AI Agent for JDBC MCP Server
Seamlessly connect Large Language Models (LLMs) to your databases using the JDBC Model Context Protocol (MCP) Server. Effortlessly inspect, query, create, and modify database content across PostgreSQL, Oracle, MariaDB, SQLite, and many more—just by providing a JDBC URL. Accelerate your data workflows and empower AI-driven database management with robust, secure, and flexible integration.
Universal Database Integration for AI
Connect your AI workflows to virtually any JDBC-compatible database. The JDBC MCP Server supports PostgreSQL, Oracle, MariaDB, MySQL, SQLite, SQL Server, and more, providing a unified bridge for LLMs to interact with your data securely and efficiently.
- Broad Database Support.
- Integrate with PostgreSQL, Oracle, MariaDB, MySQL, SQLite, SQL Server, and more through a single interface.
- AI-Driven Data Access.
- Empower LLMs to read, write, and manage database content, driving smarter automation and insights.
- Secure & Controlled.
- Leverage secure connectivity and granular control for safe AI-driven database interactions.
- Lightning-Fast Deployment.
- Start the server with a single command. No heavy setup—just provide a JDBC URL and go.
Powerful Query & Management Tools
Harness a suite of built-in tools to perform SELECT, INSERT, UPDATE, DELETE operations; manage tables; and describe schemas—directly from your AI agent. Streamline manipulation and exploration of complex data structures in real time.
- Read & Write Queries.
- Run SELECT, INSERT, UPDATE, and DELETE operations securely from your LLM workflows.
- Table Management.
- Create, list, and describe tables programmatically to enable dynamic schema exploration.
- Prompt-Based Exploration.
- Jumpstart AI-powered data discovery with example prompts and ready-to-use sample databases.
Effortless Setup & Scalability
Launch the JDBC MCP Server instantly with JBang—no manual driver management or complicated installation required. Easily scale from in-memory test databases to live production environments, and leverage downloadable database samples for rapid prototyping.
- Instant Launch.
- Deploy the server with a single JBang command—no Java expertise required.
- Flexible for Any Workflow.
- Supports both in-memory and live databases for development, testing, and production.
MCP INTEGRATION
Available JDBC MCP Integration Tools
The following tools are available as part of the JDBC MCP integration:
- read_query
Execute SELECT queries on the database to retrieve and filter data from tables.
- write_query
Perform INSERT, UPDATE, or DELETE operations to modify or remove data in the database.
- create_table
Create new tables in the database with specified columns and schema.
- list_tables
List all tables currently available in the connected database.
- describe_table
Retrieve schema details and column information for a specific table.
Effortlessly Connect LLMs to Any Database with JDBC MCP Server
Explore, query, and manage your databases using natural language. Instantly set up the Model Context Protocol server for JDBC and empower your AI workflows with seamless database integration—no complex configuration required.
What is Quarkiverse
Quarkiverse is an open and collaborative ecosystem focused on developing extensions and tools for Quarkus, a Kubernetes-native Java framework. Quarkiverse brings together community-driven efforts to build reusable, high-quality extensions that simplify and accelerate Java development for cloud-native applications. The project encourages innovation and contribution by providing a central hub for extension documentation, guidance, and resources. This enables developers to extend Quarkus capabilities, integrate with external systems, and rapidly build robust solutions for modern enterprise, AI, and microservices environments.
Capabilities
What we can do with Quarkus MCP Server
Quarkus MCP Server is a Quarkiverse extension that implements the Model Context Protocol (MCP), enabling seamless integration between LLM applications and external data sources or tools. With this extension, developers can use declarative and programmatic APIs to expose prompts, resources, and AI tools efficiently. It supports multiple communication transports (stdio and HTTP) and allows easy integration with AI frameworks like LangChain4j, making it a powerful choice for building AI-enhanced applications.
- Expose AI-powered prompts
- Create and register prompt templates that LLMs can access and complete.
- Integrate external resources
- Expose files, data sources, or other resources to LLMs through a standardized API.
- Support multiple transports
- Communicate over stdio or HTTP/SSE for flexible deployment scenarios.
- Programmatic feature registration
- Dynamically register prompts and resources at startup using code.
- Fine-grained execution model
- Control blocking and non-blocking logic for optimal resource utilization.
What is Quarkiverse
AI agents can benefit from using Quarkus MCP Server by gaining standardized, secure access to external resources, tools, and prompts within an enterprise Java environment. This enables agents to retrieve context-rich data, execute custom business logic, and interact with various backends, all while leveraging Quarkus’s performance, scalability, and developer-friendly model.