI Package: Installable wheel and source distribution
• Artifacts: Build artifacts for debugging

🛠️ Development Workflow

For Contributors

1. Fork & Branch: Create feature branch
2. Local Testing: Run uv run pytest locally
3. Create PR: Automated validation runs
4. Address Feedback: Respond to reviews and checks
5. Merge: Maintainer merges after approval

For Maintainers

1. Review PRs: Use automated validation insights
2. Security Review: Check security scan results weekly
3. Dependencies: Review automated dependency update PRs
4. Releases: Tag releases when ready
5. Monitoring: Review workflow analytics monthly

🔧 Customization

Adding New Workflows

1. Create new .yml file in .github/workflows/
2. Follow existing patterns for structure
3. Add appropriate permissions and timeouts
4. Test thoroughly on feature branch

Modifying Existing Workflows

1. Test Changes: Always test on feature branch first
2. Documentation: Update this README if needed
3. Permissions: Review security implications
4. Notifications: Consider impact on team notifications

Environment-Specific Configuration

• Development: Use feature branch testing
• Staging: Main branch represents staging environment
• Production: Tags trigger production releases

📚 Additional Resources

• GitHub Actions Documentation
• UV Package Manager
• Ruff Linter Configuration
• PyPI Trusted Publishing
• Codecov Integration

🆘 Troubleshooting

Common Issues

Workflow fails on dependency installation

• Check UV cache configuration
• Verify pyproject.toml syntax
• Review dependency conflicts

Security scans reporting false positives

• Review .github/workflows/security.yml configuration
• Add exceptions to Bandit configuration in pyproject.toml
• Update security tool versions

Release workflow fails

• Verify version format (must be semantic versioning)
• Check PyPI trusted publishing configuration
• Review release permissions

Tests fail in CI but pass locally

• Check environment variable configuration
• Review OS-specific test conditions
• Verify test isolation

Getting Help

1. Check workflow logs: Detailed error information
2. Review this documentation: Common solutions
3. Search existing issues: Similar problems may be documented
4. Create new issue: Use issue templates for bug reports

This CI/CD pipeline is designed to be robust, secure, and maintainable. Regular reviews and updates ensure it continues to serve the project's needs effectively.