Snowflake MCP Server

Slightly altered from https://github.com/isaacwasserman/mcp-snowflake-server

Overview

A Model Context Protocol (MCP) server implementation that provides database interaction with Snowflake. This server enables running SQL queries via tools and exposes data insights and schema context as resources. Does not include the ability to execute write operations, and includes a system prompt.

Components

Resources

• memo://insights
  A continuously updated memo aggregating discovered data insights.
  Updated automatically when new insights are appended via the append_insight tool.

• context://table/{table_name}
  (If prefetch enabled) Per-table schema summaries, including columns and comments, exposed as individual resources.

Tools

The server exposes the following tools:

Query Tools

• read_query
  Execute SELECT queries to read data from the database.
  Input:
  • query (string): The SELECT SQL query to execute
    Returns: Query results as array of objects

Schema Tools

• list_databases
  List all databases in the Snowflake instance.
  Returns: Array of database names

• list_schemas
  List all schemas within a specific database.
  Input:

  • database (string): Name of the database
    Returns: Array of schema names

• list_tables
  List all tables within a specific database and schema.
  Input:

  • database (string): Name of the database
  • schema (string): Name of the schema
    Returns: Array of table metadata

• describe_table
  View column information for a specific table.
  Input:

  • table_name (string): Fully qualified table name (database.schema.table)
    Returns: Array of column definitions with names, types, nullability, defaults, and comments

Analysis Tools

• append_insight
  Add new data insights to the memo resource.
  Input:
  • insight (string): Data insight discovered from analysis
    Returns: Confirmation of insight addition
    Effect: Triggers update of memo://insights resource

Usage with Claude Desktop

Installing via UVX

"mcpServers": {
  "snowflake_pip": {
    "command": "uvx",
    "args": [
      "--python=3.12",  // Optional: specify Python version <=3.12
      "mcp_snowflake_server",
      "--account", "your_account",
      "--warehouse", "your_warehouse",
      "--user", "your_user",
      "--password", "your_password",
      "--role", "your_role",
      "--database", "your_database",
      "--schema", "your_schema"
      // Optionally: "--log_dir", "/absolute/path/to/logs"
      // Optionally: "--log_level", "DEBUG"/"INFO"/"WARNING"/"ERROR"/"CRITICAL"
      // Optionally: "--exclude_tools", "{tool_name}", ["{other_tool_name}"]
    ]
  }
}

Installing Locally

1. Install Claude AI Desktop App

2. Install uv:

curl -LsSf https://astral.sh/uv/install.sh | sh

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

SNOWFLAKE_USER="xxx@your_email.com"
SNOWFLAKE_ACCOUNT="xxx"
SNOWFLAKE_ROLE="xxx"
SNOWFLAKE_DATABASE="xxx"
SNOWFLAKE_SCHEMA="xxx"
SNOWFLAKE_WAREHOUSE="xxx"
SNOWFLAKE_PASSWORD="xxx"
# Alternatively, use external browser authentication:
# SNOWFLAKE_AUTHENTICATOR="externalbrowser"

4. [Optional] Modify runtime_config.json to set exclusion patterns for databases, schemas, or tables.

5. Test locally:

uv --directory /absolute/path/to/mcp_snowflake_server run mcp_snowflake_server

6. Add the server to your claude_desktop_config.json:

"mcpServers": {
  "snowflake_local": {
    "command": "/absolute/path/to/uv",
    "args": [
      "--python=3.12",  // Optional
      "--directory", "/absolute/path/to/mcp_snowflake_server",
      "run", "mcp_snowflake_server"
      // Optionally: "--log_dir", "/absolute/path/to/logs"
      // Optionally: "--log_level", "DEBUG"/"INFO"/"WARNING"/"ERROR"/"CRITICAL"
      // Optionally: "--exclude_tools", "{tool_name}", ["{other_tool_name}"]
    ]
  }
}

Notes

• The server supports filtering out specific databases, schemas, or tables via exclusion patterns.
• The server exposes additional per-table context resources if prefetching is enabled.
• The append_insight tool updates the memo://insights resource dynamically.

License

MIT