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

What is FreePeak db mcp server

Multi Database MCP Server

*License: MIT* *Go Report Card* *Go Reference* *Contributors*

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:

  1. Domain Layer: Core business entities and interfaces
  2. Repository Layer: Data access implementations
  3. Use Case Layer: Application business logic
  4. 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": {
      ```json
      "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:

  1. Fork the repository
  2. Create a feature branch (git checkout -b feature/amazing-feature)
  3. Commit your changes (git commit -m 'feat: add amazing feature')
  4. Push to the branch (git push origin feature/amazing-feature)
  5. 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.

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Frequently Asked Questions

What is MCP?

MCP (Model Context Protocol) is an open protocol that standardizes how applications provide context to LLMs. Think of MCP like a USB-C port for AI applications, providing a standardized way to connect AI models to different data sources and tools.

What are MCP Servers?

MCP Servers are lightweight programs that expose specific capabilities through the standardized Model Context Protocol. They act as bridges between LLMs like Claude and various data sources or services, allowing secure access to files, databases, APIs, and other resources.

How do MCP Servers work?

MCP Servers follow a client-server architecture where a host application (like Claude Desktop) connects to multiple servers. Each server provides specific functionality through standardized endpoints and protocols, enabling Claude to access data and perform actions through the standardized protocol.

Are MCP Servers secure?

Yes, MCP Servers are designed with security in mind. They run locally with explicit configuration and permissions, require user approval for actions, and include built-in security features to prevent unauthorized access and ensure data privacy.

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