Igloo MCP - Snowflake MCP Server for Agentic Native Workflows

Igloo MCP is a standalone MCP server for Snowflake operations, designed for agentic native workflows with AI assistants. Built from the ground up with SnowCLI integration for maximum simplicity and performance.

✨ Features

🛡️ SQL Safety: Blocks destructive operations (DELETE, DROP, TRUNCATE) with safe alternatives
🧠 Intelligent Errors: Compact mode (default) saves 70% tokens; verbose mode for debugging
⏱️ Agent-Controlled Timeouts: Configure query timeouts per-request (1-3600s)
✅ MCP Protocol Compliant: Standard exception-based error handling
🚀 Zero Vendoring: Imports from upstream, stays in sync

📖 See Release Notes for details.

PyPI version Python 3.12+ License: MIT

Available MCP Tools

Igloo MCP Tools

execute_query - Execute SQL queries with safety checks
preview_table - Preview table contents
build_catalog - Build metadata catalog
get_catalog_summary - Get catalog overview
build_dependency_graph - Build dependency graph
test_connection - Test Snowflake connection
health_check - Get system health status

See MCP Documentation for details.

Installation

For End Users (Recommended)

Install from PyPI for stable releases:

uv pip install igloo-mcp

⚡ Quickstart

# 1. Install (1 minute) uv pip install igloo-mcp # snowflake-cli-labs installed automatically # 2. Create Snowflake profile (2 minutes) snow connection add \ --connection-name "quickstart" \ --account "<your-account>.<region>" \ # e.g., abc12345.us-east-1 --user "<your-username>" \ --password \ --warehouse "<your-warehouse>" # e.g., COMPUTE_WH # Enter password when prompted # 3. Configure your MCP client (1 minute) # Add to your MCP client config (e.g., Claude Code, Continue, Zed): { "mcpServers": { "snowflake": { "command": "igloo-mcp", "args": ["--profile", "quickstart"] } } } # 4. Test it! (1 minute) # In your AI assistant, ask: # "Show me my Snowflake databases"

Success! 🎉 Your AI can now query Snowflake.

New to Snowflake? See Parameter Guide for help finding your account identifier and understanding which parameters are required.

Complete Setup Guide key-pair authentication

For production with key-pair authentication:

# 1. 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" # 2. Start MCP server SNOWFLAKE_PROFILE=my-profile igloo-mcp # Expected output: # ✓ MCP server started successfully # ✓ Listening on stdio for MCP requests

See Getting Started Guide for detailed setup instructions.

MCP Server (MCP-Only Interface)

Task	Command	Notes
Start MCP server	`igloo-mcp`	For AI assistant integration
Start with profile	`igloo-mcp --profile PROF`	Specify profile explicitly
Configure	`igloo-mcp --configure`	Interactive setup

🐻‍❄️ MCP-Only Architecture Nanuk is MCP-only. All functionality is available through MCP tools.

Profile Selection Options:

Command flag: igloo-mcp --profile PROFILE_NAME (explicit)
Environment variable: export SNOWFLAKE_PROFILE=PROFILE_NAME (session)
Default profile: Set with snow connection set-default PROFILE_NAME (implicit)

Python API

from nanuk_mcp import QueryService, CatalogService # Execute query query_service = QueryService(profile="my-profile") result = query_service.execute("SELECT * FROM users LIMIT 10") # Build catalog catalog_service = CatalogService(profile="my-profile") catalog = catalog_service.build_catalog(database="MY_DB")

Documentation

Examples

Query Execution via MCP

# AI assistant sends query via MCP { "tool": "execute_query", "arguments": { "statement": "SELECT COUNT(*) FROM users WHERE created_at > CURRENT_DATE - 30", "timeout_seconds": 60 } }

Data Lineage

# Query lineage for impact analysis { "tool": "query_lineage", "arguments": { "object_name": "MY_TABLE", "direction": "both", "depth": 3 } }

This server cannot be installed

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security - not tested

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license - not tested

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quality - not tested

How are these scores calculated?

remote-capable server

The server can be hosted and run remotely because it primarily relies on remote services or has no dependency on the local environment.

Enables AI assistants to interact with Snowflake databases through SQL queries, table previews, and metadata operations. Features built-in safety checks that block destructive operations and intelligent error handling optimized for AI workflows.

Igloo MCP