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
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.
MCP server for MySQL and MariaDB that lets AI agents inspect schemas, list tables, and run parameterized SQL queries. Supports read-only or read-write modes so agents can explore data, debug, and prototype against a MySQL database with controlled access.
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 AI agents with access to ClickHouse analytical databases through the Model Context Protocol. Enables running analytical queries, exploring table schemas, inspecting materialized views, and monitoring query performance. Designed for OLAP workloads with support for large result sets and query profiling.
MCP server for Neon's serverless PostgreSQL platform. Enables AI agents to manage Neon projects, branches, databases, and roles. Supports creating database branches for development and testing, running SQL queries, managing connection strings, and performing schema migrations. Leverages Neon's instant branching for safe experimentation without affecting production data.
MCP server for Google BigQuery that lets AI agents explore datasets, inspect table schemas, and run SQL analytics queries with dry-run cost estimation. Useful for natural-language data analysis, ad-hoc reporting, and pipeline debugging against large-scale BigQuery warehouses.
Official Snowflake MCP server enabling AI agents to query and analyze data in the Snowflake AI Data Cloud. Supports running SQL against warehouses, exploring databases and schemas, describing tables, and invoking Cortex AI services for search and analytics, with role-based access control honored end to end.
MCP server for DuckDB, the fast in-process analytical database. Lets AI agents run analytical SQL over local files (CSV, Parquet, JSON), attach databases, inspect schemas, and profile queries. Ideal for ad-hoc data analysis, ETL prototyping, and querying large columnar files without a separate database server.
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.
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.
Apache Doris' MCP server provides agents with governed access to Doris analytics databases for schema discovery, query assistance, and operational investigation.
InfluxData's MCP server connects agents to InfluxDB 3 for SQL queries, schema exploration, and time-series database operations.
Google's MCP Toolbox provides secure, ready-made and custom tools for database queries, schema operations, and semantic search in agent workflows.
Metabase's built-in MCP server that lets AI clients connect directly to a Metabase instance, scoped to the connecting user's permissions. Enables agents to discover databases and models, run queries, and retrieve results and dashboards so teams can ask questions of their business intelligence data in natural language.
Official MCP server for DuckDB and MotherDuck. Lets AI assistants run SQL analytics directly against local DuckDB files, in-memory databases, S3-hosted data, and MotherDuck cloud warehouses. Supports read and write queries, browsing database catalogs, and switching between connections on the fly, making it well suited for conversational data exploration and lightweight analytics.
MCP server for interacting with a Tinybird Workspace from any MCP client. Lets AI agents explore data sources, call published API endpoints, run SQL queries over real-time data, and push datafiles, making Tinybird's analytics readily available to LLM-driven workflows.
Official Supabase MCP server for database and backend integration. Enables AI agents to query PostgreSQL databases, manage tables and schemas, handle authentication users, interact with storage buckets, and invoke edge functions. Provides full access to Supabase project management including migrations and type generation.
The official Azure MCP Server brings Microsoft Azure to AI agents. It lets models query and manage Azure resources through natural language — Storage blobs and tables, Cosmos DB, Azure SQL, Key Vault, Monitor/Log Analytics (KQL), App Configuration, and more — and run Azure CLI commands, enabling cloud automation and infrastructure workflows directly from your tools.
Confluent's open-source MCP server that connects AI assistants to Confluent Cloud, Confluent Platform, and standalone Apache Kafka deployments. Provides tools to manage Kafka topics and connectors, work with Schema Registry, and run Flink SQL statements through natural language, helping teams operate streaming data platforms from an MCP client.
Community-supported MCP server from the Couchbase ecosystem that lets AI assistants interact with data in Couchbase clusters and Capella. Exposes tools to browse scopes and collections, run SQL++ (N1QL) queries, and read or modify documents, with authentication and safety controls enforced by the server. Useful for conversational data exploration and operational queries against Couchbase.
Community MCP server that connects a personal WhatsApp account to AI assistants. Using the WhatsApp multi-device web API, it lets agents search and read your messages and contacts and send messages, including media. Messages are stored locally in SQLite and only shared with the model when the agent accesses them through tools, keeping data on your machine.
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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