Servidores MCP
El registro abierto de servidores Model Context Protocol. Encuentra herramientas, recursos y prompts para tus agentes de IA, filtrados por categoría, transporte o caso de uso.
Servidores
177
Herramientas
471
Categorías
11
Colaboradores
155
MCP server for Exa's neural search API. Provides AI agents with powerful web search capabilities using embeddings-based semantic search. Returns clean, parsed content from web pages with relevance scoring. Supports filtering by domain, date range, and content type for precise information retrieval from the internet.
MCP server for Firecrawl's web scraping and crawling API. Converts any website into clean, LLM-ready markdown or structured data. Supports single page scraping, multi-page crawling with depth control, sitemap-based extraction, and batch operations. Handles JavaScript-rendered pages, bypasses common anti-bot measures, and returns structured content suitable for RAG pipelines and knowledge base construction.
MCP server for searching and accessing arXiv research papers. Enables AI agents to search papers with filters for date ranges and categories, download full paper content, read papers in markdown format, and perform semantic search across locally stored papers. Supports citation graph exploration via Semantic Scholar and research alert watches for tracking new publications on topics of interest.
MCP server for Tavily's AI-optimized search engine. Designed specifically for LLM agents and RAG applications, providing concise, factual search results with source attribution. Supports general web search, news search, and direct Q&A extraction. Returns pre-processed content optimized for AI consumption with relevance scoring and content deduplication.
MCP server that fetches transcripts, captions, and metadata from YouTube videos so AI agents can summarize, search, and analyze video content without watching it. Supports multiple languages, timestamped segments, and channel/playlist lookups for research and content workflows.
MCP server that provides access to Wikipedia content. Lets AI agents search articles, fetch full or summarized page content, and resolve references, giving models reliable, citable background knowledge for research and question answering.
Community MCP server that provides privacy-friendly web search through DuckDuckGo, plus fetching and parsing of web page content into clean text. Lets AI agents look up current information and retrieve source pages without an API key, making it a lightweight option for research and retrieval workflows. Not affiliated with DuckDuckGo.
Skills frente a servidores MCP
¿cuál es la diferencia?Skillsel «qué hacer»
Una Skill reúne conocimientos prácticos —instrucciones, un prompt de ejemplo y modelos recomendados— para que un agente realice una tarea de forma consistente. Las Skills aportan conocimiento, no nuevas conexiones.
Servidores MCPel «cómo conectarse»
Un servidor MCP proporciona nuevas capacidades a un agente conectándolo con sistemas reales —bases de datos, API o archivos— mediante un transporte. MCP añade conexiones y acciones, no instrucciones de tarea.
Regla práctica: usa una Skill cuando necesites que el modelo realice bien una tarea y un servidor MCP cuando necesites conectarlo con una herramienta o sistema. Se complementan: una Skill puede utilizar las herramientas que proporciona un servidor MCP.
¿Has creado un servidor MCP?
Envíalo al registro: es de código abierto y está mantenido por la comunidad.