Descubre nuestra colección curada de servidores MCP para database management. Explora 1735 servidores y encuentra los MCP perfectos para tus necesidades.
Provides a standardized interface for managing ML models, execution contexts, and communication protocols between applications and the HANA Cloud database.
Enables Large Language Models (LLMs) to query, analyze, and interact with Prometheus databases through predefined routes.
Enables AI models to interact with MySQL databases through a standardized interface.
Stores and loads JSON documents for use with Large Language Model (LLM) tools.
Enables Large Language Models to interact with Oracle Databases, generate SQL statements, and return results using prompts.
Enables database interaction and business intelligence capabilities through Apache IoTDB.
Exposes access to an InfluxDB instance using the InfluxDB OSS API v2 via a Model Context Protocol (MCP) server.
Enables AI agents to interact with PostgreSQL databases through a standardized Model Context Protocol (MCP).
Connects AI models with FalkorDB graph databases via the Model Context Protocol.
Manages records and files within a PocketBase instance, providing tools for data manipulation and migration management.
Provides an MCP server for Apache Iceberg catalogs, enabling metadata access and management.
Extends JDBC drivers to support dynamic, multi-language queries and federated data source connectivity.
Provides a comprehensive Message Control Protocol (MCP) server for managing Kafka Schema Registry operations.
Provides comprehensive access to the PubChem chemical database via the Model Context Protocol (MCP).
Provides advanced access to the ChEMBL chemical database through a Model Context Protocol (MCP) server.
Provides HTTP and Stdio transports for interacting with PostgreSQL databases through the Model Context Protocol.
Enables robust data extraction, manipulation, and transformation for BIM applications, specifically Autodesk Revit, to facilitate communication with MCP-compatible AI agents.
Automates the generation of complete Java layered code, including Entity, DAO, Service, and Controller, for multiple databases using smart database analysis.
Empowers AI assistants with persistent, intelligent memory capabilities through a unified graph database architecture.
Equips AI agents with a shared, persistent knowledge graph to retain facts, decisions, and context across sessions and tools.
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