General Purpose Database Server

A Model Context Protocol (MCP) server that provides LLMs with generic database access capabilities for PostgreSQL databases. Built with Python and FastMCP.

Features

• Query Tools: Execute SELECT queries, write operations (INSERT/UPDATE/DELETE), and export data
• Schema Management: Create, alter, and drop tables, list tables, describe table schemas
• Insights: Store and retrieve business insights in a dedicated memo table
• Connection Pooling: Efficient database connection management
• Docker Support: Easy containerized deployment
• Flexible Configuration: Support for DATABASE_URL or individual connection parameters
• Multiple Transport Modes: stdio (local) or SSE (HTTP for remote deployment)

Installation

Local Development

1. Clone or navigate to the repository:

cd general-database-mcp-python

2. Create a virtual environment:

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install dependencies:

pip install -r requirements.txt

4. Configure environment variables:

cp .env.example .env
# Edit .env with your database credentials

5. Run the server:

python main.py

Docker Deployment

1. Build the Docker image:

docker build -t general-database-mcp .

2. Run the container:

docker run -p 8008:8008 \
  -e DATABASE_URL="postgresql://user:password@host:5432/database" \
  -e MCP_TRANSPORT=http \
  general-database-mcp

Configuration

Environment Variables

Database Configuration (choose one option):

Option 1: DATABASE_URL (recommended)

DATABASE_URL=postgresql://user:password@host:5432/database

Option 2: Individual parameters

DB_HOST=localhost
DB_PORT=5432
DB_NAME=your_database
DB_USER=your_username
DB_PASSWORD=your_password

Server Configuration:

PORT=8008
MCP_TRANSPORT=stdio  # Options: stdio (local) or http (remote)
API_KEY=your_secret_key  # Optional: for authentication

Available Tools

Query Tools

read_query

Execute SELECT queries to read data from the database.

• Parameters: query (string) - SQL SELECT statement
• Returns: Query results as JSON

write_query

Execute INSERT, UPDATE, or DELETE queries to modify data.

• Parameters: query (string) - SQL modification statement
• Returns: Number of affected rows

export_query

Execute a SELECT query and export results in CSV or JSON format.

• Parameters:
  • query (string) - SQL SELECT statement
  • format (string) - "csv" or "json" (default: "json")
• Returns: Formatted query results

Schema Management Tools

create_table

Create new tables in the database.

• Parameters: query (string) - CREATE TABLE statement
• Returns: Success status

alter_table

Modify existing table schema (add columns, rename, etc.).

• Parameters: query (string) - ALTER TABLE statement
• Returns: Success status

drop_table

Remove a table from the database with safety confirmation.

• Parameters:
  • table_name (string) - Name of table to drop
  • confirm (boolean) - Must be True to proceed
• Returns: Success status

list_tables

Get a list of all tables in the database.

• Parameters: None
• Returns: Array of table names

describe_table

View schema information for a specific table.

• Parameters: table_name (string) - Name of table
• Returns: Column definitions with types, constraints, etc.

Insights Tools

append_insight

Add a business insight to the memo table.

• Parameters: insight (string) - Text of the insight
• Returns: Success status

list_insights

List all business insights stored in the memo table.

• Parameters: None
• Returns: Array of insights with timestamps

Monitoring

health_check

Health check endpoint for monitoring and deployment verification.

• Parameters: None
• Returns: Server status and database connection info

Usage Examples

Using with Claude Desktop

Add to your Claude Desktop configuration file:

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json Windows: %APPDATA%\Claude\claude_desktop_config.json Linux: ~/.config/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "database": {
      "command": "python",
      "args": [
        "/absolute/path/to/general-database-mcp-python/main.py"
      ],
      "env": {
        "DATABASE_URL": "postgresql://user:password@localhost:5432/mydb"
      }
    }
  }
}

Example Prompts for Claude

Query data:

Show me all tables in the database.
Describe the structure of the users table.
Select all records from the products table where price > 100.

Modify data:

Insert a new user with name 'John Doe' and email '[email protected]'.
Update all products in the 'Electronics' category to increase price by 10%.
Delete all orders older than 2 years.

Schema operations:

Create a new table called 'logs' with columns for id, timestamp, and message.
Add a 'created_at' column to the users table.
Drop the temporary_data table (confirm=True).

Export data:

Export all customer data as CSV.
Export sales summary as JSON.

Business insights:

Add an insight: "Sales increased 25% in Q4 due to holiday promotions"
Show me all stored insights.

Architecture

general-database-mcp-python/
├── main.py                    # FastMCP server entry point
├── db/
│   ├── __init__.py
│   └── postgres_adapter.py   # PostgreSQL adapter with connection pooling
├── tools/
│   ├── __init__.py
│   ├── query_tools.py        # Query execution tools
│   ├── schema_tools.py       # DDL operation tools
│   └── insights_tools.py     # Business insights tools
└── utils/
    ├── __init__.py
    └── format_utils.py       # Response formatting and CSV conversion

Development

Running Tests

# TODO: Add test suite
python -m pytest tests/

Security Considerations

1. Never expose database credentials in your conversations with Claude
2. Use environment variables for sensitive configuration
3. Enable API_KEY for production deployments
4. Review SQL queries generated by the LLM before execution in production
5. Use read-only database users when only SELECT access is needed

License

MIT License - See LICENSE file for details

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

Support

For issues, questions, or contributions, please open an issue on the repository.

Version

Current Version: 1.0.0

Acknowledgments

• Built with FastMCP framework
• Inspired by general-database-mcp
• Part of the Model Context Protocol ecosystem