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。2201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。
Analyzes code and provides debugging capabilities using the Perplexity AI API within the Claude desktop client.
Provides a foundational example for integrating custom tools with the Gemini CLI using the Model Context Protocol (MCP).
Provides LLM clients with dynamic access to up-to-date implementation details and documentation from popular AI libraries like LangChain, LlamaIndex, and OpenAI.
Provides a structured environment for building custom tools and servers compatible with the Model Context Protocol (MCP) using mcp-framework.
Generates detailed financial reports for various companies, serving as a practical demonstration for learning the Model Context Protocol (MCP).
Provides a foundational server implementation for Dremio's Materialized Centralized Processing (MCP) protocol, enabling file-based data interactions.
Connects AI agents to remote Git repositories to fetch and search markdown documentation and notes.
Access real-time information about U.S. National Parks, including park details, alerts, activities, and facilities via the National Park Service API.
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.
Demonstrates a Model Context Protocol (MCP) server featuring example tools, resources, and prompts for Large Language Model (LLM) integration.
Demonstrates the Model Context Protocol (MCP) through a simple client-server greeting tool utilizing standard input and output for communication.
Provides professional C++ coding style checks and best practice suggestions.
Demonstrates fundamental Model Context Protocol (MCP) server creation on .NET 10, enabling AI assistants to utilize essential mathematical and string processing tools.
Tracks student learning progress and schedules review sessions using a personalized knowledge graph with spaced repetition.
Streamlines LaTeX manuscript compilation with robust command-line interface and MCP server capabilities.
Integrates Canvas LMS data directly with AI clients for querying courses, assignments, grades, and more, ensuring user data privacy.
Provides documentation search and framework reference for AI coding assistants to facilitate Symbols.app development.
Provides Retrieval Augmented Generation (RAG) capabilities for your markdown documentation.
Query evidence-based supplement research data directly from AI assistants like Claude, Cursor, and Windsurf.
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