"AI Programming with Standards-Driven Development" matching MCP servers:

A server providing programming guidelines and coding standards for multiple languages, enabling access and search of best practices for C#, Go, JavaScript, Python, and TypeScript.

A Model Context Protocol (MCP) server that provides intelligent, context-aware access to development standards, enabling LLMs to automatically select and apply appropriate standards based on project requirements.

Transforms static coding standards into a queryable live data store for AI agents, delivering task-specific rules and fix guidance on demand. This optimizes context window usage through progressive disclosure, ensuring agents apply relevant governance without loading massive documentation.

MCP server for Next2D application development that generates code following MVVM + Clean Architecture + Atomic Design patterns, validates architecture, and provides API references.

Automatically enforces team coding standards in AI-assisted development by providing an MCP server that AI assistants can query for language-specific standards, style guides, and best practices.

Enables AI-assisted development of CodeQL queries for security analysis through the Model Context Protocol. Provides tools for compiling, testing, and executing CodeQL queries across multiple programming languages.

Provides comprehensive development tools for FastMCP projects including documentation access, NPM package version management, and TypeScript type definitions retrieval. Enables developers to fetch FastMCP documentation, analyze NPM packages, and access MCP architecture information through natural language.

Provides comprehensive code analysis (quality, complexity, linting, dependencies, security) and web scraping capabilities (static/dynamic content, API discovery) for development workflows.

Provides AI agents with professional coding standards, development best practices, and context-aware guidance through static documentation and AI-powered custom recommendations. Enables agents to access comprehensive development guidelines including coding rules, debugging techniques, and AI steering instructions.

A Cursor-compatible toolkit that provides intelligent coding assistance through custom AI tools for code architecture planning, screenshot analysis, code review, and file reading capabilities.

Provides a read-only interface to audit and continue coding agent sessions by extracting plans, intents, and edit authorship from history across multiple agents (Claude, Codex, OpenCode, Antigravity, Pi) via MCP, CLI, and Python SDK.

AI development assistant with 36 specialized tools for memory management, code analysis, project planning, and problem-solving through natural language interactions in Korean and English.

Spec-driven development tool for AI coding assistants that generates specs, validates code compliance, and provides actionable feedback.

Enables interactive GitHub pull-request review from Claude Code, with tools to fetch PRs, inspect files and repo structure, post review comments, and query a RAG index of the codebase.

A tool for vibecoding personnel and non-programmers to perform static code audit, query knowledge graph, and generate project documentation via MCP protocol.

Provides AI-powered development tools including code generation, refactoring, debugging, performance optimization, and test generation, along with smart prompts for code analysis and documentation, and a built-in knowledge base of coding best practices.

MCP server for Angular 19+ development, providing PR review, code scaffolding, modernization audits, and Storybook guidance.

🚀 Kill the Junior AI Era. 🤖 Level up your AI code to Principal standards. No more sloppy lines or junior mistakes. Automated ESLint ✨ TypeScript 🔧 Prettier 🎨 SonarQube 🛡️ Security 🔒 Complexity 📊 in seconds. High-stakes quality, forced to ship only the best. ⚡🏆 Goodbye, bad code. Hello, Principal Engineer. 🚀✨

Enables IDE integration with a multi-agent AI pipeline for solving, reviewing, and optimizing code through adversarial peer review and security filtering.

Offers a control surface for AI agent security with four independent checks: source-code scanning, tenant isolation, LLM content verification, and deploy gating. Currently in pre-release, with no functional scanning engines yet.