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qualityCreate sandboxed local development environments directly from Github and execute tests, see coverage and more! Supports Python, Node, Bun and many test runners.
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Why this server?
Supports Python, Node, Bun and many test runners which are helpful for development and debugging.
Why this server?
A TypeScript-based MCP server that facilitates SQL query execution and MySQL database connectivity which can be used to develop backend projects.
Why this server?
Provides an interactive Python REPL environment that maintains persistent session state, allowing users to execute Python code and access session history, useful for python backend development.
Why this server?
Enables AI models to perform file system operations (reading, creating, and listing files) on a local file system which are used in web frontend and python backend.
Why this server?
A Model Context Protocol server that enables AI assistants to perform GitHub operations including repository management, file operations, issue tracking, and pull request creation which helps in web and backend development.
Why this server?
Analyzes source code dependencies across multiple programming languages in the specified directory to identify file relationships, assisting in dependency management and project structure understanding.
Why this server?
A Model Context Protocol Server that enables LLMs to interact with and execute REST API calls through natural language prompts, supporting GET/PUT/POST/PATCH operations on configured APIs which would be helpful to connect web frontend and python backend.
Why this server?
Enables AI agents and assistants like Goose or Claude to interact with VS Code through the Model Context Protocol. This helps in code correction.
Why this server?
Added support for STDIO mode and SSE mode, multiple SQL execution, ability to query database table names and fields based on table comments, SQL Execution Plan Analysis which are useful in web frontend and python backend development.
Why this server?
A Model Context Protocol server that enables LLMs to interact with web pages, take screenshots, generate test code, scrape web pages, and execute JavaScript in a real browser environment for web frontend development.