A Node.js server that integrates with pytest to facilitate the ModelContextProtocol (MCP) service tools, enabling test execution recording and environment tracking.
Enables AI assistants to run and analyze pytest tests for desktop applications through interactive commands. Supports test execution, filtering, result analysis, and debugging for comprehensive test automation workflows.
Facilitates unified execution and result parsing for various testing frameworks, including Bats, Pytest, Flutter, Jest, and Go, through a Model Context Protocol interface.
Enables AI coding agents to debug Python projects by running pytest, extracting failure locations, displaying code context around failures, and optionally requesting fix suggestions from Gemini.
Enables AI assistants to perform comprehensive code quality checks including pylint, pytest, and mypy analysis on Python projects, with smart prompts for explaining issues and suggesting fixes.
An MCP server that executes tox commands to run Python tests within a project using pytest, allowing users to run all tests or specific test groups, files, cases, or directories.