Database MCP Server (by Legion AI)

A server that helps people access and query data in databases using the Legion Query Runner with integration of the Model Context Protocol (MCP) Python SDK.

Features

• Database access via Legion Query Runner
• Model Context Protocol (MCP) support for AI assistants
• Expose database operations as MCP resources, tools, and prompts
• Multiple deployment options (standalone MCP server, FastAPI integration)
• Query execution and result handling
• Flexible configuration via environment variables, command-line arguments, or MCP settings JSON

Supported Databases

| Database | DB_TYPE code | |----------|--------------| | PostgreSQL | pg | | Redshift | redshift | | CockroachDB | cockroach | | MySQL | mysql | | RDS MySQL | rds_mysql | | Microsoft SQL Server | mssql | | Big Query | bigquery | | Oracle DB | oracle | | SQLite | sqlite |

We use Legion Query Runner library as connectors. You can find more info on their api doc.

What is MCP?

The Model Context Protocol (MCP) is a specification for maintaining context in AI applications. This server uses the MCP Python SDK to:

• Expose database operations as tools for AI assistants
• Provide database schemas and metadata as resources
• Generate useful prompts for database operations
• Enable stateful interactions with databases

Installation & Configuration

Required Parameters

Two parameters are required for all installation methods:

• DB_TYPE: The database type code (see table above)
• DB_CONFIG: A JSON configuration string for database connection

The DB_CONFIG format varies by database type. See the API documentation for database-specific configuration details.

Installation Methods

Option 1: Using UV (Recommended)

When using uv, no specific installation is needed. We will use uvx to directly run database-mcp.

UV Configuration Example:

REPLACE DB_TYPE and DB_CONFIG with your connection info.
{
    "mcpServers": {
      "database-mcp": {
        "command": "uvx",
        "args": [
          "database-mcp"
        ],
        "env": {
          "DB_TYPE": "pg",
          "DB_CONFIG": "{\"host\":\"localhost\",\"port\":5432,\"user\":\"user\",\"password\":\"pw\",\"dbname\":\"dbname\"}"
        },
        "disabled": true,
        "autoApprove": []
      }
    }
}

Option 2: Using PIP

Install via pip:

pip install database-mcp

PIP Configuration Example:

{
  "mcpServers": {
    "database": {
      "command": "python",
      "args": [
        "-m", "database_mcp", 
        "--repository", "path/to/git/repo"
      ],
      "env": {
        "DB_TYPE": "pg",
        "DB_CONFIG": "{\"host\":\"localhost\",\"port\":5432,\"user\":\"user\",\"password\":\"pw\",\"dbname\":\"dbname\"}"
      }
    }
  }
}

Running the Server

Development Mode

mcp dev mcp_server.py

Production Mode

python mcp_server.py

Configuration Methods

Environment Variables

export DB_TYPE="pg"  # or mysql, postgresql, etc.
export DB_CONFIG='{"host":"localhost","port":5432,"user":"username","password":"password","dbname":"database_name"}'
mcp dev mcp_server.py

Command Line Arguments

python mcp_server.py --db-type pg --db-config '{"host":"localhost","port":5432,"user":"username","password":"password","dbname":"database_name"}'

Or with UV:

uv mcp_server.py --db-type pg --db-config '{"host":"localhost","port":5432,"user":"username","password":"password","dbname":"database_name"}'

Exposed MCP Capabilities

Resources

| Resource | Description | |----------|-------------| | schema://all | Get the complete database schema |

Tools

| Tool | Description | |------|-------------| | execute_query | Execute a SQL query and return results as a markdown table | | execute_query_json | Execute a SQL query and return results as JSON | | get_table_columns | Get column names for a specific table | | get_table_types | Get column types for a specific table | | get_query_history | Get the recent query history |

Prompts

| Prompt | Description | |--------|-------------| | sql_query | Create an SQL query against the database | | explain_query | Explain what a SQL query does | | optimize_query | Optimize a SQL query for better performance |

Development

Testing

uv pip install -e ".[dev]"
pytest

Publishing

rm -rf dist/ build/ *.egg-info/ && python -m build
python -m build
python -m twine upload dist/*

License

This repository is licensed under GPL