This document outlines the community support structure, resources, and guidelines for the Dataproc MCP Server project.
Before seeking help, please check our comprehensive documentation:
- Quick Start Guide - Get started in 5 minutes
- API Reference - Complete tool documentation
- Configuration Examples - Real-world configurations
- Testing Guide - Testing and debugging information
Check if your question has already been answered:
- GitHub Issues - Bug reports and feature requests
- GitHub Issues - Community Q&A and support
- Q&A: General questions and help requests (use question label)
- Ideas: Feature suggestions and brainstorming (use enhancement label)
- Show and Tell: Share your projects and use cases (use discussion label)
- General: Community announcements and discussions
- Bug Reports: Use the bug report template
- Feature Requests: Use the feature request template
- Security Issues: Use private security reporting
Issues are automatically labeled based on:
- Type:
bug,enhancement,documentation,question - Priority:
critical,high,medium,low - Status:
needs-triage,in-progress,waiting-for-response - Component:
authentication,profiles,security,performance
-
Initial Triage (within 24 hours)
- Label assignment
- Priority assessment
- Assignment to maintainers
-
Investigation (within 48 hours)
- Reproduce issues
- Gather additional information
- Provide initial response
-
Resolution (timeline varies)
- Bug fixes: 1-2 weeks for critical, 2-4 weeks for others
- Features: 4-8 weeks depending on complexity
- Documentation: 1 week
- Critical Issues: 4 hours
- High Priority: 24 hours
- Medium Priority: 48 hours
- Low Priority: 1 week
**Problem**: Clear description of what you're trying to achieve
**Environment**: OS, Node.js version, package version
**Configuration**: Relevant config (sanitized)
**Error**: Exact error message or unexpected behavior
**Attempted Solutions**: What you've already tried
- Vague descriptions: "It doesn't work"
- Missing context: No environment information
- Duplicate questions: Not searching existing issues
- Demanding responses: "URGENT!!!" or "FIX NOW"
All community interactions must follow our Code of Conduct.
We recognize outstanding contributors through:
- GitHub Achievements: Contributor badges and recognition
- Release Notes: Contributor acknowledgments
- Community Spotlights: Featured contributions
- Maintainer Nominations: Path to maintainer status
We value all types of contributions:
- Code: Bug fixes, features, performance improvements
- Documentation: Guides, examples, API docs
- Testing: Bug reports, test cases, QA
- Community: Answering questions, mentoring
- Design: UI/UX improvements, graphics
- Advocacy: Blog posts, talks, tutorials
- First-time contributors
- Occasional contributions
- Community participation
- Multiple contributions
- Consistent quality
- Community engagement
- Significant contributions
- Domain expertise
- Mentoring others
- Project leadership
- Code review responsibilities
- Community management
- When: First Wednesday of each month, 2 PM UTC
- Format: Video call (Google Meet/Zoom)
- Agenda:
- Project updates
- Community Q&A
- Feature discussions
- Contributor spotlights
- When: End of each quarter
- Format: GitHub Discussion + optional video call
- Purpose: Review progress, plan next quarter
- Frequency: Bi-annual
- Duration: 48 hours
- Focus: New features, integrations, examples
- Frequency: Monthly
- Topics:
- Getting started with MCP
- Advanced Dataproc configurations
- Security best practices
- Performance optimization
- Target Conferences:
- Google Cloud Next
- KubeCon
- Data Engineering conferences
- Open source events
- Issue Triage: Auto-labeling based on content
- Stale Issue Management: Close inactive issues after 60 days
- Welcome Bot: Greet new contributors
- Release Notes: Auto-generate from PRs
We track:
- Response Times: Average time to first response
- Resolution Times: Time from issue to closure
- Contributor Growth: New contributors per month
- Community Health: Issue/PR ratios, activity levels
- Average Response Time: 6 hours
- Issue Resolution Rate: 95%
- Community Satisfaction: 4.8/5
- Documentation Coverage: 90%
| Priority | First Response | Resolution Target |
|---|---|---|
| Critical | 4 hours | 24 hours |
| High | 24 hours | 1 week |
| Medium | 48 hours | 2 weeks |
| Low | 1 week | 4 weeks |
- Bug Fix Quality: 99% success rate
- Documentation Accuracy: 95% user satisfaction
- Test Coverage: 90% minimum
- Security Response: 2 hours for critical vulnerabilities
- Private Reporting: Use GitHub's private vulnerability reporting
- Email: security@dataproc-mcp.dev (if available)
- Response Time: 2 hours acknowledgment, 24 hours initial assessment
- Assessment: Evaluate severity and impact
- Fix Development: Create patch in private
- Coordination: Work with reporters and users
- Disclosure: Public advisory after fix release
- Welcome Package: Quick start guide, examples, community links
- Mentorship Program: Pair new users with experienced community members
- Office Hours: Weekly sessions for live help
- Good First Issues: Labeled issues for newcomers
- Contribution Guide: Step-by-step process
- Code Review: Constructive feedback and mentoring
- User Stories: Feature community use cases
- Success Stories: Highlight community achievements
- Feedback Loops: Regular surveys and feedback collection
- Primary Maintainer: @dipseth
- Community Manager: TBD
- Security Contact: security@dataproc-mcp.dev
- GitHub: dipseth/dataproc-mcp
- Issues: GitHub Issues
- NPM: @dataproc/mcp-server
- Twitter: @dataproc_mcp (planned)
- LinkedIn: Dataproc MCP Server (planned)
- Blog: Medium/Dev.to (planned)
Together, we're building the best Dataproc MCP experience for everyone! 🚀