Multi Database MCP Server

A powerful multi-database server implementing the Model Context Protocol (MCP) to provide AI assistants with structured access to databases.

Overview • Core Concepts • Features • Quick Start • Running • Configuration • Tools • Examples • Troubleshooting • Contributing

What is DB MCP Server?

The DB MCP Server provides a standardized way for AI models to interact with multiple databases simultaneously. Built on the FreePeak/cortex framework, it enables AI assistants to execute SQL queries, manage transactions, explore schemas, and analyze performance across different database systems through a unified interface.

Core Concepts

Multi-Database Support

Unlike traditional database connectors, DB MCP Server can connect to and interact with multiple databases concurrently:

{
  "connections": [
    {
      "id": "mysql1",
      "type": "mysql",
      "host": "localhost",
      "port": 3306,
      "name": "db1",
      "user": "user1",
      "password": "password1"
    },
    {
      "id": "postgres1",
      "type": "postgres",
      "host": "localhost",
      "port": 5432,
      "name": "db2",
      "user": "user2",
      "password": "password2"
    }
  ]
}

Dynamic Tool Generation

For each connected database, the server automatically generates a set of specialized tools:

// For a database with ID "mysql1", these tools are generated:
query_mysql1       // Execute SQL queries
execute_mysql1     // Run data modification statements
transaction_mysql1 // Manage transactions
schema_mysql1      // Explore database schema
performance_mysql1 // Analyze query performance

Clean Architecture

The server follows Clean Architecture principles with these layers:

Domain Layer: Core business entities and interfaces
Repository Layer: Data access implementations
Use Case Layer: Application business logic
Delivery Layer: External interfaces (MCP tools)

Features

Simultaneous Multi-Database Support: Connect to and interact with multiple MySQL and PostgreSQL databases concurrently
Database-Specific Tool Generation: Auto-creates specialized tools for each connected database
Clean Architecture: Modular design with clear separation of concerns
OpenAI Agents SDK Compatibility: Full compatibility with the OpenAI Agents SDK for seamless integration with AI assistants
Dynamic Database Tools:
- Execute SQL queries with parameters
- Run data modification statements with proper error handling
- Manage database transactions across sessions
- Explore database schemas and relationships
- Analyze query performance and receive optimization suggestions
Unified Interface: Consistent interaction patterns across different database types
Connection Management: Simple configuration for multiple database connections

Currently Supported Databases

Database	Status	Features
MySQL	✅ Full Support	Queries, Transactions, Schema Analysis, Performance Insights
PostgreSQL	✅ Full Support	Queries, Transactions, Schema Analysis, Performance Insights

Quick Start

Using Docker

The quickest way to get started is with Docker:

# Pull the latest image
docker pull freepeak/db-mcp-server:latest

# Option 1: Run with environment variables (recommended)
docker run -p 9092:9092 \
  -v $(pwd)/config.json:/app/my-config.json \
  -e TRANSPORT_MODE=sse \
  -e CONFIG_PATH=/app/my-config.json \
  freepeak/db-mcp-server

# Option 2: Override the entrypoint
docker run -p 9092:9092 \
  -v $(pwd)/config.json:/app/my-config.json \
  --entrypoint /app/server \
  freepeak/db-mcp-server \
  -t sse -c /app/my-config.json

# Option 3: Use shell to execute the command
docker run -p 9092:9092 \
  -v $(pwd)/config.json:/app/my-config.json \
  freepeak/db-mcp-server \
  /bin/sh -c "/app/server -t sse -c /app/my-config.json"

Note: We mount to /app/my-config.json because the container already has a file at /app/config.json. If you encounter platform mismatch warnings, you can specify the platform: --platform linux/amd64 or --platform linux/arm64.

From Source

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

# Build the server
make build

# Run the server in SSE mode
./server -t sse -c config.json

Running the Server

The server supports multiple transport modes to fit different use cases:

STDIO Mode (for IDE integration)

Ideal for integration with AI coding assistants:

# Run the server in STDIO mode
./server -t stdio -c config.json

Output will be sent as JSON-RPC messages to stdout, while logs go to stderr.

For Cursor integration, add this to your .cursor/mcp.json:

{
    "mcpServers": {
        "stdio-db-mcp-server": {
            "command": "/path/to/db-mcp-server/server",
            "args": [
                "-t", "stdio",
                "-c", "/path/to/config.json"
            ]
        }
    }
}

SSE Mode (Server-Sent Events)

For web-based applications and services:

# Run with default host (localhost) and port (9092)
./server -t sse -c config.json

# Specify a custom host and port
./server -t sse -host 0.0.0.0 -port 8080 -c config.json

Connect your client to http://localhost:9092/sse for the event stream.

Docker Compose

For development environments with database containers:

# docker-compose.yml
version: '3'
services:
  db-mcp-server:
    image: freepeak/db-mcp-server:latest
    ports:
      - "9092:9092"
    volumes:
      - ./config.json:/app/my-config.json
    environment:
      - TRANSPORT_MODE=sse
      - CONFIG_PATH=/app/my-config.json
    # Alternative using entrypoint
    # entrypoint: ["/app/server"]
    # command: ["-t", "sse", "-c", "/app/my-config.json"]
    depends_on:
      - mysql
      - postgres
  
  mysql:
    image: mysql:8
    environment:
      MYSQL_ROOT_PASSWORD: rootpassword
      MYSQL_DATABASE: testdb
      MYSQL_USER: user
      MYSQL_PASSWORD: password
    ports:
      - "3306:3306"
  
  postgres:
    image: postgres:14
    environment:
      POSTGRES_DB: testdb
      POSTGRES_USER: user
      POSTGRES_PASSWORD: password
    ports:
      - "5432:5432"

Configuration

Database Configuration

Create a config.json file with your database connections:

{
  "connections": [
    {
      "id": "mysql1",
      "type": "mysql",
      "host": "localhost",
      "port": 3306,
      "name": "db1",
      "user": "user1",
      "password": "password1"
    },
    {
      "id": "postgres1",
      "type": "postgres",
      "host": "localhost",
      "port": 5432,
      "name": "db2",
      "user": "user2",
      "password": "password2"
    }
  ]
}

Command-Line Options

The server supports various command-line options:

# Basic options
./server -t <transport> -c <config-file>

# Available transports: stdio, sse
# For SSE transport, additional options:
./server -t sse -host <hostname> -port <port> -c <config-file>

# Direct database configuration:
./server -t stdio -db-config '{"connections":[...]}'

# Environment variable configuration:
export DB_CONFIG='{"connections":[...]}'
./server -t stdio

Available Tools

For each connected database (e.g., "mysql1", "mysql2"), the server creates:

Tool Naming Convention

The server automatically generates tools with names following this format:

<tool_type>_<database_id>

Where:

<tool_type>: One of: query, execute, transaction, schema, performance
<database_id>: The ID of the database as defined in your configuration

Example tool names for a database with ID "mysql1":

query_mysql1
execute_mysql1
transaction_mysql1
schema_mysql1
performance_mysql1

Database-Specific Tools

query_<dbid>: Execute SQL queries on the specified database

{
  "query": "SELECT * FROM users WHERE age > ?",
  "params": [30]
}

execute_<dbid>: Execute SQL statements (INSERT, UPDATE, DELETE)

{
  "statement": "INSERT INTO users (name, email) VALUES (?, ?)",
  "params": ["John Doe", "[email protected]"]
}

transaction_<dbid>: Manage database transactions

// Begin transaction
{
  "action": "begin",
  "readOnly": false
}

// Execute within transaction
{
  "action": "execute",
  "transactionId": "<from begin response>",
  "statement": "UPDATE users SET active = ? WHERE id = ?",
  "params": [true, 42]
}

// Commit transaction
{
  "action": "commit",
  "transactionId": "<from begin response>"
}

schema_<dbid>: Get database schema information
```
{
  "random_string": "dummy"
}
```

performance_<dbid>: Analyze query performance

{
  "action": "analyzeQuery",
  "query": "SELECT * FROM users WHERE name LIKE ?"
}

Global Tools

list_databases: List all configured database connections
```
{}
```

Examples

Querying Multiple Databases

// Query the first database
{
  "name": "query_mysql1",
  "parameters": {
    "query": "SELECT * FROM users LIMIT 5"
  }
}

// Query the second database
{
  "name": "query_mysql2",
  "parameters": {
    "query": "SELECT * FROM products LIMIT 5"
  }
}

Executing Transactions

// Begin transaction
{
  "name": "transaction_mysql1",
  "parameters": {
    "action": "begin"
  }
}
// Response contains transactionId

// Execute within transaction
{
  "name": "transaction_mysql1",
  "parameters": {
    "action": "execute",
    "transactionId": "tx_12345",
    "statement": "INSERT INTO orders (user_id, product_id) VALUES (?, ?)",
    "params": [1, 2]
  }
}

// Commit transaction
{
  "name": "transaction_mysql1",
  "parameters": {
    "action": "commit",
    "transactionId": "tx_12345"
  }
}

Roadmap

We're committed to expanding DB MCP Server to support a wide range of database systems:

Q3 2025

MongoDB - Support for document-oriented database operations
SQLite - Lightweight embedded database integration
MariaDB - Complete feature parity with MySQL implementation

Q4 2025

Microsoft SQL Server - Enterprise database support with T-SQL capabilities
Oracle Database - Enterprise-grade integration
Redis - Key-value store operations

2026

Cassandra - Distributed NoSQL database support
Elasticsearch - Specialized search and analytics capabilities
CockroachDB - Distributed SQL database for global-scale applications
DynamoDB - AWS-native NoSQL database integration
Neo4j - Graph database support
ClickHouse - Analytics database support

Troubleshooting

Common Issues

Connection Errors: Verify your database connection settings in config.json
Tool Not Found: Ensure the server is running and check tool name prefixes
Failed Queries: Check your SQL syntax and database permissions
Docker Volume Mount Errors: If you see errors like mountpoint for /app/config.json: not a directory, it's because the container already has a file at that path. Mount to a different path (e.g., /app/my-config.json) and update your configuration accordingly.
Docker Command Errors: If you encounter command-related errors with Docker, use one of these approaches:
- Use environment variables: -e TRANSPORT_MODE=sse -e CONFIG_PATH=/app/my-config.json
- Override the entrypoint: --entrypoint /app/server freepeak/db-mcp-server -t sse -c /app/my-config.json
- Use shell execution: freepeak/db-mcp-server /bin/sh -c "/app/server -t sse -c /app/my-config.json"

Logs

The server writes logs to:

STDIO mode: stderr
SSE mode: stdout and ./logs/db-mcp-server.log

Enable debug logging with the -debug flag:

./server -t sse -debug -c config.json

Contributing

Contributions are welcome! Here's how you can help:

Fork the repository
Create a feature branch: git checkout -b new-feature
Commit your changes: git commit -am 'Add new feature'
Push to the branch: git push origin new-feature
Submit a pull request

Please ensure your code follows our coding standards and includes appropriate tests.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Support & Contact

For questions or issues, email [email protected]
Open an issue directly: Issue Tracker
If DB MCP Server helps your work, please consider supporting:

Cursor Integration

Tool Naming Convention

The MCP server registers tools with names that match the format Cursor expects. The tool names follow this format:

mcp_<servername>_<tooltype>_<dbID>

For example: mcp_mysql1_db_mcp_server_stdio_schema_mysql1_db

The server uses the name mysql1_db_mcp_server_stdio by default, which should match your Cursor configuration in the mcp.json file.

Cursor Configuration

In your Cursor configuration (~/.cursor/mcp.json), you should have a configuration like:

{
    "mcpServers": {
        "multidb": {
            "command": "/path/to/db-mcp-server/server",
            "args": [
                "-t",
                "stdio",
                "-c",
                "/path/to/database_config.json"
            ]
        }
    }
}

The server will automatically register tools with simple names that match the database identifiers in your configuration.

Using MCP Tools in Cursor

Once your DB MCP Server is running and properly configured in Cursor, you can use the MCP tools in your AI assistant conversations. The tools follow this naming pattern:

mcp_<server_name>_<tool_type>_<database_id>

Where:

<server_name> is the name defined in your .cursor/mcp.json (e.g., "multidb")
<tool_type> is one of: query, execute, transaction, schema, performance, list_databases
<database_id> is the database ID from your configuration (not needed for list_databases)

Examples:

For a server named "multidb" with a database ID "mysql1":

Listing all databases:

mcp_multidb_list_databases

Querying the database:

mcp_multidb_query_mysql1
Query: SELECT * FROM users LIMIT 10

Viewing database schema:

mcp_multidb_schema_mysql1

Executing statements:

mcp_multidb_execute_mysql1
Statement: INSERT INTO users (name, email) VALUES ('John Doe', '[email protected]')

Managing transactions:

mcp_multidb_transaction_mysql1
Action: begin

Troubleshooting MCP Tools in Cursor

If the AI assistant can't call the MCP tools:

Make sure the server is running (check with ps aux | grep server)
Verify your .cursor/mcp.json configuration is correct
Ensure the server_name in .env matches what's in your MCP tool calls
Restart Cursor after making configuration changes
Check the logs in the logs/ directory for any errors

OpenAI Agents SDK Integration

The DB MCP Server fully supports OpenAI's Agents SDK, allowing you to create AI agents that can interact with databases directly.

Prerequisites

OpenAI account with API access
OpenAI Agents SDK installed: pip install openai-agents
A running DB MCP Server instance (SSE mode)

Basic Integration Example

Here's how to integrate the DB MCP Server with an OpenAI Agent:

from openai import OpenAI
from agents.agent import Agent, ModelSettings
from agents.tools.mcp_server import MCPServerSse, MCPServerSseParams

# Connect to the MCP server
db_server = MCPServerSse(
    params=MCPServerSseParams(
        url="http://localhost:9095/sse",  # URL to your running DB MCP server
        schema={
            "params": {
                "type": "array", 
                "items": {
                    "type": "object",
                    "properties": {
                        "name": {"type": "string"},
                        "description": {"type": "string"},
                        "parameters": {"type": "object"}
                    }
                }
            }
        }
    ),
)

# Create the agent with access to database tools
agent = Agent(
    name="Database Agent",
    model="gpt-4o",
    model_settings=ModelSettings(temperature=0.1),
    instructions="""
    You are a database helper agent. You can execute SQL queries,
    manage database transactions, and explore schema information.
    """,
    mcp_servers=[db_server],
)

# Now the agent can be used to interact with your databases through the OpenAI API

Testing Your Integration

The repository includes a test script to verify compatibility with the OpenAI Agents SDK:

# Run the test script
./test_tools/openai-agent-sdk-test/run_test.sh

The script will:

Build the server with the latest changes
Start the server if it's not already running
Test the connection with the OpenAI Agents SDK
Report if the integration is working correctly

Troubleshooting Agents SDK Integration

If you encounter issues:

Ensure the server is running in SSE mode on the expected port
Check that your OpenAI API key is set as an environment variable
Verify that your agent's instructions mention the database tools specifically
Inspect the server logs for any error messages

Name		Name	Last commit message	Last commit date
Latest commit History 102 Commits
.cursor		.cursor
.github		.github
assets		assets
cmd/server		cmd/server
docs		docs
internal		internal
pkg		pkg
.DS_Store		.DS_Store
.dockerignore		.dockerignore
.env.example		.env.example
.gitignore		.gitignore
.golangci.yml		.golangci.yml
CHANGELOG.md		CHANGELOG.md
Dockerfile		Dockerfile
LICENSE		LICENSE
Makefile		Makefile
README-old.md		README-old.md
README.md		README.md
config.json		config.json
coverage.out		coverage.out
docker-compose.test.yml		docker-compose.test.yml
docker-compose.yml		docker-compose.yml
glama.json		glama.json
go.mod		go.mod
go.sum		go.sum
llms-full.txt		llms-full.txt
repomix-output.txt		repomix-output.txt
request.json		request.json
server		server
server-linux		server-linux
start-mcp.sh		start-mcp.sh
test.Dockerfile		test.Dockerfile
wait-for-it.sh		wait-for-it.sh

License

FreePeak/db-mcp-server

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Multi Database MCP Server

A powerful multi-database server implementing the Model Context Protocol (MCP) to provide AI assistants with structured access to databases.

What is DB MCP Server?

Core Concepts

Multi-Database Support

Dynamic Tool Generation

Clean Architecture

Features

Currently Supported Databases

Quick Start

Using Docker

From Source

Running the Server

STDIO Mode (for IDE integration)

SSE Mode (Server-Sent Events)

Docker Compose

Configuration

Database Configuration

Command-Line Options

Available Tools

Tool Naming Convention

Database-Specific Tools

Global Tools

Examples

Querying Multiple Databases

Executing Transactions

Roadmap

Q3 2025

Q4 2025

2026

Troubleshooting

Common Issues

Logs

Contributing

License

Support & Contact

Cursor Integration

Tool Naming Convention

Cursor Configuration

Using MCP Tools in Cursor

Examples:

Troubleshooting MCP Tools in Cursor

OpenAI Agents SDK Integration

Prerequisites

Basic Integration Example

Testing Your Integration

Troubleshooting Agents SDK Integration

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