Learning & Documentation MCP Servers

AI Book Agent

Empowers AI assistants with intelligent access to ML textbook content for creating accurate, source-grounded documentation.

Youtube Transcripts

Retrieves YouTube video transcripts in various formats for Large Language Model (LLM) integration.

Java Documentation Publisher

Generate structured JSON documentation from Java source code or crawl existing HTML Javadoc for intelligent search capabilities.

AST2LLM for Go

Parses Go source code into an Abstract Syntax Tree (AST) and converts it into a clean, LLM-friendly format to enhance prompt context.

Arxiv Search

Enables LLMs to search and retrieve academic papers from arXiv, providing cleaned titles, abstracts, and content.

Context7

Provides up-to-date, version-specific documentation and code examples directly to AI language models.

Python Template

Provides a DevOps-friendly template for building MCP servers, integrating CI/CD, Docker, and Documentation-as-Code.

Grokipedia

Provides intelligent, unified access to Grokipedia's knowledge base for AI tools like Claude Desktop, VS Code, and Cursor.

Project Context

Provides persistent project context and planning state to AI coding assistants like Claude Code.

Kibela

Enables LLMs to interact with Kibela content by providing a Model Context Protocol (MCP) server.

SimDoc

Integrates scientific simulation documentation for tools like PyBaMM and Cantera with AI assistants via the Model Context Protocol.

Markdown RAG

Indexes and semantically searches Markdown documents using vector embeddings and a self-contained vector database.

Appcan Helper

Provides development assistance and comprehensive documentation access for AppCan applications.

Greeter

Generates short personalized greeting messages through a minimal Model Context Protocol (MCP) server.

Mcps Playground

Experiment with Anthropic's Claude and the Model Context Protocol (MCP) through an interactive web interface.

Context7

Provides an MCP server to access the Context7 API for comprehensive code documentation and development assistance.

Serve Learn

Facilitates multilingual translation and resource management via the Model Context Protocol (MCP).

Initial

Implements a basic Model Context Protocol (MCP) server in TypeScript, following official specifications and best practices.

AI

Registers a system information tool within an MCP service, enabling remote execution via `cline`.

Canvas LMS

Enables student access to Canvas LMS resources through an MCP server.