发现我们为 learning & documentation 精心策划的 MCP 服务器集合。浏览 1782 个服务器,找到满足您需求的完美 MCP。
Enables semantic search and management of documentation through vector similarity using RAG techniques.
Analyze chess positions and get professional evaluations using Stockfish within Claude.
Centralizes a collection of resources to boost productivity within the Cursor AI-powered IDE.
Navigate the Model Context Protocol ecosystem with this curated collection of resources, tools, and services.
Provides LLMs with access to documentation websites by scraping them with crawl4ai, enabling real-time documentation access for AI tools.
Provides a curated navigation site for Model Context Protocol (MCP) resources, tools, and services.
Provides comprehensive tutorials for mastering Model Context Protocol (MCP) development using Rust.
Provides a standardized interface to access aging and longevity research data for AI systems through the Model Context Protocol (MCP).
Stores AI memories as Obsidian-compatible Markdown files, enabling knowledge graph visualization.
Integrates AI interfaces with specialized Contextual AI agents for context-aware, grounded responses.
Transforms any documentation website into an AI-accessible knowledge base, making its content searchable and usable by AI assistants.
Serves AI agents with comprehensive context, documentation, and intelligent development assistance for the HeroUI component library via a Model Context Protocol (MCP) server.
Integrates official Agent Development Kit documentation into Gemini CLI for accurate, real-time information retrieval.
Guides AI-powered IDEs through a comprehensive spec-driven development workflow, from goal setting to task execution.
Provides example Model Context Protocol (MCP) servers and guidance for integration with AI tools like GitHub Copilot Chat.
Integrates Vale prose linting into AI coding assistants to check files for style and grammar issues.
Empower any AI agent with modular, reusable domain-specific capabilities by integrating Claude's Skills pattern.
Empower AI models with private, offline, and shareable Retrieval-Augmented Generation (RAG) libraries built directly from your own documentation.
Provides AI assistants with programmatic access to the Midnight blockchain, enabling contract search, code analysis, and documentation exploration.
Establishes a personal memory layer for AI assistants, enabling semantic search, philosophical reflection, and knowledge management.
Scroll for more results...