MCP Connector

Connect to Databases via JDBC

A Java/Quarkus MCP server for any JDBC-compatible database, with SQL, SPARQL, and SPASQL query tools for Virtuoso.

Works with virtuosojdbc

91
Spark score
out of 100
Updated 12 months ago
Version 1.0.0
Models
universal

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Why it matters

Integrate diverse databases into your AI workflows by leveraging this JDBC connector. It enables seamless data querying, schema exploration, and even AI-assisted data interaction for Virtuoso and other JDBC-compatible systems.

Outcomes

What it gets done

01

Query any database with a JDBC driver using SQL.

02

Retrieve database schemas and table structures.

03

Execute SPARQL and SPASQL queries for Virtuoso.

04

Utilize AI for data interaction via Virtuoso Support Assistant.

Install

Add it to your toolbox

Run in your project directory:

curl -fsSL https://spark.entire.vc/get/vb-openlink-generic-java-database-connectivity | bash

Capabilities

Tools your agent gets

jdbc_get_schemas

Get a list of database schemas available in the connected DBMS

jdbc_get_tables

Get a list of tables associated with the selected database schema

jdbc_describe_table

Provide detailed description of a table including columns, data types, and constraints

jdbc_filter_table_names

Get a list of tables based on a substring pattern from the selected schema

jdbc_query_database

Execute an SQL query and return results in JSONL format

jdbc_execute_query

Execute an SQL query and return results in JSONL format

jdbc_execute_query_md

Execute an SQL query and return results in Markdown table format

jdbc_spasql_query

Execute a SPASQL query and return results (Virtuoso-specific)

+2 tools

Overview

OpenLink Generic Java Database Connectivity MCP Server

A Java/Quarkus MCP server for JDBC databases with schema/table introspection, SQL query execution in JSON/JSONL/Markdown, and Virtuoso-specific SPARQL/SPASQL and AI Support Assistant tools. Use when an AI assistant needs schema introspection and SQL access to a JDBC database, or Virtuoso-specific SPARQL/SPASQL and AI Support Assistant features; requires Java 21+.

What it does

This is a lightweight Java-based MCP server built with Quarkus for JDBC databases, compatible with Virtuoso DBMS and any other database with a JDBC driver. It provides ten tools: jdbc_get_schemas lists all schema names from the connected database; jdbc_get_tables retrieves table information for a specific schema or the connection's default; jdbc_describe_table returns detailed column information for a named table (names, data types, nullability, autoincrement, primary and foreign keys); jdbc_filter_table_names filters tables by a substring pattern; jdbc_query_database, jdbc_execute_query, and jdbc_execute_query_md run a SQL query and return results as JSON, JSONL, or a Markdown table respectively, chosen by which format best fits the client. Three tools are Virtuoso-specific: jdbc_spasql_query executes a SPASQL (SQL/SPARQL hybrid) query with configurable max_rows (default 20) and timeout (default 30000ms), calling Virtuoso's underlying stored procedure; jdbc_sparql_query runs a SPARQL query with a configurable result format (default json) and a query timeout (default 30000ms); and jdbc_virtuoso_support_ai passes a required prompt and an optional API key (default "none") to Virtuoso's built-in AI Support Assistant function. Every tool accepts optional user/password/url parameters (defaulting to "demo"/"demo"/the connection default) so a single server instance can be pointed at different credentials or databases per call.

When to use - and when NOT to

Use this to give an AI assistant read access to schema structure and SQL query execution against any JDBC-reachable database, or to use Virtuoso-specific capabilities like SPARQL/SPASQL hybrid queries or its built-in AI Support Assistant.

Requires Java 21 or higher. Non-Virtuoso databases only get the generic JDBC tools (schema/table introspection and SQL execution) - the SPASQL, SPARQL, and Virtuoso Support AI tools are explicitly Virtuoso-only features and won't function against another JDBC backend.

Capabilities

Schema and table introspection (list schemas, list or filter tables, describe a table's full column structure including keys), SQL query execution with a choice of JSON, JSONL, or Markdown table output, and - for Virtuoso specifically - SPASQL and SPARQL query execution plus an AI Support Assistant integration.

How to install

Requires Java 21+. Clone the repository (git clone https://github.com/OpenLinkSoftware/mcp-jdbc-server.git), then configure a .env file with jdbc.url, jdbc.user, jdbc.password, and jdbc.api_key overriding the defaults. For Claude Desktop with Virtuoso, point the command at java -jar MCPServer-1.0.0-runner.jar with those JDBC settings as environment variables; for other JDBC drivers, use java -cp MCPServer-1.0.0-runner.jar:driver1.jar:driverN.jar io.quarkus.runner.GeneratedMain instead, adding each driver JAR to the classpath. For troubleshooting, the MCP Inspector (npx @modelcontextprotocol/inspector) can connect directly to the running server - for additional drivers like Oracle (ojdbc17.jar) or Informix (jdbc-15.0.0.1.1.jar), register their JARs on $CLASSPATH first, then launch the inspector with the same -cp/GeneratedMain invocation used for production.

Who it's for

Developers who need an AI assistant to query any JDBC-reachable database's schema and data, or specifically Virtuoso users who want SPARQL/SPASQL query access and Virtuoso's AI Support Assistant through the same interface.

git clone https://github.com/OpenLinkSoftware/mcp-jdbc-server.git  
cd mcp-jdbc-server
Source README

Features

  • Get Schemas: Fetch and list all schema names from the connected database.
  • Get Tables: Retrieve table information for specific schemas or all schemas.
  • Describe Table: Generate a detailed description of table structures, including:
    • Column names and data types
    • Nullable attributes
    • Primary and foreign keys
  • Search Tables: Filter and retrieve tables based on name substrings.
  • Execute Stored Procedures: A Virtuoso-specific feature! Execute stored procedures and retrieve results.
  • Execute Queries:
    • JSONL result format: Optimized for structured responses.
    • Markdown table format: Ideal for reporting and visualization.

Prerequisites

MCP server requires Java 21 or above.


Installation

Clone this repository:

git clone https://github.com/OpenLinkSoftware/mcp-jdbc-server.git  
cd mcp-jdbc-server

Environment Variables

Update your .env by overriding these defaults to match your preferences:

jdbc.url=jdbc:virtuoso://localhost:1111
jdbc.user=dba
jdbc.password=dba
jdbc.api_key=xxx

Configuration

For Claude Desktop users using Virtuoso and its JDBC driver:

Add the following to claude_desktop_config.json:

{
  "mcpServers": {
    "my_database": {
      "command": "java",
      "args": ["-jar", "/path/to/mcp-jdbc-server/MCPServer-1.0.0-runner.jar"],
      "env": {
        "jdbc.url": "jdbc:virtuoso://localhost:1111",
        "jdbc.user": "username",
        "jdbc.password": "password",
        "jdbc.api_key": "sk-xxx"
      }
    }
  }
}

For Claude Desktop users using another JDBC driver or a combination of drivers:

Add the following, edited to suit your local environment, to claude_desktop_config.json:

    "jdbc": {
      "command": "java",
      "args": [
        "-cp",
        "/path/to/mcp-jdbc-server/MCPServer-1.0.0-runner.jar:/path/to/jdbc_driver1.jar:/path/to/jdbc_driverN.jar",
        "io.quarkus.runner.GeneratedMain"
      ],
      "env": {
        "jdbc.url": "jdbc:virtuoso://localhost:1111",
        "jdbc.user": "dba",
        "jdbc.password": "dba"
      }
    }

Use

Tools Provided

After successful installation, the following tools will be available to MCP client applications.

Overview
name description
jdbc_get_schemas List database schemas accessible to connected database management system (DBMS).
jdbc_get_tables List tables associated with a selected database schema.
jdbc_describe_table Provide the description of a table associated with a designated database schema. This includes information about column names, data types, nulls handling, autoincrement, primary key, and foreign keys.
jdbc_filter_table_names List tables, based on a substring pattern from the q input field, associated with a selected database schema.
jdbc_query_database Execute a SQL query and return results in JSONL format.
jdbc_execute_query Execute a SQL query and return results in JSONL format.
jdbc_execute_query_md Execute a SQL query and return results in Markdown table format.
jdbc_spasql_query A Virtuoso-specific feature! Execute a SPASQL query and return results.
jdbc_sparql_query A Virtuoso-specific feature! Execute a SPARQL query and return results.
jdbc_virtuoso_support_ai A Virtuoso-specific feature! Interact with LLMs through the Virtuoso Support Assistant/Agent.
Detailed Description
  • jdbc_get_schemas

    • Retrieve and return a list of all schema names from the connected database.
    • Input parameters:
      • user (string, optional): Database username. Defaults to "demo".
      • password (string, optional): Database password. Defaults to "demo".
      • url (string, optional): JDBC URL connection string.
    • Returns a JSON string array of schema names.
  • jdbc_get_tables

    • Retrieve and return a list containing information about tables in a specified schema. If no schema is provided, uses the connection's default schema.
    • Input parameters:
      • schema (string, optional): Database schema to filter tables. Defaults to connection default.
      • user (string, optional): Database username. Defaults to "demo".
      • password (string, optional): Database password. Defaults to "demo".
      • url (string, optional): JDBC URL connection string.
    • Returns a JSON string containing table information (e.g., TABLE_CAT, TABLE_SCHEM, TABLE_NAME, TABLE_TYPE).
  • jdbc_filter_table_names

    • Filters and returns information about tables whose names contain a specific substring.
    • Input parameters:
      • q (string, required): The substring to search for within table names.
      • schema (string, optional): Database schema to filter tables. Defaults to connection default.
      • user (string, optional): Database username. Defaults to "demo".
      • password (string, optional): Database password. Defaults to "demo".
      • url (string, optional): JDBC URL connection string.
    • Returns a JSON string containing information for matching tables.
  • jdbc_describe_table

    • Retrieve and return detailed information about the columns of a specific table.
    • Input parameters:
      • schema (string, required): The database schema name containing the table.
      • table (string, required): The name of the table to describe.
      • user (string, optional): Database username. Defaults to "demo".
      • password (string, optional): Database password. Defaults to "demo".
      • url (string, optional): JDBC URL connection string.
    • Returns a JSON string describing the table's columns (e.g., COLUMN_NAME, TYPE_NAME, COLUMN_SIZE, IS_NULLABLE).
  • jdbc_query_database

    • Execute a standard SQL query and return the results in JSON format.
    • Input parameters:
      • query (string, required): The SQL query string to execute.
      • user (string, optional): Database username. Defaults to "demo".
      • password (string, optional): Database password. Defaults to "demo".
      • url (string, optional): JDBC URL connection string.
    • Returns query results as a JSON string.
  • jdbc_query_database_md

    • Execute a standard SQL query and return the results formatted as a Markdown table.
    • Input parameters:
      • query (string, required): The SQL query string to execute.
      • user (string, optional): Database username. Defaults to "demo".
      • password (string, optional): Database password. Defaults to "demo".
      • url (string, optional): JDBC URL connection string.
    • Returns query results as a Markdown table string.
  • jdbc_query_database_jsonl

    • Execute a standard SQL query and return the results in JSON Lines (JSONL) format (one JSON object per line).
    • Input parameters:
      • query (string, required): The SQL query string to execute.
      • user (string, optional): Database username. Defaults to "demo".
      • password (string, optional): Database password. Defaults to "demo".
      • url (string, optional): JDBC URL connection string.
    • Returns query results as a JSONL string.
  • jdbc_spasql_query

    • A Virtuoso-specific feature!
    • Execute a SPASQL (SQL/SPARQL hybrid) query return results.
    • Input parameters:
      • query (string, required): The SPASQL query string.
      • max_rows (number, optional): Maximum number of rows to return. Defaults to 20.
      • timeout (number, optional): Query timeout in milliseconds. Defaults to 30000 (i.e., 30 seconds).
      • user (string, optional): Database username. Defaults to "demo".
      • password (string, optional): Database password. Defaults to "demo".
      • url (string, optional): JDBC URL connection string.
    • Returns the result from the underlying stored procedure call (e.g., Demo.demo.execute_spasql_query).
  • jdbc_sparql_query

    • A Virtuoso-specific feature!
    • Execute a SPARQL query and return results.
    • Input parameters:
      • query (string, required): The SPARQL query string.
      • format (string, optional): Desired result format. Defaults to 'json'.
      • timeout (number, optional): Query timeout in milliseconds. Defaults to 30000 (i.e., 30 seconds).
      • user (string, optional): Database username. Defaults to "demo".
      • password (string, optional): Database password. Defaults to "demo".
      • url (string, optional): JDBC URL connection string.
    • Returns the result from the underlying function call (e.g., "UB".dba."sparqlQuery").
  • jdbc_virtuoso_support_ai

    • A Virtuoso-specific feature!
    • Utilizes a Virtuoso-specific AI Assistant function, passing a prompt and optional API key.
    • Input parameters:
      • prompt (string, required): The prompt text for the AI function.
      • api_key (string, optional): API key for the AI service. Defaults to "none".
      • user (string, optional): Database username. Defaults to "demo".
      • password (string, optional): Database password. Defaults to "demo".
      • url (string, optional): JDBC URL connection string.
    • Returns the result from the AI Support Assistant function call (e.g., DEMO.DBA.OAI_VIRTUOSO_SUPPORT_AI).

Basic Use & Troubleshooting

MCP Inspector Connecting to Virtuoso's ODBC Driver

For basic MCP client use and troubleshooting, use the MCP Inspector as follows:

  1. Install the MCP Inspector:

    npm install -g @modelcontextprotocol/inspector
    
  2. Start the inspector:

    npx @modelcontextprotocol/inspector java -jar /path/to/mcp-jdbc-server/MCPServer-1.0.0-runner.jar
    

Access the URL returned by the inspector to troubleshoot MCP server interactions.

MCP Inspector Connecting to additional Drivers

For basic MCP client use and troubleshooting, use the MCP Inspector as follows:

  1. Install the JDBC Driver(s), ensuring their JAR files are registered with the host operating system's Java Virtual Machine (JVM) via $CLASSPATH. For instance:

    export CLASSPATH=$CLASSPATH:/path/to/driver1.jar:/path/to/driver2.jar:/path/to/driverN.jar
    
  2. Start the inspector using the following command-line arguments:

    npx @modelcontextprotocol/inspector java -cp MCPServer-1.0.0-runner.jar:/path/to/driver1.jar:/path/to/driver2.jar:/path/to/driverN.jar io.quarkus.runner.GeneratedMain
    
Use Example based on Oracle and Informix Drivers
  1. Assuming the following JDBC Driver information:

    • Oracle JDBC Driver URL Template

      jdbc:oracle:thin:@<hostname>:[port]:<SERVICEID>
      
    • Informix JDBC Driver URL Template

      jdbc:informix-sqli://<hostname>:<port>/<database></database>:<INFORMIXSERVER>=<SERVICEID>
      
  2. Install the Oracle (ojdbc17.jar) and/or Informix (jdbc-15.0.0.1.1.jar) JDBC Drivers, and ensure their JAR files are registered with the host operating system's Java Virtual Machine (JVM) via $CLASSPATH. For instance:

     export CLASSPATH=$CLASSPATH:/path/to/Java/Extensions/jdbc-15.0.0.1.1.jar
     export CLASSPATH=$CLASSPATH:/path/to/Java/Extensions/ojdbc17.jar
    
  3. Start the inspector using the following command-line arguments:

    npx @modelcontextprotocol/inspector java -cp MCPServer-1.0.0-runner.jar:/path/to/Java/Extensions/ojdbc17.jar:/path/to/Java/Extensions/jdbc-15.0.0.1.1.jar io.quarkus.runner.GeneratedMain
    
  4. Access the URL returned by the inspector and then use the jdbc_execute_query operation to query the target database, by providing actual values for the following input field templates:

    • JDBC URL
    • User
    • Password
    • Query

FAQ

Common questions

Discussion

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