Multi Database MCP Server

Overview

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 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 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 for seamless AI assistant integration
Dynamic Database Tools: Execute queries, run statements, manage transactions, explore schemas, analyze performance
Unified Interface: Consistent interaction patterns across different database types
Connection Management: Simple configuration for multiple database connections

Supported Databases

Database	Status	Features
MySQL	✅ Full Support	Queries, Transactions, Schema Analysis, Performance Insights
PostgreSQL	✅ Full Support (v9.6-17)	Queries, Transactions, Schema Analysis, Performance Insights
TimescaleDB	✅ Full Support	Hypertables, Time-Series Queries, Continuous Aggregates, Compression, Retention Policies

Deployment Options

The DB MCP Server can be deployed in multiple ways to suit different environments and integration needs:

Docker Deployment

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

# Run with mounted config file
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

Note: Mount to /app/my-config.json as the container has a default file at /app/config.json.

STDIO Mode (IDE Integration)

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

For Cursor IDE integration, add to .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)

# Default configuration (localhost:9092)
./bin/server -t sse -c config.json

# Custom host and port
./bin/server -t sse -host 0.0.0.0 -port 8080 -c config.json

Client connection endpoint: http://localhost:9092/sse

Source Code Installation

# 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
./bin/server -t sse -c config.json

Configuration

Database Configuration File

Create a config.json file with your database connections:

{
  "connections": [
    {
      "id": "mysql1",
      "type": "mysql",
      "host": "mysql1",
      "port": 3306,
      "name": "db1",
      "user": "user1",
      "password": "password1",
      "query_timeout": 60,
      "max_open_conns": 20,
      "max_idle_conns": 5,
      "conn_max_lifetime_seconds": 300,
      "conn_max_idle_time_seconds": 60
    },
    {
      "id": "postgres1",
      "type": "postgres",
      "host": "postgres1",
      "port": 5432,
      "name": "db1",
      "user": "user1",
      "password": "password1"
    }
  ]
}

Command-Line Options

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

# SSE transport options
./bin/server -t sse -host <hostname> -port <port> -c <config-file>

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

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

Available Tools

For each connected database, DB MCP Server automatically generates these specialized tools:

Query Tools

Tool Name	Description
`query_<db_id>`	Execute SELECT queries and get results as a tabular dataset
`execute_<db_id>`	Run data manipulation statements (INSERT, UPDATE, DELETE)
`transaction_<db_id>`	Begin, commit, and rollback transactions

Schema Tools

Tool Name	Description
`schema_<db_id>`	Get information about tables, columns, indexes, and foreign keys
`generate_schema_<db_id>`	Generate SQL or code from database schema

Performance Tools

Tool Name	Description
`performance_<db_id>`	Analyze query performance and get optimization suggestions

TimescaleDB Tools

For PostgreSQL databases with TimescaleDB extension, these additional specialized tools are available:

Tool Name	Description
`timescaledb_<db_id>`	Perform general TimescaleDB operations
`create_hypertable_<db_id>`	Convert a standard table to a TimescaleDB hypertable
`list_hypertables_<db_id>`	List all hypertables in the database
`time_series_query_<db_id>`	Execute optimized time-series queries with bucketing
`time_series_analyze_<db_id>`	Analyze time-series data patterns
`continuous_aggregate_<db_id>`	Create materialized views that automatically update
`refresh_continuous_aggregate_<db_id>`	Manually refresh continuous aggregates

For detailed documentation on TimescaleDB tools, see TIMESCALEDB_TOOLS.md.

Examples

Querying Multiple Databases

-- Query the first database
query_mysql1("SELECT * FROM users LIMIT 10")

-- Query the second database in the same context
query_postgres1("SELECT * FROM products WHERE price > 100")

Managing Transactions

-- Start a transaction
transaction_mysql1("BEGIN")

-- Execute statements within the transaction
execute_mysql1("INSERT INTO orders (customer_id, product_id) VALUES (1, 2)")
execute_mysql1("UPDATE inventory SET stock = stock - 1 WHERE product_id = 2")

-- Commit or rollback
transaction_mysql1("COMMIT")
-- OR
transaction_mysql1("ROLLBACK")

Exploring Database Schema

-- Get all tables in the database
schema_mysql1("tables")

-- Get columns for a specific table
schema_mysql1("columns", "users")

-- Get constraints
schema_mysql1("constraints", "orders")

Troubleshooting

Common Issues

Connection Failures: Verify network connectivity and database credentials
Permission Errors: Ensure the database user has appropriate permissions
Timeout Issues: Check the query_timeout setting in your configuration

Logs

Enable verbose logging for troubleshooting:

./bin/server -t sse -c config.json -v

Contributing

We welcome contributions to the DB MCP Server project! To contribute:

Fork the repository
Create a feature branch (git checkout -b feature/amazing-feature)
Commit your changes (git commit -m 'feat: add amazing feature')
Push to the branch (git push origin feature/amazing-feature)
Open a Pull Request

Please see our CONTRIBUTING.md file for detailed guidelines.

License

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

This server cannot be installed

security - not tested

license - permissive license

quality - not tested

How are these scores calculated?

hybrid server

The server is able to function both locally and remotely, depending on the configuration or use case.

The Multi DB MCP Server is a high-performance implementation of the Database Model Context Protocol designed to revolutionize how AI agents interact with databases. Currently supporting MySQL and PostgreSQL databases.

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