Vertica MCP Server

A Model Context Protocol (MCP) server that provides comprehensive Vertica Database integration capabilities for AI assistants and agents.

Features

• Query Execution: Execute SQL queries with safety controls (SELECT, DESCRIBE, EXPLAIN only)

• Schema Inspection: Browse database tables, views, and Vertica-specific projections

• Database Documentation: Generate comprehensive database documentation

• Query Analysis: Analyze query performance with execution plans

• Data Export: Export query results in JSON and CSV formats

• Vertica-Specific: Support for projections, cluster status, and columnar storage features

Related MCP server: MCP Toolkit

Installation

Prerequisites

• Python 3.11 or higher

• Access to a Vertica database

• uv package manager

Install from Source

git clone <repository-url>
cd vertica-mcp-server
uv sync

Install as Package

uv add vertica-mcp-server

Quick Start

1. Set up environment variables:

   export DB_CONNECTION_STRING="vertica://username:password@hostname:5433/database"

2. Start the MCP server:

   vertica-mcp-server

3. Use with AI assistants that support MCP (like Claude Desktop or VS Code extensions)

Configuration

Connection String Formats

URL Format (recommended):

vertica://username:password@hostname:port/database

Simple Format:

hostname:port/database

When using simple format, set these environment variables:

• VERTICA_USER: Database username

• VERTICA_PASSWORD: Database password

Environment Variables

Docker Development

A Docker setup is provided for testing with Vertica Community Edition:

cd docker-example
docker-compose up -d

See docker-example/README.md for detailed instructions.

Available Tools

The MCP server provides these tools for AI assistants:

• execute_query: Execute SQL queries (SELECT, DESCRIBE, EXPLAIN only)

• describe_table: Get detailed table column information

• list_tables: List all tables with metadata

• list_views: List all database views

• list_projections: List Vertica projections (unique to Vertica)

• explain_query: Get query execution plans

• generate_sample_queries: Generate example queries for tables

• export_query_results: Export query results as JSON or CSV

Vertica-Specific Features

This server includes Vertica-specific functionality:

• Projections: List and inspect Vertica projections

• Columnar Storage: Handle Vertica's columnar data types

• Query Optimization: Vertica-specific query execution plans

• Data Types: Support for Vertica data types (UUID, ARRAY, etc.)

Safety Features

• Query Restriction: Only SELECT, DESCRIBE, and EXPLAIN statements allowed

• Row Limiting: Automatic LIMIT clause added to prevent large result sets

• SQL Injection Protection: Basic protection against malicious queries

• Whitelisting: Optional table and column whitelisting

Development

Running Tests

# Run all tests
uv run pytest

# Run unit tests only
uv run pytest -m unit

# Run integration tests only (requires running Vertica instance)
uv run pytest -m integration

# Run tests with coverage
uv run pytest --cov=src/vertica_mcp_server

Code Quality

# Format code
uv run black src/ tests/

# Sort imports
uv run isort src/ tests/

# Type checking
uv run mypy src/

# Lint code
uv run flake8 src/ tests/

Project Structure

vertica-mcp-server/
   src/vertica_mcp_server/
      __init__.py
      server.py          # Main server implementation
      py.typed
   tests/                 # Test suite
   docker-example/        # Docker setup for testing
   docs/                  # Documentation
   pyproject.toml        # Project configuration

Contributing

1. Fork the repository

2. Create a feature branch

3. Make your changes

4. Add tests for new functionality

5. Run the test suite

6. Submit a pull request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Changelog

0.1.0

• Initial release

• Core MCP server functionality

• Vertica database integration

• Query execution and schema inspection

• Docker development environment

• Comprehensive test suite