Shippie is an extensible code review and QA agent that uses Large Language Models to review code in your CI/CD pipeline, detecting common issues like exposed secrets, inefficient code, and potential bugs.
One-Minute Overview#
Shippie is an AI-powered code review tool that integrates into CI/CD pipelines to help teams deliver high-quality code faster. It's designed for developers and automatically detects common code issues while supporting local command-line use.
Core Value: Automates code review through AI, reducing manual review time and improving code quality and development efficiency.
Quick Start#
Installation Difficulty: Medium - Requires cloning repository, installing dependencies, and configuring API key
# Clone the repository
git clone https://github.com/mattzcarey/shippie.git
cd shippie
# Install dependencies (using bun recommended, npm or pnpm also work)
bun install
# Set up API key
cp .env.example .env
# Edit .env file, replace YOUR_API_KEY with your actual OpenAI API key
Is this suitable for me?
- ✅ CI/CD Integration: Teams needing automated code review workflows
- ✅ Local Code Checking: Developers who want to quickly review code before committing
- ❌ Pure Static Code Analysis: Scenarios that don't rely on AI
- ❌ Offline Environments: Requires internet connection for AI services
Core Capabilities#
1. AI Code Review - Detecting Code Issues#
Shippie uses Large Language Models to analyze code and automatically identifies security vulnerabilities, performance issues, and potential bugs. Actual Value: Reduces code review time and catches potential issues early, improving software quality
2. CI/CD Integration - Automated Workflow#
Vertically integrated into CI/CD pipelines, automatically executing code reviews before code merges. Actual Value: Prevents problematic code from entering the main branch, reducing later fix costs
3. Local Command-line Tool - Developer Friendly#
Can run locally from the command line to review staged files. Actual Value: Catch issues before committing, reducing unnecessary commits and CI test failures
4. Rules File Configuration - Custom Review Rules#
Supports custom review rules through configuration files to maximize tool effectiveness. Actual Value: Customize review standards according to specific project needs, ensuring compliance with team standards
5. Model Context Protocol (MCP) - Tool Extension#
Functions as an MCP client for integration with external tools like browser use, infrastructure deployments, etc. Actual Value: Extends review capabilities beyond code to impact related systems
Tech Stack & Integration#
Development Language: TypeScript Main Dependencies: Bun runtime (recommended), Node.js (via npm), OpenAI API Integration Method: Command-line tool / GitHub Action / MCP client
Maintenance Status#
- Development Activity: Actively maintained, indicated by contributors and Pulse badges
- Recent Updates: Uses release-please for automated version releases
- Community Response: Project has a discussion area for user exchange of ideas and feedback
Documentation & Learning Resources#
- Documentation Quality: Basic - Covers setup, configuration, and development guidelines
- Official Documentation: Repository contains setup instructions, rules files, AI provider configuration, etc.
- Example Code: Demo video provided showing tool usage