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
Official Asana MCP server that connects AI tools to the Asana Work Graph. Enables agents to create and update tasks, manage projects and sections, add comments, search work, and summarize project status via a remote OAuth-secured endpoint.
MCP server for Todoist that lets AI agents create, update, complete, and query tasks using natural language. Supports projects, due dates, priorities, labels, and filters, making it easy to manage a personal or team task list conversationally.
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 HubSpot MCP server connecting AI tools to the HubSpot CRM. Enables agents to read and manage contacts, companies, deals, and tickets, search the CRM, and create engagements such as notes and tasks. Honors HubSpot scopes and rate limits via OAuth.
MCP server for Google Sheets. Lets AI agents read and write cell ranges, create and update spreadsheets and tabs, append rows, and apply formatting via the Sheets API with OAuth. Useful for lightweight data entry, reporting, dashboards, and automating spreadsheet-driven workflows.
MCP server for the ClickUp project management platform. Enables AI agents to create and update tasks, browse spaces, folders, and lists, and manage task status and assignees, bringing ClickUp work management into AI-powered tools.
Official dbt Labs MCP server for analytics engineering workflows. Lets AI agents run dbt commands (build, run, test), inspect models and lineage via the dbt project, and query the Semantic Layer and Discovery API in dbt Cloud. Useful for transforming data, validating models, and answering metric questions grounded in governed definitions.
A VSCode extension that turns your running VS Code instance into an MCP server, giving external AI agents (Claude Desktop, Claude Code, and others) direct access to VS Code's editing, navigation, and debugging capabilities. Supports reviewing code changes through diffs, real-time diagnostic streaming (type errors, lint warnings), terminal command execution, URL preview in the built-in browser, debug session management, and multi-window instance switching. Also relays built-in MCP servers introduced in VS Code 1.99, including GitHub Copilot tools.
MCP server for the Databricks Data Intelligence Platform. Enables AI agents to run SQL against the Unity Catalog, inspect schemas and tables, and manage and monitor jobs, bringing lakehouse data and workflows into AI-powered development tools.
MCP server for Salesforce that lets AI agents query and modify CRM data using SOQL, manage standard and custom objects (Accounts, Contacts, Opportunities, Cases), describe object metadata, and execute Apex anonymous blocks. Supports both production and sandbox orgs via OAuth or username-password flows.
MCP server for Trello that lets AI agents manage boards, lists, and cards. Supports creating and moving cards, updating due dates and labels, adding comments and checklists, and searching across boards, turning Trello into a conversational task and project tracker.
MCP server for Replicate, which hosts thousands of open machine learning models behind a single API. Lets AI agents search models, run predictions (image, video, audio, and text generation), poll prediction status, and retrieve outputs. Useful for adding generative media and specialized ML capabilities to agent workflows without managing infrastructure.
Official Semgrep MCP server for static application security testing. Lets AI agents scan code for security vulnerabilities and bugs, run custom rules, and return findings with severity and remediation guidance, embedding SAST into AI-powered development workflows.
Official Heroku MCP server that lets AI agents manage Heroku Platform resources. Supports listing and inspecting apps, scaling dynos, viewing logs, managing config vars and add-ons, and running one-off commands, so deployment and operations tasks can be handled conversationally.
Official Netlify MCP server for managing web deployments. Lets AI agents create and configure sites, trigger and monitor deploys, manage environment variables, and read build logs. Useful for shipping frontends and serverless functions, debugging failed builds, and automating deployment workflows from an AI assistant.
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.
Official PayPal MCP server for commerce and payments. Lets AI agents create and capture orders, issue invoices, process refunds, manage subscriptions, and query transactions and disputes via the PayPal APIs. Useful for building checkout integrations, automating billing, and reconciling payments from an AI assistant.
MCP server for the Weaviate open-source vector database. Enables AI agents to store objects, run semantic and hybrid searches, and manage collections, making it a memory and retrieval backend for RAG applications directly from AI-powered tools.
MCP server for Atlassian Bitbucket that connects AI tools to repositories, pull requests, branches, and pipelines. Enables agents to review and create pull requests, read file contents and diffs, leave comments, and inspect build status on Bitbucket Cloud and Server.
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 HashiCorp Vault secrets management. Enables AI agents to read and write secrets, list secret paths, and manage key/value engines under controlled policies, so applications and workflows can retrieve credentials securely from AI-powered tools.
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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