oriona-database-tools 0.4.6

MCP server providing database exploration and query tools for AI assistants

Database Tools MCP Server

An MCP (Model Context Protocol) server that provides database exploration and query tools for AI assistants. This server enables safe SQL querying and database schema exploration with built-in security features.

Features

• Table List Explorer: List all tables and views in a database
• Table Details Explorer: Get detailed schema information and sample data for specific tables
• Query Engine: Execute read-only SQL queries with safety features and timeouts

Installation

No installation required! Use uvx to run directly:

uvx oriona-database-tools

Quick Start

1. No installation needed - uvx runs the package directly

2. Set your database URL:

   # PostgreSQL
   export DATABASE_URL="postgresql://user:password@localhost:5432/mydb"
   
   # SQL Server
   export DATABASE_URL="mssql+pymssql://user:password@localhost:1433/mydb"
   
   # MySQL
   export DATABASE_URL="mysql+pymysql://user:password@localhost:3306/mydb"
   
   # SQLite
   export DATABASE_URL="sqlite:///path/to/database.db"
   

3. Add to Claude Desktop (see configuration below)

Claude Desktop Configuration

Add to your Claude Desktop configuration file:

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

{
  "mcpServers": {
    "database-tools": {
      "command": "uvx",
      "args": ["oriona-database-tools"],
      "env": {
        "DATABASE_URL": "postgresql://user:password@localhost:5432/mydb",
        "TABLE_WHITELIST": "users,orders,products",
        "TABLE_BLACKLIST": "api_keys,secrets"
      }
    }
  }
}

Security Note: Always use a read-only database user for the MCP server to ensure data safety.

Available Tools

1. list_tables

List all tables and views in a database.

Parameters:

• include_views (boolean, optional): Include database views in the list (default: true)

Example:

{
  "tool": "list_tables",
  "arguments": {
    "include_views": true
  }
}

2. explore_table

Get detailed information about a specific table including schema, foreign keys, and sample data.

Parameters:

• table_name (string, required): The name of the table to analyze
• sample_size (integer, optional): Number of sample rows to retrieve (0-100, default: 3)

Example:

{
  "tool": "explore_table",
  "arguments": {
    "table_name": "customers",
    "sample_size": 5
  }
}

3. query_database_readonly

Execute read-only SELECT queries with safety features.

Parameters:

• query (string, required): The SQL query to execute (SELECT only)
• timeout_seconds (integer, optional): Maximum query execution time in seconds (default: 30)
• max_rows (integer, optional): Maximum number of rows to return (0 for unlimited, default: 100)

Example:

{
  "tool": "query_database_readonly",
  "arguments": {
    "query": "SELECT * FROM orders WHERE created_at > '2024-01-01' LIMIT 10",
    "timeout_seconds": 30,
    "max_rows": 100
  }
}

Supported Databases

• PostgreSQL (recommended)
• MySQL
• Microsoft SQL Server
• SQLite
• BigQuery (Google Cloud)
• Any SQLAlchemy-supported database

Security Features

• Read-only queries: Only SELECT and WITH queries are allowed
• Query timeout: Configurable timeout to prevent long-running queries
• Row limits: Default limit of 100 rows per query (configurable)
• Connection pooling: Efficient connection management with pool recycling
• URI sanitization: Automatic conversion of legacy postgres:// to postgresql://
• Table filtering: Whitelist/blacklist specific tables to control access

Environment Variables

Required:

• DATABASE_URL: The database connection URL (e.g., postgresql://user:pass@localhost:5432/mydb)

Optional:

• DATABASE_TOOLS_LOG_LEVEL: Set logging level (default: INFO)
• DATABASE_TOOLS_MAX_CONNECTIONS: Maximum database connections per pool (default: 5)
• TABLE_WHITELIST: Comma-separated list of allowed tables (e.g., users,orders,products)
• TABLE_BLACKLIST: Comma-separated list of forbidden tables (e.g., secrets,sensitive_data)

BigQuery-specific (when using BigQuery):

• BIGQUERY_PROJECT_ID: Google Cloud project ID (required for BigQuery)
• BIGQUERY_CREDENTIALS_BASE64: Base64 encoded service account JSON (optional, falls back to default credentials)
• BIGQUERY_DATASET: Default dataset name (optional, if not specified, queries all accessible datasets)
• BIGQUERY_LOCATION: BigQuery location/region (default: US)

Microsoft SQL Server Setup

{
  "mcpServers": {
    "database-tools": {
      "command": "uvx",
      "args": ["oriona-database-tools"],
      "env": {
        "DATABASE_URL": "mssql+pymssql://{{username}}:{{password}}@{{host}}:{{port}}/database"
      }
    }
  }
}

Connection String Examples:

# Basic connection
mssql+pymssql://user:password@localhost:1433/mydb

BigQuery Setup

Authentication

Option 1: Base64 Encoded Service Account (Recommended)

1. Create a service account in Google Cloud Console
2. Download the JSON key file
3. Encode to base64:

   base64 -i /path/to/service-account.json
   

4. Configure Claude Desktop:

   {
     "mcpServers": {
       "database-tools": {
         "command": "uvx",
         "args": ["oriona-database-tools"],
         "env": {
           "BIGQUERY_PROJECT_ID": "your-project-id",
           "BIGQUERY_CREDENTIALS_BASE64": "eyJ0eXBlIjoic2VydmljZV9hY2NvdW50Ii...",
           "BIGQUERY_DATASET": "your_dataset"
         }
       }
     }
   }
   

Option 2: Default Credentials (Fallback)

If you have the Google Cloud CLI installed and authenticated:

gcloud auth application-default login

Then configure without credentials:

{
  "mcpServers": {
    "database-tools": {
      "command": "uvx",
      "args": ["oriona-database-tools"],
      "env": {
        "BIGQUERY_PROJECT_ID": "your-project-id",
        "BIGQUERY_DATASET": "your_dataset"
      }
    }
  }
}

Dataset Configuration

• Specific dataset: Set BIGQUERY_DATASET to limit access to one dataset
• All datasets: Leave BIGQUERY_DATASET unset to access all datasets (tables will be prefixed with dataset.table)

Required Permissions

Your service account needs these BigQuery permissions:

• bigquery.datasets.get
• bigquery.tables.list
• bigquery.tables.get
• bigquery.tables.getData
• bigquery.jobs.create

Table Filtering

You can control which tables are accessible through the MCP server using whitelist and blacklist configurations:

Whitelist Mode

When TABLE_WHITELIST is set, only the specified tables will be accessible:

{
  "env": {
    "DATABASE_URL": "postgresql://user:pass@localhost:5432/mydb",
    "TABLE_WHITELIST": "users,orders,products"
  }
}

In this example, only users, orders, and products tables can be accessed.

Blacklist Mode

When TABLE_BLACKLIST is set, the specified tables will be blocked:

{
  "env": {
    "DATABASE_URL": "postgresql://user:pass@localhost:5432/mydb",
    "TABLE_BLACKLIST": "api_keys,user_passwords,audit_logs"
  }
}

In this example, api_keys, user_passwords, and audit_logs tables cannot be accessed.

Filtering Behavior

• Filtered tables won't appear in list_tables results
• Attempts to access filtered tables with explore_table will return an access denied error
• Table names are case-insensitive (e.g., Users and users are treated the same)

Error Handling

The server returns structured error responses:

{
  "error": "Error message",
  "error_type": "ExceptionType",
  "recommendation": "Suggested action"
}

Common errors:

• Table/column not found: Check table names with list_tables
• Query timeout: Reduce query complexity or increase timeout
• Permission denied: Verify database credentials