"Resources for Learning Law" matching MCP servers:

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.

Integrates Google's Gemini AI models into Claude Code and other MCP clients to provide second opinions, code comparisons, and token counting. It supports streaming responses and multi-turn conversations directly within your existing AI development workflow.

Scans source code for possible Korean compliance risks (PIPA, Network Act, Credit Information Act, E-Commerce Act) and maps findings to specific legal provisions. Runs locally, exposes MCP tools for scanning and law lookup, and does not constitute legal advice. That's hedged (matches the project's "possible risk / not legal advice" rule), keyword-rich for search, and names all four laws.

An MCP server for interacting with the Rell Language Server Protocol interface. It enables LLMs to query LSP Hover and Completion providers for Rell projects.

An MCP toolkit for algorithm learning that enables AI agents to search problems, generate step-by-step hints, analyze code, and create review templates for Baekjoon and Programmers problems.

Analyzes codebases to suggest relevant learning projects and generate interactive slides with direct links to the Marble platform. It enables developers to create tailored learning experiences based on their specific technologies, patterns, and code context.

A comprehensive MCP server providing arithmetic tools, dynamic file resources for frontend/backend documentation, reusable prompt templates for code review/debugging/testing, and complete development workflow management from requirements to deployment.

Enables automated migration of JavaScript/TypeScript packages from legacy test runners like Karma, Webpack, and Mocha to Vitest, including AST codemods, multi-project test scaffolding, and self-learning diagnostics for resolving runtime errors.

Enhances Claude AI with persistent memory storage for Infrastructure-as-Code components, supporting version tracking and relationship mapping for Terraform and Ansible resources.

Enables LLM-powered agents to generate, execute, and analyze Alloy modeling language code for software modeling and formal verification. Provides tools to run Alloy models, access documentation and examples, and generate models from system descriptions.

A Model Context Protocol server that helps programmers understand code by providing explanations, tech stack analysis, and best practice suggestions through prompt templates.

Enables AI agents to assess AI-readiness and improve AI leverage through analysis tools, resources, and prompts for project scanning and remediation.

Enables agents to connect to Language Server Protocol servers as a headless editor, exposing LSP capabilities like diagnostics, rename, and formatting through MCP tools and resources.

Provides ChatGPT read-only access to inspect repositories, code, merge requests, pipelines, and CI logs on self-managed GitLab instances, including those reachable only from a private network or VPN.

A local project intelligence, batch coding, and self-learning engine for Codex that enables task-level batch coding, reduces token usage, and automatically learns skills.

Provides AI agents with ground-truth knowledge of Strapi projects by reading real schema files, enabling accurate queries and safe refactoring operations.

A server component of the Model Context Protocol that provides intelligent analysis of codebases using vector search and machine learning to understand code patterns, architectural decisions, and documentation.

Enables LLM clients like Claude to interact with IDA Pro for binary analysis, decompilation, cross-references, patching, and more via 41 MCP tools, 8 resources, and 7 guided prompts.

Enables interaction with Binary Ninja for binary analysis and reverse engineering, providing tools and resources to examine binaries, decompile functions, and manage symbols through natural language.

An MCP server that scans web projects for Russian Federal Law 152-FZ compliance, identifying risks like missing consent checkboxes, cookie banners without opt-out, and unauthorized trackers, with legal references and fix suggestions.