learning & documentation를 위한 엄선된 MCP 서버 컬렉션을 찾아보세요. 1780개의 서버를 탐색하고 필요에 맞는 완벽한 MCP를 찾아보세요.
Connects Claude Desktop to Anki to analyze and manage learning using leech-tagged cards.
Manages document ingestion, chunking, semantic search, and note management.
Provides a foundational example for integrating custom tools with the Gemini CLI using the Model Context Protocol (MCP).
Automates the generation of Anki flashcards from Notion pages, converting toggle blocks into structured cards using AI and real-time import via AnkiConnect.
Provides advanced vector store operations, document search, and information retrieval through a Model Context Protocol (MCP) interface.
Manages a simple notes system through a Model Context Protocol server, providing resources, tools, and prompts for note interaction.
Provides PyTorch AI/ML examples for Modal Context Protocol (MCP), Agent-to-Agent (A2A), RAG, and vLLM workflows, enabling reproducible and scalable pipelines for research and deployment.
Connects AI agents to remote Git repositories to fetch and search markdown documentation and notes.
Experiments with MCP server technology to explore its capabilities and behaviors.
Enhances digital reading with AI insights, transforming books into interactive learning experiences for students, researchers, and avid readers.
Serves and queries documentation with advanced AI capabilities, providing a robust platform for knowledge management.
Provides semantic search and Retrieval-Augmented Generation (RAG) capabilities for markdown documentation.
Track real-time AI/LLM research advancements across multiple academic and development platforms.
Provides intelligent, unified access to Grokipedia's knowledge base for AI tools like Claude Desktop, VS Code, and Cursor.
Provides a simple example for building an MCP server using FastMCP and Python, designed for use with Smithery.
Streamlines LaTeX manuscript compilation with robust command-line interface and MCP server capabilities.
Automates the generation, conduction, and evaluation of exams through an AI-powered assessment platform leveraging RAG and multi-LLM validation.
Discover, share, and evaluate Google Apps Script (GAS) libraries to efficiently find and integrate resources into projects.
Exposes local Markdown documentation libraries directly to AI assistants via the Model Context Protocol.
Integrates LimeLink dynamic link management with AI assistants via the Model Context Protocol, enabling link creation, lookup, and management.
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