How does Basin integrate with AI code editors?

Basin integrates via the Model Context Protocol (MCP), allowing it to automatically test code after generation. It also supports parameter-based testing using prompt, server URL, and endpoint details.

What parameters does Basin use for testing?

Basin accepts parameters such as the original user prompt, server URL, endpoint details, thread ID, credentials (optional), features, and UI elements for comprehensive testing.

How can I improve the reliability of Basin's tests?

Keep code changes small and isolated. Explicitly declare any authentication requirements in your prompt, providing either credentials or instructions for creating a new user.

What are some best practices when using Basin?

Isolate changes, declare auth requirements explicitly, and keep code changes small to optimize testing.

Basin

Name: Basin
Author: basin-ai

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Ensures code quality and reliability in AI code editors by testing for bugs, hallucinations, and unintended changes after code generation.

Basin is a Model Context Protocol (MCP) tool designed to integrate with AI code editors like Cursor and Windsurf, providing automated code quality and reliability testing. By invoking the 'check-generated-code' tool after each code generation step, Basin helps developers identify bugs, hallucinations, and unintended changes. The tool accepts parameters like user prompts, server URLs, endpoint information, and thread IDs to facilitate comprehensive testing and conversation tracking. It encourages small, isolated code changes and explicit declaration of authentication requirements for optimal performance and accuracy.

主要功能

01Automated code quality testing for AI code editors

02Detects bugs, hallucinations, and unintended changes

03Integrates via Model Context Protocol (MCP)

04Supports parameter-based testing with prompt, server URL, and endpoint details

05Provides guidelines for best practices to improve test reliability

060 GitHub stars

使用案例

01Validating the correctness of new or modified API endpoints

02Identifying regressions and unintended side effects of code changes

03Ensuring code quality after AI-assisted code generation