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 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.
Official MCP server for the Perplexity API Platform. Provides AI agents with real-time web search, deep research, and advanced reasoning capabilities through Sonar models. Includes tools for quick web search, conversational Q&A with citations, comprehensive deep research reports, and complex analytical reasoning. Returns answers with source attribution and supports configurable timeouts for long research queries.
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.
MCP server for the Reddit API. Lets AI agents search subreddits, fetch hot/new/top posts, read comment threads, and retrieve user activity. Useful for market and community research, sentiment monitoring, trend discovery, and summarizing discussions across communities.
MCP server for Hacker News. Lets AI agents fetch top, new, best, Ask HN, and Show HN stories, read comment threads, and look up items and users via the official Firebase API. Useful for tracking tech trends, summarizing discussions, and research into what the developer community is talking about.
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.
Official MCP server backed by the Kagi API. Exposes Kagi's high-quality search and summarization tools to MCP-compatible clients, including web search and the Universal Summarizer for pages and videos. Useful for research workflows that want ad-free, privacy-respecting results with concise summaries. Requires a Kagi API key.
OpenBB's MCP server connects agents to financial market data, research, and analytics for evidence-based investment and business workflows.
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?
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