发现我们为 learning & documentation 精心策划的 MCP 服务器集合。浏览 1291 个服务器,找到满足您需求的完美 MCP。
Provides seamless access to academic literature databases, enabling researchers to accelerate their literature review process with LLMs and MCP clients.
Generates Model Context Protocol servers automatically from OpenAPI specifications and FastAPI applications.
Provides a foundational Model Context Protocol (MCP) server implementation with boilerplate code for user and project management functionalities.
Serves as an interactive AI teaching assistant, simplifying complex artificial intelligence concepts for workshop participants and learners.
Facilitates educational penetration testing by enabling AI assistants to interact securely with authentic Kali Linux tools via a Model Context Protocol server.
Enables searching and retrieving scientific articles from PubMed via the NCBI E-utilities API.
Illustrates the practical implementation of OAuth and Dynamic Client Registration (DCR) for a Remote Model Context Protocol (MCP) server.
Connects date-fns documentation as an MCP server for various AI clients and development environments.
Serves comprehensive Institute of Internal Auditors (IIA) professional standards and resources to AI assistants via a Model Context Protocol server.
Demonstrates basic Model Context Protocol server functionality with FastMCP and uv for dependency management.
Provides AI assistants with programmatic access to the Consumer Rights Wiki, documenting modern consumer exploitation issues.
Serves documentation for applications using the Model Context Protocol (MCP).
Provides instant access to comprehensive development knowledge, examples, and patterns for mastering the Model Context Protocol.
Provides programmatic access to Cursor and Claude Code chat history, enabling search, organization, and retrieval of past AI conversations.
Offers a remote Model Context Protocol server enabling AI-powered tutoring and personalized learning analytics for students preparing for Romanian police academy entrance exams.
Provides cat facts via a command-line interface.
Demonstrates creating MCP clients and servers in Python and TypeScript, integrating with local LLMs.
Showcases various .NET applications and code examples across different platforms and technologies for learning and development.
Empower large language models to access and retrieve technical documentation on-demand through a RAG system and MCP server.
Validates and renders Mermaid diagrams for use with LLMs, incorporating an essential fix for WSL stdin.
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