Simple Snowflake MCP server

Enhanced Snowflake MCP Server with comprehensive configuration system and full MCP protocol compliance.

A production-ready MCP server that provides seamless Snowflake integration with advanced features including configurable logging, resource subscriptions, and comprehensive error handling. Designed to work seamlessly behind corporate proxies.

For release details, see CHANGELOG.md.

Tools

The server exposes the following MCP tools to interact with Snowflake:

Database Operations:

• execute-snowflake-sql: Executes a SQL query on Snowflake and returns the result. Supports json (default), markdown, and csv output via the format argument.

• execute-query: Executes a SQL query with server-enforced read-only protection. In read-only mode (the default) only SELECT, SHOW, DESCRIBE, EXPLAIN, and WITH statements (without DML) are allowed. Read-only mode is governed solely by server configuration and cannot be relaxed by the caller. Supports a limit, an offset for paging, and markdown (default)/json/csv output via format. When a result is truncated the response includes the offset for the next page.

Discovery and Metadata:

• get-connection-info: Returns current Snowflake connection information and server status.

• list-snowflake-warehouses: Lists available Data Warehouses (DWH) on Snowflake. Pass include_details: false for names only.

• list-databases: Lists all accessible Snowflake databases. Supports a pattern filter (wildcards) and include_details.

• list-schemas: Lists schemas in a database. Supports a pattern filter (wildcards) and include_details.

• list-tables: Lists tables in a database/schema. Supports a pattern filter (wildcards) and include_details.

• list-views: Lists views in a database/schema. Supports a pattern filter (wildcards) and include_details.

• describe-table: Returns the columns and types of a database/schema/table (works for views too). Supports json (default)/markdown/csv via format.

• query-view: Reads rows from a database/schema/view (or table) by name, with the same server-enforced read-only protection and row limiting as execute-query. Supports a limit, an offset for paging, and markdown (default)/json/csv via format.

• export-schema: Exports hierarchical schema metadata (databases → schemas → tables/views → columns). Supports json (default), yaml, and sql via format, an optional database filter, and opt-in include_data_samples (table rows only, max 3 rows per table).

Notes (in-memory session state):

• add-note: Adds or updates a note (name, content) kept in server memory for the session.

• delete-note: Deletes an existing note by name.

• list-notes: Lists current note names in sorted order.

• get-note: Returns the note payload (name, content) for a given note name.

Prompts

The server also exposes MCP prompts that bundle server context into ready-to-use messages:

• summarize-notes: Summarizes the stored notes. Arguments: style (brief/detailed/executive), format (text/markdown/json).

• analyze-snowflake-schema: Produces a schema-analysis prompt. Arguments: database (optional focus), focus (tables/views/functions/all).

• generate-sql-query: Helps draft a SQL query from a natural-language goal. Arguments: intent (required), complexity (simple/intermediate/advanced).

• troubleshoot-connection: Builds a connection-troubleshooting prompt. Arguments: error_message (optional).

🔒 Security Model

This server executes client-supplied SQL against Snowflake using a single set of credentials. Treat the MCP client as untrusted (an LLM can be prompt-injected) and deploy accordingly.

The real security boundary is a least-privilege Snowflake role, not the server's keyword filter. The built-in read-only check is defense-in-depth only. Always connect with a role scoped to exactly what you need.

Required deployment posture:

1. Use a least-privilege, read-only Snowflake role. For read-only deployments, grant only USAGE/SELECT (and the relevant SHOW/DESCRIBE visibility) — no INSERT/UPDATE/DELETE/DDL/GRANT. If the role cannot write, no bypass of the keyword filter can cause damage.

2. Keep read_only: true (the default). Read-only mode is governed solely by server configuration / the MCP_READ_ONLY environment variable. It is not client-controllable — there is no read_only tool argument.

3. Set a statement timeout and rate limit (see config.yaml) to bound runaway or abusive queries and warehouse-credit consumption.

What the server enforces:

• Read-only mode applies to every SQL-executing tool through a single guard; comments are stripped, multi-statement input and CTE-fronted DML (e.g. WITH ... DELETE) are rejected.

• pattern / database arguments are validated against a strict allow-list before being placed into LIKE clauses; limit is coerced to a bounded integer and applied at the driver, never concatenated into SQL.

• Row-producing reads without an explicit LIMIT are capped at default_query_limit rows (applied at the driver). When a result is capped the response includes an explicit "results were truncated" notice — rows are never dropped silently. Pass a larger limit (up to max_query_limit) or add your own LIMIT clause to retrieve more.

• Snowflake errors are not returned verbatim to the client; a generic message with a reference id is returned and full detail is logged server-side.

• Query text is not logged at INFO (only a length + hash); full SQL is DEBUG-only.

Related MCP server: mcp-server-motherduck

🆕 Configuration System

The server now includes a comprehensive YAML-based configuration system that allows you to customize all aspects of the server behavior.

Configuration File Structure

Create a config.yaml file in your project root:

# Logging Configuration
logging:
  level: INFO  # DEBUG, INFO, WARNING, ERROR, CRITICAL (overridable via LOG_LEVEL)
  format: "%(asctime)s - %(name)s - %(levelname)s - %(message)s"
  file_logging:
    enabled: false        # Set to true to enable file logging
    filename: "logs/server.log"  # Must resolve under repository ./logs/
    max_bytes: 10485760   # Rotate after 10 MB
    backup_count: 5

# Server Configuration
server:
  name: "simple_snowflake_mcp"
  version: "0.4.0"
  description: "Enhanced Snowflake MCP Server with full protocol compliance"
  connection:
    test_on_startup: true
    timeout: 30

# Snowflake Configuration
snowflake:
  # Read-only mode is read from here (and the MCP_READ_ONLY env var), NOT from
  # the server block. Set to false to allow write operations.
  read_only: true
  default_query_limit: 1000
  max_query_limit: 50000
  statement_timeout_seconds: 300
  connection_reuse: true

# Security controls
security:
  rate_limit:
    enabled: true
    max_calls: 60
    window_seconds: 60
  notes:
    max_count: 100
    max_content_length: 10000

# MCP Protocol Settings
mcp:
  experimental_features:
    resource_subscriptions: true  # Enable resource change notifications
    completion_support: false    # Set to true when MCP version supports it
  
  notifications:
    resources_changed: true
    tools_changed: true
    prompts_changed: true

Using Custom Configuration

You can specify a custom configuration file using the CONFIG_FILE environment variable:

Windows:

set CONFIG_FILE=config_debug.yaml
python -m simple_snowflake_mcp

Linux/macOS:

CONFIG_FILE=config_production.yaml python -m simple_snowflake_mcp

Configuration Override Priority

Configuration values are resolved in this order (highest to lowest priority):

1. Environment variables (e.g., LOG_LEVEL, MCP_READ_ONLY)

2. Custom configuration file (via CONFIG_FILE)

3. Default config.yaml file

4. Built-in defaults

🚀 Quick Install

Method 1: Install with uvx (Recommended)

# Install and run directly
uvx simple-snowflake-mcp

Method 2: Install from source

# Clone the repo
git clone https://github.com/YannBrrd/simple_snowflake_mcp
cd simple_snowflake_mcp

# Install with uv (creates a venv automatically)
uv sync

# Run
uv run simple-snowflake-mcp

Method 3: Development

# Install with development dependencies
uv sync --all-extras

# Run the tests
uv run pytest

# Lint with ruff
uv run ruff check .
uv run ruff format .

Configuration Claude Desktop

On MacOS: ~/Library/Application\ Support/Claude/claude_desktop_config.json

On Windows: %APPDATA%/Claude/claude_desktop_config.json

"mcpServers": {
  "simple_snowflake_mcp": {
    "command": "uv",
    "args": [
      "--directory",
      ".", 
      "run",
      "simple_snowflake_mcp"
    ]
  }
}

"mcpServers": {
  "simple_snowflake_mcp": {
    "command": "uvx",
    "args": [
      "simple_snowflake_mcp"
    ]
  }
}

Docker Setup

Prerequisites

• Docker and Docker Compose installed on your system

• Your Snowflake credentials

Quick Start with Docker

1. Clone the repository

   git clone <your-repo>
   cd simple_snowflake_mcp

2. Set up environment variables

   cp .env.example .env
   # Edit .env with your Snowflake credentials

3. Build and run with Docker Compose

   # Build the Docker image
   docker-compose build
   
   # Start the service
   docker-compose up -d
   
   # View logs
   docker-compose logs -f

Docker Commands

Using Docker Compose directly:

# Build the image
docker-compose build

# Start in production mode
docker-compose up -d

# Start in development mode (with volume mounts for live code changes)
docker-compose --profile dev up simple-snowflake-mcp-dev -d

# View logs
docker-compose logs -f

# Stop the service
docker-compose down

# Clean up (remove containers, images, and volumes)
docker-compose down --rmi all --volumes --remove-orphans

Using the provided Makefile (Windows users can use make with WSL or install make for Windows):

# See all available commands
make help

# Build and start
make build
make up

# Development mode
make dev-up

# View logs
make logs

# Clean up
make clean

Docker Configuration

The Docker setup includes:

• Dockerfile: Multi-stage build with Python 3.11 slim base image

• docker-compose.yml: Service definition with environment variable support

• .dockerignore: Optimized build context

• Makefile: Convenient commands for Docker operations

Environment Variables

All Snowflake configuration can be set via environment variables:

Required:

• SNOWFLAKE_USER: Your Snowflake username

• SNOWFLAKE_PASSWORD: Your Snowflake password

• SNOWFLAKE_ACCOUNT: Your Snowflake account identifier

Optional:

• SNOWFLAKE_WAREHOUSE: Warehouse name

• SNOWFLAKE_DATABASE: Default database

• SNOWFLAKE_SCHEMA: Default schema

• MCP_READ_ONLY: Set to "TRUE" for read-only mode (default: TRUE)

Configuration System (v0.2.0):

• CONFIG_FILE: Path to custom configuration file (default: config.yaml)

• LOG_LEVEL: Override logging level (DEBUG, INFO, WARNING, ERROR, CRITICAL)

Development Mode

For development, use the development profile which mounts your source code:

docker-compose --profile dev up simple-snowflake-mcp-dev -d

This allows you to make changes to the code without rebuilding the Docker image.

Development

Installing dependencies

# Sync all dependencies (prod + dev)
uv sync --all-extras

# Update dependencies
uv lock --upgrade

# Add a new dependency
uv add <package-name>

# Add a dev dependency
uv add --dev <package-name>

Build and Publish

# Build
uv build

# Publish to PyPI
uv publish --token $UV_PUBLISH_TOKEN

CI

GitHub Actions CI runs on pushes to main and on pull requests via .github/workflows/ci.yml:

uv run ruff check .
uv run ruff format --check .
uv run pytest

Debugging with MCP Inspector

Since MCP servers run over stdio, debugging can be challenging. For the best debugging experience, we strongly recommend using the MCP Inspector.

You can launch the MCP Inspector via npm with this command:

npx @modelcontextprotocol/inspector uv run simple-snowflake-mcp

Upon launching, the Inspector will display a URL that you can access in your browser to begin debugging.

New Feature: Snowflake SQL Execution

The server exposes an MCP tool execute-snowflake-sql to execute a SQL query on Snowflake and return the result.

Usage

Call the MCP tool execute-snowflake-sql with a sql argument containing the SQL query to execute. The result will be returned as a list of dictionaries (one per row).

Example:

{
  "name": "execute-snowflake-sql",
  "arguments": { "sql": "SELECT CURRENT_TIMESTAMP;" }
}

The result will be returned in the MCP response.

Installation and configuration in VS Code

1. Clone the project and install dependencies

   git clone https://github.com/YannBrrd/simple_snowflake_mcp
   cd simple_snowflake_mcp
   
   # Install with uv (creates a venv automatically)
   uv sync --all-extras

2. Configure Snowflake access

   • Copy .env.example to .env and fill in your credentials:

     SNOWFLAKE_USER=...
     SNOWFLAKE_PASSWORD=...
     SNOWFLAKE_ACCOUNT=...
     # SNOWFLAKE_WAREHOUSE   Optional: Snowflake warehouse name
     # SNOWFLAKE_DATABASE    Optional: default database name
     # SNOWFLAKE_SCHEMA      Optional: default schema name
     # MCP_READ_ONLY=true|false   Optional: true/false to force read-only mode

3. Configure the server (v0.2.0)

   • If no config.yaml is present, the server uses its built-in defaults (no file is created automatically)

   • Customize logging, limits, and MCP features by editing config.yaml (an example is provided in the repository)

   • Use CONFIG_FILE=custom_config.yaml to specify a different file (resolved within the repository only, to prevent path traversal)

4. Configure VS Code for MCP debugging

   • The .vscode/mcp.json file is already present:

     {
       "servers": {
         "simple-snowflake-mcp": {
           "type": "stdio",
           "command": "uv",
           "args": ["run", "simple-snowflake-mcp"]
         }
       }
     }

   • Open the command palette (Ctrl+Shift+P), type MCP: Start Server, and select simple-snowflake-mcp.

5. Usage

   • The exposed MCP tools let you query Snowflake (list-databases, list-snowflake-warehouses, execute-query, execute-snowflake-sql, export-schema, etc.).

   • For more examples, see the MCP protocol documentation: https://github.com/modelcontextprotocol/create-python-server

Enhanced MCP Features (v0.2.0)

Advanced MCP Protocol Support

This server now implements comprehensive MCP protocol features:

🔔 Resource Subscriptions

• Real-time notifications when Snowflake resources change

• Automatic updates for database schema changes

• Tool availability notifications

📋 Enhanced Resource Management

• Dynamic resource discovery and listing

• Detailed resource metadata and descriptions

• Resource templates for browsing the object hierarchy by URI (snowflake://database/{database}/schemas, snowflake://database/{database}/schema/{schema}/tables, snowflake://table/{database}/{schema}/{table})

• Argument completion for prompts and resource templates (live database/ schema/table name suggestions)

• Client-controlled log verbosity via the MCP logging/setLevel request

⚡ Performance & Reliability

• Configurable query limits and a server-side statement timeout

• Comprehensive error handling with generic client messages and a server-side reference id

• Single-connection reuse with automatic reconnect on a stale connection

🔧 Development Features

• Multiple output formats (JSON, Markdown, CSV)

• In-process rate limiting across all tool calls

• Comprehensive logging with configurable levels (and an explicit truncation notice on capped results)

MCP Capabilities Advertised

The server advertises these MCP capabilities:

• ✅ Tools: Full tool execution with comprehensive schemas

• ✅ Resources: Dynamic resource discovery, subscriptions, and templates

• ✅ Prompts: Enhanced prompts with resource integration

• ✅ Notifications: Real-time change notifications

• ✅ Completion: Argument completion for prompts and resource templates

• ✅ Logging: Client-controlled log level via logging/setLevel

Supported MCP Functions

The server exposes the following MCP tools (see the Tools section above for full argument details):

Database Operations:

• execute-snowflake-sql: Executes a SQL query and returns results as JSON, markdown, or CSV

• execute-query: Query execution with read-only protection, row limit, and multiple output formats

Discovery and Metadata:

• get-connection-info: Current connection information and server status

• list-snowflake-warehouses: Lists available Data Warehouses with status

• list-databases: Lists all accessible databases, with optional pattern filtering

• export-schema: Exports hierarchical schema metadata in JSON, YAML, or SQL format (with optional capped table samples)

Session Notes:

• add-note / delete-note / list-notes / get-note: Manage in-memory notes for the session

The server also implements MCP resources (Snowflake objects with subscription support) and prompts. For parameter schemas, inspect handle_list_tools in src/simple_snowflake_mcp/server.py.

🚀 Getting Started Examples

Basic Usage

# Execute a simple query
{
  "name": "execute-query",
  "arguments": {
    "sql": "SELECT CURRENT_TIMESTAMP;",
    "format": "markdown"
  }
}

# List all databases
{
  "name": "list-databases",
  "arguments": {}
}

Advanced Configuration

# config_production.yaml
logging:
  level: WARNING
  file_logging:
    enabled: true
    filename: "logs/mcp_server.log"

snowflake:
  # Keep true unless the connecting Snowflake role is itself read-only.
  read_only: true
  default_query_limit: 5000
  max_query_limit: 100000
  statement_timeout_seconds: 120
  connection_reuse: true

security:
  rate_limit:
    enabled: true
    max_calls: 60
    window_seconds: 60
  notes:
    max_count: 100
    max_content_length: 10000

mcp:
  experimental_features:
    resource_subscriptions: true

Debugging and Troubleshooting

Enable Debug Logging:

# Method 1: Environment variable
export LOG_LEVEL=DEBUG
python -m simple_snowflake_mcp

# Method 2: Custom config file
export CONFIG_FILE=config_debug.yaml
python -m simple_snowflake_mcp

Common Issues:

• Connection errors: Check your Snowflake credentials and network connectivity

• Permission errors: Ensure your user has appropriate Snowflake privileges

• Query limits: Adjust default_query_limit in config.yaml for large result sets

• MCP compatibility: Update to latest MCP client version for full feature support