Server For Snowflake

A Model Context Protocol (MCP) server for performing read-only operations against Snowflake databases. This tool enables Claude to securely query Snowflake data without modifying any information.

Features

• Flexible authentication to Snowflake using either:
  • Service account authentication with private key
  • External browser authentication for interactive sessions
• Connection pooling with automatic background refresh to maintain persistent connections
• Support for querying multiple views and databases in a single session
• Support for multiple SQL statement types (SELECT, SHOW, DESCRIBE, EXPLAIN, WITH)
• MCP-compatible handlers for querying Snowflake data
• Read-only operations with security checks to prevent data modification
• Support for Python 3.12+
• Stdio-based MCP server for easy integration with Claude Desktop

Available Tools

The server provides the following tools for querying Snowflake:

• list_databases: List all accessible Snowflake databases
• list_views: List all views in a specified database and schema
• describe_view: Get detailed information about a specific view including columns and SQL definition
• query_view: Query data from a view with an optional row limit
• execute_query: Execute custom read-only SQL queries (SELECT, SHOW, DESCRIBE, EXPLAIN, WITH) with results formatted as markdown tables

Installation

Prerequisites

• Python 3.12 or higher
• A Snowflake account with either:
  • A configured service account (username + private key), or
  • A regular user account for browser-based authentication
• uv package manager (recommended)

Steps

1. Clone this repository:

   git clone https://github.com/yourusername/snowflake-mcp-server.git
   cd snowflake-mcp-server
   

2. Install the package:

   uv pip install -e .
   

3. Create a .env file with your Snowflake credentials:

   Choose one of the provided example files based on your preferred authentication method:

   For private key authentication:

   cp .env.private_key.example .env
   

   Then edit the .env file to set your Snowflake account details and path to your private key.

   For external browser authentication:

   cp .env.browser.example .env
   

   Then edit the .env file to set your Snowflake account details.

Usage

Running with uv

After installing the package, you can run the server directly with:

uv run snowflake-mcp

# Or you can be explicit about using stdio transport
uv run snowflake-mcp-stdio

This will start the stdio-based MCP server, which can be connected to Claude Desktop or any MCP client that supports stdio communication.

When using external browser authentication, a browser window will automatically open prompting you to log in to your Snowflake account.

Claude Desktop Integration

1. In Claude Desktop, go to Settings → MCP Servers

2. Add a new server with the full path to your uv executable:

   "snowflake-mcp-server": {
      "command": "uv",
      "args": [
         "--directory",
         "/<path-to-code>/snowflake-mcp-server",
         "run",
         "snowflake-mcp"
      ]
   }
   

   Or explicitly specify the stdio transport:

   "snowflake-mcp-server": {
      "command": "uv",
      "args": [
         "--directory",
         "/<path-to-code>/snowflake-mcp-server",
         "run",
         "snowflake-mcp-stdio"
      ]
   }
   

3. You can find your uv path by running which uv in your terminal

4. Save the server configuration

Example Queries

When using with Claude, you can ask questions like:

• "Can you list all the databases in my Snowflake account?"
• "List all views in the MARKETING database"
• "Describe the structure of the CUSTOMER_ANALYTICS view in the SALES database"
• "Show me sample data from the REVENUE_BY_REGION view in the FINANCE database"
• "Run this SQL query: SELECT customer_id, SUM(order_total) as total_spend FROM SALES.ORDERS GROUP BY customer_id ORDER BY total_spend DESC LIMIT 10"
• "Query the MARKETING database to find the top 5 performing campaigns by conversion rate"
• "Compare data from views in different databases by querying SALES.CUSTOMER_METRICS and MARKETING.CAMPAIGN_RESULTS"

Configuration

Connection pooling behavior can be configured through environment variables:

• SNOWFLAKE_CONN_REFRESH_HOURS: Time interval in hours between connection refreshes (default: 8)

Example .env configuration:

# Set connection to refresh every 4 hours
SNOWFLAKE_CONN_REFRESH_HOURS=4

Authentication Methods

Private Key Authentication

This method uses a service account and private key for non-interactive authentication, ideal for automated processes.

1. Create a key pair for your Snowflake user following Snowflake documentation
2. Set SNOWFLAKE_AUTH_TYPE=private_key in your .env file
3. Provide the path to your private key in SNOWFLAKE_PRIVATE_KEY_PATH

External Browser Authentication

This method opens a browser window for interactive authentication.

1. Set SNOWFLAKE_AUTH_TYPE=external_browser in your .env file
2. When you start the server, a browser window will open asking you to log in
3. After authentication, the session will remain active for the duration specified by your Snowflake account settings

Security Considerations

This server:

• Enforces read-only operations (only SELECT, SHOW, DESCRIBE, EXPLAIN, and WITH statements are allowed)
• Automatically adds LIMIT clauses to prevent large result sets
• Uses secure authentication methods for connections to Snowflake
• Validates inputs to prevent SQL injection

⚠️ Important: Keep your .env file secure and never commit it to version control. The .gitignore file is configured to exclude it.

Development

Static Type Checking

mypy mcp_server_snowflake/

Linting

ruff check .

Formatting

ruff format .

Running Tests

pytest

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

Technical Details

This project uses:

• Snowflake Connector Python for connecting to Snowflake
• MCP (Model Context Protocol) for interacting with Claude
• Pydantic for data validation
• python-dotenv for environment variable management