learning & documentation向けの厳選されたMCPサーバーコレクションをご覧ください。1223個のサーバーを閲覧し、ニーズに最適なMCPを見つけましょう。
Enables checking Mathematica code via a local Mathematica installation.
Provides an integrated server and UI panel within VS Code/Cursor for retrieving and displaying command-line tool documentation.
Manages and stores code snippets across different programming languages using a standardized server interface.
Enables Claude Desktop to interact with Hacker News using the Model Context Protocol (MCP).
Recursively fetches and extracts content from web pages for LLM consumption.
Provides a deliberately vulnerable Model Context Protocol (MCP) server for security research and AI/ML security learning.
Provides programmatic access to UV package manager documentation through a Model Context Protocol (MCP) server.
Integrates Appwrite documentation into IDEs and AI agents, enabling seamless browsing and context-aware assistance.
Provides LLMs with comprehensive, searchable context on the Model Context Protocol (MCP) specification.
Converts Compiled HTML Help (CHM) files to Markdown format for easier accessibility and version control.
Enables language models to programmatically access and manipulate Readwise documents and highlights.
Transforms Bilibili video content into structured notes, provides intelligent Q&A, and transcribes audio.
Enables LLM interaction with EPUB and PDF documents via the Model Context Protocol (MCP).
Enables LLMs to interact with Kibela content by providing an MCP server implementation for the Kibela API.
Provides up-to-date documentation for npm packages directly in your IDE by fetching the latest README from either GitHub or the bundled package.
Browse and interact with an entire Notion workspace as a Model Context Protocol server, eliminating the need for individual database tokens.
Integrates Mercado Pago functionalities and provides access to its developer documentation via a Model Context Protocol server.
Exposes a comprehensive suite of Nix/NixOS tooling functionalities via the Model Context Protocol (MCP).
Indexes technical documentation on a local vector database and integrates with AI IDEs for semantic search.
Caches a codebase as a graph to provide LLMs with efficient code memory.
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