Discover our curated collection of MCP servers for learning & documentation. Browse 1780servers and find the perfect MCPs for your needs.
Generates intelligent queries and provides documentation assistance by leveraging API documentation and Claude AI.
Demonstrates a basic JSON-RPC client and server implementation using Node.js.
Enables AI models to interact with SourceSync.ai's knowledge management platform through a standardized Model Context Protocol (MCP) server.
Programmatically interact with Anki decks for Japanese language learning through a Model Context Protocol (MCP) server.
Provides a basic MCP server implementation utilizing streamable HTTP for communication.
Manages and organizes conversational content on an MCP server using templated recording features.
Provides a robust backend for AI agents, delivering custom instruction files and executable scripts.
Offers a robust content management solution through a TypeScript-based server for Markdown processing, document generation, and intelligent note searching.
Provides production-ready WebAssembly plugin examples for the Noorle platform, showcasing HTTP APIs, WASI 2.0, and the Component Model across Rust, Go, Python, JavaScript, and TypeScript.
Leverage LightRAG and Tree-sitter to build a repository knowledge graph from code and documentation for Q&A and implementation planning.
Enables AI assistants to interact with Anki decks for enhanced studying, card creation, and progress analysis.
Interact with the arXiv API using natural language to retrieve, search, and manage scholarly articles.
Delivers access to the HUMMBL Base120 mental models framework through a Model Context Protocol server.
Access the Semantic Scholar Academic Graph API to search for academic papers, authors, and retrieve detailed research information.
Automatically generates and updates comprehensive documentation for your codebase using AI.
Integrates AI tools with Obsidian vaults, ensuring canonical context for accurate responses grounded in your established knowledge.
Access Purdue Brightspace courses and academic information using natural language with any Model Context Protocol (MCP) client.
Provides AI assistants with direct access to comprehensive Gemini API documentation.
Empower AI coding agents with a structured, versioned, and graph-based persistent memory system.
Automates multiphysics simulations via the MCP protocol, enabling AI agents to control COMSOL Multiphysics.
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