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.
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Servidores
177
Herramientas
471
Categorías
11
Colaboradores
155
Official Cloudflare MCP server for managing Cloudflare services. Enables AI agents to interact with Workers, KV namespaces, R2 storage, D1 databases, and DNS records. Supports deploying Workers scripts, managing environment variables, querying analytics, and configuring security settings across Cloudflare's edge network.
MCP server for Sentry error tracking integration. Enables AI agents to retrieve and analyze issues, view error stack traces, search events by query, and access project performance data. Helps developers debug production errors by providing contextual error information directly in AI-powered development workflows.
Official MCP server for Qdrant vector search engine. Acts as a semantic memory layer enabling AI agents to store and retrieve information using vector similarity search. Supports storing text with metadata, semantic querying, configurable embedding models via FastEmbed, and both cloud-hosted and local Qdrant instances. Useful for building RAG pipelines, code search, knowledge bases, and long-term agent memory.
Provides access to AWS documentation and service information through the Model Context Protocol. Enables AI agents to search AWS documentation, retrieve service descriptions, look up API references, and find best practices for AWS services. Part of the official AWS Labs MCP servers collection with multiple AWS-focused servers available.
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.
Official MCP server for interacting with MongoDB databases and MongoDB Atlas. Enables AI agents to query collections, run aggregations, manage indexes, inspect schemas, and perform CRUD operations. Also supports Atlas cloud management including cluster provisioning, database user management, performance advisor, and stream processing. Supports read-only mode for safe exploration.
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.
Provides a structured sequential thinking tool through the Model Context Protocol. Enables AI agents to break down complex problems into numbered thought steps, revise previous thoughts, branch into alternative paths, and adjust the total number of steps dynamically. Useful for multi-step reasoning, planning, and analysis tasks that benefit from explicit step-by-step thinking.
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.
Ofrece funciones completas de búsqueda mediante Brave Search API y Model Context Protocol. Permite a los agentes de IA realizar búsquedas web, de negocios locales, imágenes, vídeos y noticias, además de generar resúmenes con IA. Admite transportes STDIO y HTTP.
Provides HTTP request capabilities through the Model Context Protocol. Enables AI agents to fetch web content, retrieve API responses, and download resources from URLs. Supports converting HTML to Markdown for easier consumption and can handle various content types including JSON, text, and binary data.
Proporciona acceso seguro al sistema de archivos local mediante Model Context Protocol. Permite a los agentes de IA leer, escribir, buscar y gestionar archivos y directorios con controles de acceso configurables. Admite operaciones como leer archivos, crear directorios, mover archivos y buscar mediante patrones glob.
Servidor MCP oficial de GitHub que conecta herramientas de IA directamente con la plataforma de GitHub. Permite a los agentes de IA gestionar repositorios, issues, pull requests, ramas, archivos, flujos de GitHub Actions y seguridad del código. Admite un modo remoto mediante OAuth y modos locales mediante Docker o binario, con configuración detallada de herramientas.
Reference MCP server for Git repository operations. Provides tools to read, search, and manipulate Git repositories including viewing commit history, diffs, branches, file contents at specific revisions, and repository status. Enables AI agents to understand code changes and navigate version history without direct filesystem access.
Provides persistent memory capabilities through a knowledge graph stored in a local JSON file. Enables AI agents to create, read, update, and delete entities and their relationships. Useful for maintaining context across conversations, storing user preferences, and building structured knowledge bases that persist between sessions.
Proporciona acceso de solo lectura a bases de datos PostgreSQL mediante Model Context Protocol. Permite a los agentes de IA inspeccionar esquemas, ejecutar consultas SELECT y explorar estructuras de tablas. Utiliza aislamiento de transacciones de solo lectura para evitar modificaciones accidentales. Formaba parte de los servidores de referencia y ahora está archivado y disponible en servers-archived.
Provides browser automation capabilities through the Model Context Protocol using Puppeteer. Enables AI agents to navigate web pages, take screenshots, click elements, fill forms, and execute JavaScript in a browser context. Useful for web scraping, testing, and interacting with web applications programmatically. Originally part of the reference servers, now archived and available in servers-archived.
MCP server for Redis key-value store interaction. Enables AI agents to read and write data in Redis, manage keys, work with data structures (strings, hashes, lists, sets), and perform pub/sub operations. Useful for caching, session management, real-time data, and inter-service communication in distributed systems.
Provides access to the Slack API through the Model Context Protocol. Enables AI agents to read and send messages, manage channels, search conversation history, and interact with Slack workspaces. Supports listing channels, reading threads, posting messages, and adding reactions programmatically. Originally maintained by Anthropic, now maintained by Zencoder.
MCP server for SQLite database interaction and business intelligence. Enables AI agents to query SQLite databases, create and modify tables, run analytical queries, and generate insights from data. Supports read-write operations with transaction safety and provides schema introspection for understanding database structure.
Reference MCP server providing time and timezone conversion capabilities. Enables AI agents to get the current time in any timezone, convert between timezones, calculate time differences, and format dates. Useful for scheduling, international coordination, and any task requiring accurate time awareness.
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.
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