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。1169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。
Demonstrates a complete e-commerce application integrating the Model Context Protocol with the FakeStore API.
Enables AI assistants to access Go documentation and package listings via the Model Context Protocol.
Demonstrates building a Model Context Protocol (MCP) server in Python to expose custom tools and resources to large language models (LLMs) and MCP clients.
Streamlines software development projects by providing structured workflow tools across various complexity levels and phases.
Enables AI assistants to download and read attachments from Confluence pages via a Model Context Protocol (MCP) server.
Provides seamless access to academic literature databases, enabling researchers to accelerate their literature review process with LLMs and MCP clients.
Kickstart documentation projects by leveraging a customizable Docusaurus template with built-in features and extensibility.
Enables Large Language Models to retrieve and reference Jewish texts from the Sefaria library through a standardized interface.
Provides access to Payman AI's documentation for AI assistants to aid developers with integration questions.
Ingests a CSV of acronyms and initialisms to provide a server-based lookup tool for their full meanings and descriptions.
Provides current local datetime information in a clean single-line format.
Connects AI applications to the huuh.me platform, facilitating collaborative AI and knowledge management.
Enables AI models to query and analyze Practera learning data through a GraphQL API.
Manages text notes through a Model Context Protocol server, offering resources, creation tools, and summarization prompts.
Demonstrates how to build Model Context Protocol (MCP) servers using the Python SDK.
Provides access to Metaplex documentation and repository information through the Model Context Protocol.
Provides a simple notes system for Solana documentation context within the Model Context Protocol.
Provides foundational example code for building Model Context Protocol (MCP) servers using FastAPI.
Provides a hands-on Python guide for understanding the Model Context Protocol, which standardizes how AI models and agents interact with their operational context.
Provides a functional example of a FastMCP server for learning Model Context Protocol integration.
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