Built SwiPR – swipe-to-review GitHub PRs with AI context (github.com)

SwiPR, a new tool developed as a Claude MCP plugin, revolutionizes the GitHub pull request (PR) review process by enabling a swipe-to-review interface enriched with AI context. As the number of open PRs surges from an average of 20-40 to 130-200, the challenge has shifted from PR creation to efficient reviewing. By providing essential context such as risk scores, AI-generated summaries, and contributor histories directly in a user-friendly format, SwiPR enhances the decision-making process for maintainers and AI agents alike, allowing quick approvals or requests for changes. This tool is significant for the AI/ML community as it integrates machine learning in assessing PR risks, leveraging embeddings to analyze and categorize PR data. The swipe interface allows users to quickly navigate through PRs while the underlying MCP server allows for querying detailed insights. Key technical features include a risk scoring system based on file changes and contributor histories, chat functionality for real-time inquiries, and caching capabilities to optimize performance by reducing repeated API calls. SwiPR's architecture utilizes the Next.js framework, PostgreSQL for storage, and Vercel's AI Gateway for analysis, making it a lightweight yet powerful solution tailored for modern software development workflows.