What is Code Feedback?

Code Feedback is an open-source Model Context Protocol (MCP) server providing automated, multi-language code feedback, validation, and project analysis via a secure API for developers and LLM workflows.

Can Code Feedback be integrated with AI or LLMs?

Yes, it's specifically designed with an LLM-friendly API, offering advanced prompts for AI-powered code review, analysis, and suggestions, returning machine-readable JSON responses.

Which programming languages and build systems does it support?

It offers multi-language validation for TypeScript, JavaScript, Python, and Go. It also integrates with project-level build/test systems like npm and Make.

How does Code Feedback enhance code quality and developer workflows?

It catches errors early, standardizes quality across polyglot projects, reduces manual review time, and empowers LLMs/tools to safely validate, lint, build, and analyze code.

Code Feedback

Name: Code Feedback
Author: niradler

byniradler

0•

Seguridad y Pruebas

Herramientas para Desarrolladores

Despliegue y DevOps

Provides automated, multi-language code feedback, validation, and project analysis through a secure API.

Code Feedback is an open-source Model Context Protocol (MCP) server designed to streamline code quality, correctness, and maintainability across diverse programming languages and build systems. It offers a secure, extensible, and LLM-friendly API for validating, linting, building, and analyzing code, essential for modern polyglot codebases. By catching errors early and standardizing quality, it reduces manual review time and empowers developers and AI-powered workflows.

Características Principales

01Multi-language file validation (TypeScript, JavaScript, Python, Go)

02Project-level build/test integration (npm, Make)

03Secure, path-restricted file and command access

04Structured, machine-readable JSON responses

05Advanced prompt system for code review, analysis, and suggestions

060 GitHub stars

Casos de Uso

01Automating code quality checks in multi-language projects

02Standardizing code review and analysis across development teams

03Catching errors early after generating or editing code, especially LLM-generated code