SwiPR

SwiPR: Enhance Your GitHub PR Review Process with AI-Driven Insights

SwiPR introduces a seamless way to review GitHub pull requests (PRs) by integrating AI context into the decision-making process. Designed to function as a Claude MCP plugin, SwiPR allows users to swipe through PRs, gaining access to crucial insights that streamline review efficiency.

Live Demo and Integration

Experience the powerful capabilities of SwiPR in action with the live demo: Try the live demo →
For users of Claude Desktop, SwiPR can be easily integrated to facilitate direct PR reviews from the chat interface. Detailed guidelines are provided for integration.

The Motivation Behind SwiPR

As organizations face an influx of PRs, the challenge has shifted from creation to effective review. Chief Executive Zeno Rocha notes how the number of open PRs has dramatically increased, necessitating a solution to manage this workload efficiently. SwiPR steps in as a contextual tool to assist maintainers and AI agents in determining the safety of merging PRs by offering essential insights such as risk levels, contributor history, and testing coverage.

Core Functionality

SwiPR’s functionality is centered around a user-friendly swipe interface:

1. Fetch and Store: Provide any public GitHub repository, and SwiPR will retrieve open PRs, organizing them with embeddings for enhanced accessibility.
2. Swipe Navigation: Users can easily swipe right to approve, left to request changes, or down to skip using keyboard shortcuts (J, F, or Space).
3. Contextual Insights: A dedicated right panel reveals critical information including risk scores, AI-generated summaries, similar past PRs, and contributor history.
4. Request In-Depth Context: Engage with options like "Why is this risky?", "Show me callers", or "What tests cover this?" to dive deeper.
5. Interactive Q&A: Users can ask questions of the AI, which retains context from the full diff and codebase.

MCP Server for Enhanced Accessibility

SwiPR also operates as an MCP server, maintaining the same contextual insights within the chat environment, eliminating the need for a browser. Users can easily query information like risk assessments or find tests that cover specific changes.

Risk Scoring Customization

SwiPR allows teams to define their risk scoring criteria directly within the TypeScript code in lib/scoring.ts. Users can modify rules to tailor the risk assessment to their project needs, ensuring the scoring aligns with standards and practices.

Integration with AI Providers

The chat feature is compatible with various providers, enabling users to bring in their AI keys easily. This ensures flexibility and aligns with user preferences for AI interactions.

Technology Stack

SwiPR is built using a modern tech stack that includes Next.js, Tailwind CSS, and Neon Postgres, ensuring a robust and scalable application.

Contributing to SwiPR

Contributions are welcomed, with a focus on enhancing the risk scoring heuristics and working within the established architecture. A commitment to maintaining a read-only access policy for PR interactions ensures a streamlined approach to PR management without the complexity of adding features like GitHub OAuth.

**SwiPR stands as a transformative tool for developers seeking to simplify and enrich their pull request review workflows, leveraging AI for deeper insights and efficient management.