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mcp-snowflake-server

by isaacwasserman
GitHub
Python
GPL 3.0
60
  • Apple
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Integrations

  • Provides database interaction with Snowflake, enabling SQL query execution, table management, and schema exploration. Includes tools for reading data, modifying data (with appropriate permissions), creating tables, listing available tables, and describing table structures.

Snowflake MCP 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.

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
  • write_query (enabled only with --allow-write)
    Execute INSERT, UPDATE, or DELETE queries.
    Input:
    • query (string): The SQL modification query
      Returns: Number of affected rows or confirmation
  • create_table (enabled only with --allow-write)
    Create new tables in the database.
    Input:
    • query (string): CREATE TABLE SQL statement
      Returns: Confirmation of table creation
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 Smithery

To install Snowflake Server for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install mcp_snowflake_server --client claude

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: "--allow_write" // 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
  1. 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"
  1. [Optional] Modify runtime_config.json to set exclusion patterns for databases, schemas, or tables.
  2. Test locally:
uv --directory /absolute/path/to/mcp_snowflake_server run mcp_snowflake_server
  1. 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: "--allow_write" // Optionally: "--log_dir", "/absolute/path/to/logs" // Optionally: "--log_level", "DEBUG"/"INFO"/"WARNING"/"ERROR"/"CRITICAL" // Optionally: "--exclude_tools", "{tool_name}", ["{other_tool_name}"] ] } }

Notes

  • By default, write operations are disabled. Enable them explicitly with --allow-write.
  • 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

This server cannot be installed

-
security - not tested
A
license - permissive license
-
quality - not tested

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.

Snowflake integration implementing read and (optional) write operations as well as insight tracking

  1. Overview
    1. Components
      1. Resources
      2. Tools
    2. Usage with Claude Desktop
      1. Installing via Smithery
      2. Installing via UVX
      3. Installing Locally
    3. Notes
      1. License

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