hybrid server

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

Integrations

Supports integration with FastAPI for running the MCP server, providing both standalone and integrated deployment options
Provides database access capabilities for MySQL, supporting query execution and schema exploration
Enables querying and interacting with PostgreSQL databases through SQL execution tools and schema resources

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

This server cannot be installed

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security - not tested

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license - not found

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quality - not tested

A server that helps people access and query data in databases using the Query Runner with integration of the Model Context Protocol (MCP) Python SDK. Support databases including PostgreSQL Redshift MySQL Microsoft SQL Server Google APIs Amazon Web Services (via boto3) CockroachDB SQLite

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