awesome-repositories.com
Blog
MCP
awesome-repositories.com

Discover the best open-source repositories with AI-powered search.

ExploreCurated searchesOpen-source alternativesSelf-hosted softwareBlogSitemap
ProjectMCP serverAboutHow we rankPress
LegalPrivacyTerms
© 2026 Bringes Technology SRL·VAT RO45896025·hello@awesome-repositories.com
microsoft avatar

microsoft/vscode-recipes

0
View on GitHub↗

Vscode Recipes

vscode-recipes is a collection of configuration patterns and guides for setting up debuggers and runtime environments within VS Code. It provides standardized templates and blueprints to connect the editor to local, containerized, or serverless runtimes across a variety of programming languages and frameworks.

The project focuses on coordinating simultaneous debugging sessions across client-side and server-side processes to trace logic through full-stack applications. It offers specific patterns for integrating language runtimes and orchestrating multi-language development setups within a single editor instance.

The recipes cover the configuration of automated test debugging for unit, integration, and end-to-end suites. It also includes setups for debugging serverless functions and managing development workflows for various languages and tools.

AI search

Explore more awesome repositories

Describe what you need in plain English — the AI ranks thousands of curated open-source projects by relevance.

Start searching with AI

Features

  • Configuration Recipes - Ships a collection of configuration patterns for setting up debuggers and runtime environments across multiple frameworks.
  • Debugger Configuration Templates - Provides a collection of setup instructions and launch configurations for integrating VS Code with various runtimes.
  • Awesome List - A community-curated directory that catalogs and links out to other open-source projects, rather than a standalone tool you run yourself.
  • Debug Configurations - Provides systems for creating and managing parameters that control how an application is launched and inspected during debugging.
  • Configuration Guides - Offers detailed JSON launch settings and integration guides for connecting an editor to various development stacks.
  • Configuration Templates - Provides standardized configuration templates to connect a code editor to local, containerized, or serverless runtimes.
  • Runtime Integration Blueprints - Provides standardized patterns for connecting a code editor to local, containerized, or serverless runtimes.
  • VS Code Configuration Patterns - Provides a comprehensive collection of setup instructions and launch configurations specifically for VS Code.
  • VS Code Extensions - Provides specialized configuration patterns and integration settings for the VS Code editor ecosystem.
  • Compound Launch Configurations - Provides configurations that trigger the simultaneous start of multiple debugging sessions as a single action.
  • Editor Integrations - Provides templates to connect editor interfaces to language runtimes through specialized extensions and communication protocols.
  • Full-Stack Debugging Workflows - Offers a systematic way to coordinate simultaneous debugging sessions across frontend and backend layers.
  • Full-Stack Debugging Workflows - Enables intercepting execution in both front-end and back-end code within a single integrated session.
  • Application Debugging - Enables connecting a debugger to a process with automatic reconnection after application restarts.
  • Debugger Protocol Integrations - Implements integrations that allow an editor to control external debuggers via standardized protocols.
  • Debugger Source Mapping - Maps compiled or transpiled code back to original source files to enable accurate breakpoint placement and state inspection.
  • Debug Server Orchestration - Orchestrates the lifecycle of Node.js debug servers to allow automatic re-attachment on code changes.
  • Serverless Function Development Tools - Includes utilities to stream cloud requests locally for breakpoints and state inspection in serverless functions.
  • Editor-to-Runtime Bridges - Uses language-specific plugins to translate editor debugging commands into instructions the target language runtime understands.
  • Editor-to-Runtime Integrations - Relies on language-specific plugins to bridge the editor's debugging interface with the target language's runtime environment.
  • Serverless Worker Debugging - Provides configurations to stream cloud-based serverless requests to a local editor for debugging.
  • Debugger Launch Configurations - Defines debugger behavior and runtime environment settings through structured configuration files read by the editor.
  • Debugger Lifecycle Management - Configures Node.js environments to automatically reconnect the debugger after application restarts.
  • Ruby Environments - Provides configurations for executing a server with a debugger to inspect code state in Ruby environments.
  • Multi-Language Environment Templates - Includes templates for managing simultaneous debugging and test execution for full-stack applications using multiple languages.
  • Workspace-Based Resolution - Determines the appropriate launch settings and environment variables based on the active file or workspace folder structure.
  • Source-to-Source Translation - Translates compiled or transpiled code back to original source files to ensure breakpoints align with original authorship.
  • Test-Level Debugging - Allows launching debug sessions for specific unit tests to isolate bugs within a suite.
  • End-to-End Testing - Provides configurations to attach debuggers to automated suites that simulate complete user workflows across the application stack.
  • Test Debugging Templates - Offers configuration templates for attaching debuggers to unit, integration, and end-to-end test suites.
  • Test Suite Debugging - Provides templates for executing unit, integration, and end-to-end test suites with a debugger.
  • Debugger Configuration Mappings - Provides mappings that translate user-defined debugger settings into protocol-compliant requests.
  • Web Application Debugging - Provides tools and integrated interfaces for inspecting and troubleshooting web applications during execution.
  • Learning & Reference - Debugging recipes for using Vue with VS Code.
  • Learning Resources - Configuration examples for debugging applications in the editor.
5,959 stars·598 forks·JavaScript·MIT·25 views

Star history

Star history chart for microsoft/vscode-recipesStar history chart for microsoft/vscode-recipes

How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.

Frequently asked questions

What does microsoft/vscode-recipes do?

vscode-recipes is a collection of configuration patterns and guides for setting up debuggers and runtime environments within VS Code. It provides standardized templates and blueprints to connect the editor to local, containerized, or serverless runtimes across a variety of programming languages and frameworks.

What are the main features of microsoft/vscode-recipes?

The main features of microsoft/vscode-recipes are: Configuration Recipes, Debugger Configuration Templates, Awesome List, Debug Configurations, Configuration Guides, Configuration Templates, Runtime Integration Blueprints, VS Code Configuration Patterns.

Which projects share features with microsoft/vscode-recipes?

Projects with overlapping indexed features include: zuzoovn/machine-learning-for-software-engineers — A complete daily plan for studying to become a machine learning engineer. ujjwalkarn/machine-learning-tutorials — This repository serves as a structured educational resource for machine learning and data science, providing a… josephmisiti/awesome-machine-learning — This project is a comprehensive, community-driven directory of machine learning resources, software libraries, and… sindresorhus/awesome — This project is a community-maintained directory that serves as a comprehensive index of software tools, frameworks,… ashishpatel26/500-ai-machine-learning-deep-learning-computer-vision-nlp-projects-with-code — This repository serves as a comprehensive, curated collection of open-source implementations focused on artificial… mfussenegger/nvim-dap — nvim-dap is a Neovim plugin that serves as a client implementation of the Debug Adapter Protocol. It provides a…

Projects sharing features with Vscode Recipes

These projects share indexed features with Vscode Recipes. Shared tags can include platform or build tooling; verify the primary use case before treating a result as a replacement.
  • josephmisiti/awesome-machine-learningjosephmisiti avatar

    josephmisiti/awesome-machine-learning

    72,867View on GitHub↗

    This project is a comprehensive, community-driven directory of machine learning resources, software libraries, and educational materials. It serves as a centralized knowledge base for developers and researchers, organizing tools and frameworks by their primary programming language and technical domain to simplify discovery across the artificial intelligence ecosystem. The collection distinguishes itself by providing a cross-language development index that spans diverse programming environments, including C, C++, Rust, Clojure, and Python. It covers a wide range of specialized capabilities, fr

    Python
    View on GitHub↗72,867
  • sindresorhus/awesomesindresorhus avatar

    sindresorhus/awesome

    476,211View on GitHub↗

    This project is a community-maintained directory that serves as a comprehensive index of software tools, frameworks, and educational materials. It functions as an open-source knowledge base, organizing diverse engineering domains and technical resources into a structured taxonomy to assist developers in discovering high-quality content. The directory distinguishes itself through a decentralized peer-review model, where independent contributors curate, verify, and update entries to ensure accuracy and relevance. All information is stored in a version-controlled, flat-file markdown format, whic

    awesomeawesome-listlists
    View on GitHub↗476,211
  • ashishpatel26/500-ai-machine-learning-deep-learning-computer-vision-nlp-projects-with-codeashishpatel26 avatar

    ashishpatel26/500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-code

    34,579View on GitHub↗

    This repository serves as a comprehensive, curated collection of open-source implementations focused on artificial intelligence, machine learning, and computer vision. It functions as a centralized knowledge base and technical resource index, providing students and professional engineers with a structured directory of code examples for educational and practical reference. The project distinguishes itself through a community-driven curation model, relying on manual updates and contributions to maintain a relevant and expansive archive. By organizing these resources into categorized lists, the

    artificial-intelligenceartificial-intelligence-projectsawesome
    View on GitHub↗34,579
  • ujjwalkarn/machine-learning-tutorialsujjwalkarn avatar

    ujjwalkarn/Machine-Learning-Tutorials

    17,909View on GitHub↗

    This repository serves as a structured educational resource for machine learning and data science, providing a centralized collection of tutorials, lecture notes, and implementation guides. It is designed to support self-directed learning by organizing complex technical concepts into a clear, hierarchical path that spans from foundational statistical methods to advanced deep learning architectures. The project distinguishes itself through a comprehensive approach to skill development, bridging the gap between theoretical algorithmic foundations and functional software applications. It offers

    awesomeawesome-listdeep-learning
    View on GitHub↗17,909
Compare all 30 related projects→