"Learning to Create an Expert Python Program to Exit GitHub" matching MCP servers:

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.

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

An accessibility expert MCP server that provides AI coding assistants with real-time access to WAI-ARIA patterns, code review, contrast checking, and WCAG guidance for writing accessible code from the start.

MCP server that enables AI agents to read, edit, and create PLC projects in EcoStruxure Control Expert via COM automation.

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.

MCP server that studies a folder of code repositories, generates markdown documentation (architecture, interfaces, activity), and serves answers over MCP with live ripgrep search and file reads so AI assistants can query codebases and their relationships.

Indexes commit history to create a queryable expert, providing insights into code evolution, developer intent, and hidden patterns beyond static code analysis.

Analyzes codebases from local directories, GitHub, and Azure DevOps, providing intelligent context to AI coding assistants through repository structure, critical files, and semantic maps.

Automates project scaffolding for Domain-Driven Design and Clean Architecture, providing professional naming, structure verification, and bilingual documentation generation.

Validates AI-generated Python: syntax, lint, security scan and deterministic repair.

Provides educational tools for developers to learn programming concepts, review code, get best practices, compare approaches, generate learning paths, debug, explain code, and quiz themselves.

MCP server exposing GitHub tools for issues, pull requests, and code browsing via the GitHub REST API. Designed for local LLM clients with flat arguments and streamable HTTP support.

This MCP server provides direct access to ruff linting, formatting checks, and ty type-checking for Python projects, with token-efficient, structured output.

Analyzes Python code and provides guided refactoring suggestions without automatically modifying code.

Exposes the 23 Gang of Four design patterns to AI coding agents for generation, canonical examples, AST-based detection, validation, and anti-pattern refactoring in Python codebases.

Enables self-hosted, read-only remote interaction with GitHub repositories, allowing listing repositories, searching code, and inspecting commits, pull requests, issues, and diffs via authenticated MCP clients.

Enables deterministic static analysis of Python code, providing tools to inspect classes, functions, imports, dependencies, and more, without executing the code.

Enables agents to review Python dependency requirements and source code against a modernization catalog, returning structured guidance, import-level suggestions, and compatibility floors. It also lists available codemod recipes and previews their transformations as unified diffs, all read-only and without installing packages or executing supplied code.

Enables AI agents to search repositories, inspect files and code, list issues and commits, check releases, and look up GitHub user profiles through the GitHub public REST API without authentication.