Crismarquez/mcp-server-sql

Sales Analytics MCP Server

Tools for querying sales data via Model Context Protocol with pluggable database connectors (Databricks, PostgreSQL, Azure SQL, or Mock).

Setup

1. Create and activate a virtualenv (optional)
2. Install deps:

pip install -r requirements.txt

3. Copy env template and configure:

copy .env.example .env

Environment

• DB_TYPE: one of databricks, postgres, azure, mock (default: mock)
• DB_CONN_STR: SQLAlchemy connection string for selected DB (not needed for mock)

Connection string examples

• Databricks: databricks+connector://token:@/.
• PostgreSQL: postgresql+psycopg2://user:password@host:5432/dbname
• Azure SQL: mssql+pyodbc://USER:PASSWORD@SERVER.database.windows.net:1433/DB?driver=ODBC+Driver+18+for+SQL+Server&Encrypt=yes&TrustServerCertificate=no

Run

python main.py

Docker

docker build -t sales-mcp .
docker run --rm -e DB_TYPE=mock sales-mcp

Tools

• best_sellers_by_region(region: str)
• top_products(limit: int = 5)
• sales_by_date(date: str)

Claude Desktop (local connection)

1. Build the Docker image (once):

docker build -t sales-mcp .

2. On Windows, create/edit the Claude Desktop config file at: %APPDATA%\Claude\claude_desktop_config.json

3. Add this configuration to run the MCP inside Docker:

{
    "mcpServers": {
        "sales-analytics": {
            "command": "docker",
            "args": [
                "run", "--rm", "-i",
                "-e", "DB_TYPE=mock",
                "sales-mcp"
            ]
        }
    }
}

4. Save the file and restart Claude Desktop.

Note: If you want to use a connector other than mock, set DB_TYPE accordingly and, if needed, add -e DB_CONN_STR=... following the "Environment" section of this README.