snowcli-tools 1.6.0

Snowflake CLI Tools: generate a Data Catalog and Dependency Graph on top of the official Snowflake CLI; includes parallel query helpers and advanced lineage features

SnowCLI Tools

Powerful Snowflake operations with AI assistant integration

Transform your Snowflake data operations with automated cataloging, advanced lineage analysis, and seamless AI assistant connectivity through MCP (Model Context Protocol).

Quick Start

# 1. Install SnowCLI Tools
pip install snowcli-tools

# 2. Set up your Snowflake profile
snow connection add --connection-name "my-profile" \
  --account "your-account.region" --user "your-username" \
  --private-key-file "/path/to/key.p8" --database "DB" --warehouse "WH"

# 3. Verify connection
snowflake-cli verify -p my-profile

# 4. Start exploring your data
snowflake-cli catalog -p my-profile
snowflake-cli lineage MY_TABLE -p my-profile

# 5. Enable AI assistant integration
SNOWFLAKE_PROFILE=my-profile snowflake-cli mcp

Core Features

📊 Data Discovery & Analysis

• Automated Catalog: Complete metadata extraction from databases, schemas, tables
• Advanced Lineage: Column-level lineage tracking with impact analysis
• Dependency Mapping: Visual object relationships and circular dependency detection
• External Integration: S3/Azure/GCS source mapping

🤖 AI Assistant Integration

• MCP Server: Direct integration with Claude Code, VS Code, Cursor
• Natural Language: "Show me schema of CUSTOMERS" → instant results
• Health Monitoring: Real-time diagnostics and validation
• Enhanced Profiles: Clear error messages instead of timeouts

⚡ Enterprise Ready

• Layered Security: Built on Snowflake's official authentication
• High Performance: Parallel operations and connection pooling
• Fault Tolerance: Circuit breaker patterns for reliability
• Modern Architecture: Python 3.12+ with async support

Architecture

SnowCLI Tools uses a layered architecture that combines official Snowflake tools with enhanced analytics:

┌─────────────────────────────────────┐
│     AI Assistants & Applications    │  ← Your workflows
├─────────────────────────────────────┤
│      SnowCLI Tools MCP Server       │  ← Enhanced analytics
│   (Catalog, Lineage, Dependencies)  │
├─────────────────────────────────────┤
│       Snowflake Labs MCP            │  ← Official foundation
│    (Auth, Connection, Security)     │
├─────────────────────────────────────┤
│        Snowflake Platform           │  ← Your data warehouse
└─────────────────────────────────────┘

Key Benefits:

• 🔐 Secure: Leverages Snowflake's official authentication
• 🚀 Powerful: Combines official tools with advanced analytics
• 🔗 Integrated: Single MCP endpoint for AI assistants
• 📈 Scalable: Service layer architecture for extensibility

Common Use Cases

Data Discovery Workflow

# Build comprehensive catalog
snowflake-cli catalog -p prod

# Map dependencies
snowflake-cli depgraph -p prod --format dot

# Analyze critical table lineage
snowflake-cli lineage CUSTOMER_ORDERS -p prod --depth 3

AI Assistant Integration

# Start MCP server for AI assistants
SNOWFLAKE_PROFILE=prod snowflake-cli mcp

# Now use Claude Code, VS Code, or Cursor to:
# - "What tables depend on CUSTOMERS?"
# - "Show me the schema for ORDERS table"
# - "Generate a data quality report"

Multi-Environment Development

# Switch between environments easily
snowflake-cli query "SELECT COUNT(*) FROM users" -p dev
snowflake-cli query "SELECT COUNT(*) FROM users" -p staging
snowflake-cli query "SELECT COUNT(*) FROM users" -p prod

Getting Started

Prerequisites

• Python 3.12+ with pip or uv
• Snowflake account with appropriate permissions
• Snowflake CLI installed (pip install snowflake-cli)

Installation Options

Option 1: PyPI (Recommended)

pip install snowcli-tools

Option 2: Development Install

git clone <repository-url>
cd snowcli-tools
uv sync  # or pip install -e .

Profile Setup

# Key-pair authentication (recommended)
snow connection add --connection-name "my-profile" \
  --account "your-account.region" \
  --user "username" \
  --private-key-file "/path/to/key.p8" \
  --database "DATABASE" \
  --warehouse "WAREHOUSE"

# OAuth authentication
snow connection add --connection-name "my-profile" \
  --account "your-account.region" \
  --user "username" \
  --authenticator "externalbrowser"

# Verify setup
snowflake-cli verify -p my-profile

Documentation

• Getting Started Guide - Complete setup and usage guide
• Architecture Overview - Technical architecture and design patterns
• MCP Integration - AI assistant setup and configuration
• API Reference - Complete command and API documentation
• Configuration Guide - Advanced configuration options
• Contributing - Development and contribution guidelines

Requirements

• Python: 3.12 or higher
• Snowflake CLI: Latest version recommended
• Dependencies: Automatically installed with package
• Permissions: USAGE on warehouse/database/schema, SELECT on INFORMATION_SCHEMA

MCP Integration

For AI assistant integration, install MCP extras:

# Install MCP dependencies
pip install "mcp>=1.0.0" "fastmcp>=2.8.1" "snowflake-labs-mcp>=1.3.3"

# Start MCP server
SNOWFLAKE_PROFILE=my-profile snowflake-cli mcp

# Configure your AI assistant to connect via MCP

Supported AI Assistants:

• Claude Code
• VS Code with MCP extensions
• Cursor IDE
• Any MCP-compatible client

Support

• Documentation: Comprehensive guides in /docs
• Issues: Report bugs via GitHub Issues
• Examples: Sample workflows in /examples
• Community: [Discord/Slack community link]

License

[License Type] - see LICENSE file for details.

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Version 1.5.0 | Built with ❤️ for the Snowflake community