"A guide to understanding AI agents" matching MCP servers:

Provides access to clean code guide documents and enables code quality inspection of external project files based on coding standards and best practices.

An MCP server that analyzes local or remote GitHub repositories, providing intelligent code context and structure to AI coding assistants.

MCP server that analyzes codebases with tree-sitter and generates AGENTS.md files for AI agents.

Enables orchestrating multiple AI CLI agents (Claude Code, Codex, Gemini CLI, Copilot CLI) through a unified MCP interface for task delegation, cross-agent comparison, and specialized tools like code review and debugging.

A validation layer for AI coding assistants that enforces explicit LLM evaluations on plans, code diffs, and tests to ensure safer and higher-quality code.

A runtime-free MCP server that converts source code into AST🌲, regardless of language.

Turns GitHub repository history into a cited maintainer skill for coding agents, providing tools to collect evidence, query the knowledge graph, and inspect bundles.

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.

Enables Claude to use Google Gemini as a secondary AI through MCP for large-scale codebase analysis and complex reasoning tasks. Supports both Gemini Flash and Pro models with specialized functions for general queries and comprehensive code analysis.

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.

Validates AGENTS.md files against the cross-vendor coding-agent spec, detecting security smells and consistency issues.

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

Turns a codebase into a persistent knowledge graph so AI coding agents can answer structural questions about functions, call chains, routes, and cross-service links through graph queries instead of reading files one by one.

MCP server for ai-scanner that enables AI agents to scan codebases for LLM usage, AI frameworks, and exposed secrets.

Provides AI coding agents with ground truth about a Rails app via 45 read-only tools covering schema, models, routes, controllers, views, jobs, and conventions, working over MCP or CLI and functioning even when the app cannot boot.

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

A local read-only AI workbench for navigating, auditing, and analyzing 1C:Enterprise 8.3 configurations via MCP-compatible clients.

Enables automated migration of Vue projects to React with intelligent analysis, task management, and learning from user modifications.

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.