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。2179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。
Retrieves information from the AWS Knowledge Base using the Bedrock Agent Runtime, enabling Retrieval-Augmented Generation (RAG).
Provides a foundational example for integrating custom tools with the Gemini CLI using the Model Context Protocol (MCP).
Demonstrates basic usages of the Model Context Protocol with a Python server and client.
Provides an intelligent search and retrieval system for Pybricks documentation and code examples.
Provides comprehensive access to Rust crate documentation and metadata from crates.io and docs.rs.
Connects AI agents to remote Git repositories to fetch and search markdown documentation and notes.
Provides semantic search and Retrieval-Augmented Generation (RAG) capabilities for markdown documentation.
Provides AI assistants with intelligent, comprehensive access to the MAGMA computational algebra system handbook through advanced vector search and semantic understanding.
Provides a simple example for building an MCP server using FastMCP and Python, designed for use with Smithery.
Serves Python coding best practices and guidelines via a Model Context Protocol (MCP) server for general development and FastAPI APIs.
Offers extensive tools, resources, and prompts by integrating Google Custom Search and Wikipedia functionality for advanced research and information retrieval.
Streamlines LaTeX manuscript compilation with robust command-line interface and MCP server capabilities.
Enhances AI coding tools with versioned PostgreSQL knowledge and best practices for improved code generation.
Automates the generation, conduction, and evaluation of exams through an AI-powered assessment platform leveraging RAG and multi-LLM validation.
Enables AI assistants to access a database of human-curated content recommendations.
Fetches real-time weather information for any location worldwide using the wttr.in API and integrates with MCP clients like Claude.
Integrates LimeLink dynamic link management with AI assistants via the Model Context Protocol, enabling link creation, lookup, and management.
Provides Retrieval Augmented Generation (RAG) capabilities for your markdown documentation.
Provides a server with universal, language-agnostic development rules for AI coding agents to follow.
Provides a comprehensive MCP server for the Pipecat voice AI framework, enabling intelligent search and retrieval from documentation and GitHub issues via Claude Desktop or Cursor.
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