mcp-db-server-stateless

name	mcp-db-server-stateless
description	Stateless MCP database server enabling AI agents to query and manage MySQL, PostgreSQL, SQLite, SQL Server, Oracle, and H2 databases without storing credentials
triggers	["connect to my database with MCP","query database tables using AI","set up stateless database MCP server","execute SQL through MCP protocol","get database schema information","manage multiple databases with MCP","deploy MCP database service","configure Claude Desktop for database access"]

mcp-db-server Stateless Database MCP Server

Skill by ara.so — MCP Skills collection.

Overview

mcp-db-server is a stateless MCP (Model Context Protocol) service built with Spring Boot that enables AI agents to interact with databases directly. Unlike traditional database tools, it does not store any connection credentials—the AI client passes connection parameters with every request. The server caches connection pools in memory (5-minute TTL) for performance while maintaining zero persistence.

Supported Databases:

• MySQL (port 3306)
• PostgreSQL (port 5432)
• H2 (embedded)
• SQLite (file-based)
• SQL Server (port 1433)
• Oracle (port 1521)

Installation & Deployment

Quick Start with Maven

# Clone repository
git clone https://github.com/PerfectXM/mcp-db-server.git
cd mcp-db-server

# Run with Maven wrapper (Windows)
.\mvnw.cmd spring-boot:run

# Run with Maven wrapper (Linux/macOS)
./mvnw spring-boot:run

Server starts on http://localhost:8088 with SSE endpoint at /sse.

Docker Deployment

# Build image
docker build -t mcp-db-server .

# Run container
docker run -d -p 8088:8088 --name mcp-db-server mcp-db-server

# Or use docker-compose
docker-compose up -d

JAR Deployment

# Build JAR
./mvnw clean package -DskipTests

# Run JAR
java -jar target/mcp-db-server-1.0.0.jar

# Custom port
java -jar target/mcp-db-server-1.0.0.jar --server.port=9090

Configuration

Server Configuration (application.yml)

server:
  port: 8088

spring:
  ai:
    mcp:
      server:
        sse:
          enabled: true
          path: /sse
        transport: sse

AI Client Configuration

Claude Desktop (claude_desktop_config.json):

{
  "mcpServers": {
    "mcp-db-server": {
      "type": "sse",
      "url": "http://localhost:8088/sse"
    }
  }
}

Cursor (settings):

{
  "mcpServers": {
    "mcp-db-server": {
      "transport": "sse",
      "url": "http://localhost:8088/sse"
    }
  }
}

MCP Tools API

All tools require connection parameters on every invocation. No credentials are stored server-side.

Common Connection Parameters

Every tool accepts these parameters:

Parameter	Type	Required	Description
type	String	Yes	Database type: mysql, postgresql, h2, sqlite, sqlserver, oracle
host	String	Yes	Database host (use "localhost" for local)
port	int	Yes	Port number (0 = use default for type)
database	String	Yes	Database/schema name
username	String	Yes	Database username
password	String	Yes	Database password

Tool: listTables

Lists all tables in the database.

Additional Parameters:

• schema (String, optional): Schema name filter

Example AI Request:

"Show me all tables in my local MySQL database 'myapp'"

→ Tool call:
  type: "mysql"
  host: "localhost"
  port: 3306
  database: "myapp"
  username: "root"
  password: "${DB_PASSWORD}"

Response Format:

[
  {"tableName": "users", "tableType": "TABLE"},
  {"tableName": "orders", "tableType": "TABLE"},
  {"tableName": "products", "tableType": "TABLE"}
]

Tool: describeTable

Gets column information for a specific table.

Additional Parameters:

• table (String, required): Table name
• schema (String, optional): Schema name

Example AI Request:

"What columns does the users table have?"

→ Tool call:
  type: "mysql"
  host: "localhost"
  port: 3306
  database: "myapp"
  username: "root"
  password: "${DB_PASSWORD}"
  table: "users"

Response Format:

[
  {
    "columnName": "id",
    "typeName": "INT",
    "columnSize": 11,
    "nullable": "NO",
    "autoIncrement": true,
    "primaryKey": true
  },
  {
    "columnName": "email",
    "typeName": "VARCHAR",
    "columnSize": 255,
    "nullable": "NO",
    "autoIncrement": false,
    "primaryKey": false
  }
]

Tool: listIndexes

Gets index information for a table.

Additional Parameters:

• table (String, required): Table name
• schema (String, optional): Schema name

Example AI Request:

"Show indexes on the orders table"

→ Tool call:
  type: "postgresql"
  host: "db.example.com"
  port: 5432
  database: "production"
  username: "reader"
  password: "${DB_PASSWORD}"
  table: "orders"

Tool: executeQuery

Executes read-only SQL (SELECT, SHOW, DESCRIBE, EXPLAIN).

Additional Parameters:

• sql (String, required): SQL query
• limit (int, optional): Max rows to return (default: 100)

Example AI Request:

"Get the 5 most recent orders"

→ Tool call:
  type: "mysql"
  host: "localhost"
  port: 3306
  database: "myapp"
  username: "root"
  password: "${DB_PASSWORD}"
  sql: "SELECT * FROM orders ORDER BY created_at DESC"
  limit: 5

Response Format:

{
  "columns": ["id", "user_id", "total", "created_at"],
  "rows": [
    [1523, 42, 129.99, "2026-06-22 10:30:00"],
    [1522, 38, 79.50, "2026-06-22 09:15:00"]
  ],
  "rowCount": 2,
  "limited": false
}

Tool: executeUpdate

Executes write operations (INSERT, UPDATE, DELETE, DDL).

Additional Parameters:

• sql (String, required): SQL statement

Example AI Request:

"Create a new table for product reviews"

→ Tool call:
  type: "mysql"
  host: "localhost"
  port: 3306
  database: "myapp"
  username: "admin"
  password: "${DB_PASSWORD}"
  sql: "CREATE TABLE reviews (id INT PRIMARY KEY AUTO_INCREMENT, product_id INT, rating INT, comment TEXT)"

Response Format:

{
  "affectedRows": 0,
  "message": "DDL executed successfully"
}

Tool: getDatabaseInfo

Gets database metadata (version, driver, capabilities).

Example AI Request:

"What version of PostgreSQL am I connected to?"

→ Tool call:
  type: "postgresql"
  host: "localhost"
  port: 5432
  database: "myapp"
  username: "postgres"
  password: "${DB_PASSWORD}"

Response Format:

{
  "databaseProductName": "PostgreSQL",
  "databaseProductVersion": "14.2",
  "driverName": "PostgreSQL JDBC Driver",
  "driverVersion": "42.3.3",
  "maxConnections": 100,
  "supportsTransactions": true
}

Code Examples

Java: Adding Custom Tool (Extending DatabaseTools)

package com.mcp.db.tool;

import org.springframework.ai.mcp.server.McpServer;
import org.springframework.stereotype.Component;
import java.sql.Connection;
import java.sql.PreparedStatement;
import java.sql.ResultSet;

@Component
public class DatabaseTools {
    
    private final ConnectionFactory connectionFactory;
    
    public DatabaseTools(ConnectionFactory connectionFactory) {
        this.connectionFactory = connectionFactory;
    }
    
    // New custom tool: count rows in a table
    @McpServer.Tool(description = "Count total rows in a table")
    public long countRows(
        String type, String host, int port, String database,
        String username, String password,
        String table
    ) throws Exception {
        
        try (Connection conn = connectionFactory.getConnection(
                type, host, port, database, username, password)) {
            
            String sql = "SELECT COUNT(*) FROM " + table;
            try (PreparedStatement stmt = conn.prepareStatement(sql);
                 ResultSet rs = stmt.executeQuery()) {
                
                if (rs.next()) {
                    return rs.getLong();
                }
                 ;
            }
        }
    }
}

Java: Custom Connection Pool Configuration

package com.mcp.db.config;

import com.zaxxer.hikari.HikariConfig;
import com.zaxxer.hikari.HikariDataSource;
import org.springframework.stereotype.Component;

@Component
public class ConnectionFactory {
    
    private HikariDataSource createConnectionPool(
        String jdbcUrl, String username, String password
    ) {
        HikariConfig config = new HikariConfig();
        config.setJdbcUrl(jdbcUrl);
        config.setUsername(username);
        config.setPassword(password);
        
        // Custom pool settings
        config.setMaximumPoolSize(10);
        config.setMinimumIdle(2);
        config.setConnectionTimeout(30000);
        config.setIdleTimeout(300000); // 5 minutes
        config.setMaxLifetime(600000);  // 10 minutes
        
        // Performance tuning
        config.setConnectionTestQuery("SELECT 1");
        config.setPoolName("MCP-DB-Pool");
        
        return new HikariDataSource(config);
    }
}

Python: Client-Side MCP Interaction

import requests
import json

# SSE endpoint
MCP_URL = "http://localhost:8088/sse"

# Database connection parameters
db_params = {
    "type": "mysql",
    "host": "localhost",
    "port": 3306,
    "database": "myapp",
    "username": "root",
    "password": os.environ["DB_PASSWORD"]
}

# Call listTables tool
def list_tables():
    payload = {
        "jsonrpc": "2.0",
        "method": "tools/call",
        "params": {
            "name": "listTables",
            "arguments": db_params
        },
        "id": 1
    }
    
    response = requests.post(MCP_URL, json=payload)
    return response.json()

# Call executeQuery tool
def run_query(sql, limit=100):
    payload = {
        "jsonrpc": "2.0",
        "method": "tools/call",
        "params": {
            "name": "executeQuery",
            "arguments": {
                **db_params,
                "sql": sql,
                "limit": limit
            }
        },
        "id": 
    }
    
    response = requests.post(MCP_URL, json=payload)
     response.json()


tables = list_tables()
()

results = run_query(, limit=)
()

Common Patterns

Pattern 1: Database Schema Exploration

User: "I need to understand the structure of my e-commerce database"

AI workflow:
1. Call listTables with connection params
2. For each table, call describeTable
3. Call listIndexes to check optimization
4. Present schema overview to user

Pattern 2: Data Analysis Query

User: "Show me sales trends from last month"

AI workflow:
1. Call getDatabaseInfo to verify database type
2. Craft appropriate SQL for date functions
3. Call executeQuery with generated SQL
4. Format and present results

Pattern 3: Multi-Database Comparison

User: "Compare user counts between dev and prod databases"

AI workflow:
1. Call executeQuery on dev DB: "SELECT COUNT(*) FROM users"
2. Call executeQuery on prod DB: "SELECT COUNT(*) FROM users"
3. Compare results and report differences

Pattern 4: Safe Schema Migration

User: "Add an email_verified column to users table"

AI workflow:
1. Call describeTable to check current schema
2. Verify column doesn't exist
3. Call executeUpdate with ALTER TABLE statement
4. Call describeTable again to confirm change

Troubleshooting

Connection Pool Issues

Symptom: "Connection pool exhausted" errors

Solution:

# Edit application.yml or pass as Java system properties
hikari:
  maximum-pool-size: 20  # Increase max connections
  connection-timeout: 60000  # 60 seconds

Database Driver Not Found

Symptom: ClassNotFoundException: com.mysql.cj.jdbc.Driver

Solution: Add driver dependency to pom.xml:

<dependency>
    <groupId>com.mysql</groupId>
    <artifactId>mysql-connector-j</artifactId>
    <version>8.0.33</version>
</dependency>

SSL/TLS Connection Errors (PostgreSQL)

Symptom: "The server does not support SSL"

Fix: Modify connection URL in ConnectionFactory.java:

if (type.equals("postgresql")) {
    return String.format("jdbc:postgresql://%s:%d/%s?sslmode=disable",
        host, port, database);
}

Memory Leaks from Cached Connections

Symptom: Server memory grows over time

Check: Connection pool TTL is configured (default 5 minutes):

// In ConnectionFactory.java
private static final long CACHE_TTL_MILLIS = 300_000; // 5 minutes

AI Can't Access Database

Symptom: Tools are available but calls fail with authentication errors

Checklist:

1. Verify database is accessible from server host: telnet db_host db_port
2. Check user has required permissions: GRANT SELECT ON database.* TO 'user'@'%';
3. Verify firewall allows connections on database port
4. Test connection manually with JDBC URL

Oracle-Specific Connection Issues

Symptom: "Listener refused the connection"

Solution: Use correct Oracle JDBC URL format:

// For SID
jdbc:oracle:thin:@hostname:1521:SID

// For Service Name
jdbc:oracle:thin:@//hostname:1521/servicename

Security Best Practices

1. Never hardcode credentials — Always use environment variables:

   export DB_PASSWORD="your_password"
   

2. Use read-only accounts for query-only operations:

   CREATE USER 'readonly'@'%' IDENTIFIED BY 'password';
   GRANT SELECT ON database.* TO 'readonly'@'%';
   

3. Network isolation — Deploy server in same VPC as databases:

   # docker-compose.yml
   services:
     mcp-db-server:
       networks:
         - internal
     mysql:
       networks:
         - internal
   

4. Connection pool limits — Prevent resource exhaustion:

   config.setMaximumPoolSize(10);  // Per unique connection
   

Development & Extension

Adding a New Database Type

1. Update ConnectionFactory.java:

private static final Map<String, Integer> DEFAULT_PORTS = Map.of(
    // ... existing entries
    "mongodb", 27017  // Add new type
);

private static final Map<String, String> DRIVER_CLASSES = Map.of(
    // ... existing entries
    "mongodb", "com.mongodb.jdbc.MongoDriver"
);

private String buildJdbcUrl(String type, String host, int port, String database) {
    return switch (type) {
        // ... existing cases
        case "mongodb" -> String.format("jdbc:mongodb://%s:%d/%s", host, port, database);
        default -> throw new IllegalArgumentException("Unsupported type: " + type);
    };
}

2. Add driver dependency:

<dependency>
    <groupId>org.mongodb</groupId>
    <artifactId>mongodb-jdbc</artifactId>
    <version>2.0.0</version>
</dependency>

3. Test with new database type:

./mvnw test -Dtest=DatabaseToolsTest#testMongoDBConnection

---

Project: PerfectXM/mcp-db-server
License: MIT
Java Version: 17+
Spring Boot: 3.4.13
MCP Version: 1.1.7