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

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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