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. The server exposes comprehensive MCP tools to interact
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npx mdskills install YannBrrd/simple-snowflake-mcpProduction-ready Snowflake MCP server with comprehensive toolset, YAML configuration, and Docker support
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.
The server exposes comprehensive MCP tools to interact with Snowflake:
Core Database Operations:
read_only is false), result in markdown formatDiscovery and Metadata:
Advanced Operations:
The server now includes a comprehensive YAML-based configuration system that allows you to customize all aspects of the server behavior.
Create a config.yaml file in your project root:
# Logging Configuration
logging:
level: INFO # DEBUG, INFO, WARNING, ERROR, CRITICAL
format: "%(asctime)s - %(name)s - %(levelname)s - %(message)s"
file_logging: false # Set to true to enable file logging
log_file: "mcp_server.log" # Log file path (when file_logging is true)
# Server Configuration
server:
name: "simple_snowflake_mcp"
version: "0.2.0"
description: "Enhanced Snowflake MCP Server with full protocol compliance"
connection_timeout: 30
read_only: true # Set to false to allow write operations
# Snowflake Configuration
snowflake:
read_only: true
default_query_limit: 1000
max_query_limit: 50000
# 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
limits:
max_prompt_length: 10000
max_resource_size: 1048576 # 1MB
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 values are resolved in this order (highest to lowest priority):
LOG_LEVEL, MCP_READ_ONLY)CONFIG_FILE)config.yaml fileuvx (Recommandé)# Installation et exécution directe
uvx simple-snowflake-mcp
# Cloner le repo
git clone https://github.com/YannBrrd/simple_snowflake_mcp
cd simple_snowflake_mcp
# Installer avec uv (crée automatiquement un venv)
uv sync
# Exécuter
uv run simple-snowflake-mcp
# Installer avec les dépendances de développement
uv sync --all-extras
# Lancer les tests
uv run pytest
# Linter avec ruff
uv run ruff check .
uv run ruff format .
On MacOS: ~/Library/Application\ Support/Claude/claude_desktop_config.json
On Windows: %APPDATA%/Claude/claude_desktop_config.json
Development/Unpublished Servers Configuration
"mcpServers": {
"simple_snowflake_mcp": {
"command": "uv",
"args": [
"--directory",
".",
"run",
"simple_snowflake_mcp"
]
}
}
Published Servers Configuration
"mcpServers": {
"simple_snowflake_mcp": {
"command": "uvx",
"args": [
"simple_snowflake_mcp"
]
}
}
Clone the repository
git clone
cd simple_snowflake_mcp
Set up environment variables
cp .env.example .env
# Edit .env with your Snowflake credentials
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
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
The Docker setup includes:
All Snowflake configuration can be set via environment variables:
Required:
SNOWFLAKE_USER: Your Snowflake usernameSNOWFLAKE_PASSWORD: Your Snowflake passwordSNOWFLAKE_ACCOUNT: Your Snowflake account identifierOptional:
SNOWFLAKE_WAREHOUSE: Warehouse nameSNOWFLAKE_DATABASE: Default databaseSNOWFLAKE_SCHEMA: Default schemaMCP_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)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.
# Synchroniser toutes les dépendances (prod + dev)
uv sync --all-extras
# Mettre à jour les dépendances
uv lock --upgrade
# Ajouter une nouvelle dépendance
uv add
# Ajouter une dépendance de dev
uv add --dev
# Build
uv build
# Publier sur PyPI
uv publish --token $UV_PUBLISH_TOKEN
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.
The server exposes an MCP tool execute-snowflake-sql to execute a SQL query on Snowflake and return the result.
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.
Cloner le projet et installer les dépendances
git clone https://github.com/YannBrrd/simple_snowflake_mcp
cd simple_snowflake_mcp
# Installer avec uv (crée automatiquement un venv)
uv sync --all-extras
Configurer l'accès Snowflake
.env.example vers .env et remplir vos credentials :
SNOWFLAKE_USER=...
SNOWFLAKE_PASSWORD=...
SNOWFLAKE_ACCOUNT=...
# SNOWFLAKE_WAREHOUSE Optionnel: Nom du warehouse Snowflake
# SNOWFLAKE_DATABASE Optionnel: Nom de la base par défaut
# SNOWFLAKE_SCHEMA Optionnel: Nom du schéma par défaut
# MCP_READ_ONLY=true|false Optionnel: true/false pour forcer le mode lecture seule
Configurer le serveur (v0.2.0)
config.yaml par défaut au premier lancementconfig.yamlCONFIG_FILE=custom_config.yaml pour spécifier un fichier de configuration différentConfigurer VS Code pour le debugging MCP
.vscode/mcp.json est déjà présent :
{
"servers": {
"simple-snowflake-mcp": {
"type": "stdio",
"command": "uv",
"args": ["run", "simple-snowflake-mcp"]
}
}
}
MCP: Start Server et sélectionner simple-snowflake-mcp.Utilisation
This server now implements comprehensive MCP protocol features:
🔔 Resource Subscriptions
📋 Enhanced Resource Management
⚡ Performance & Reliability
🔧 Development Features
The server advertises these MCP capabilities:
The server exposes comprehensive MCP tools to interact with Snowflake:
Core Database Operations:
Discovery and Metadata:
Advanced Analytics:
For detailed usage examples and parameter schemas, see the MCP protocol documentation.
# Execute a simple query
{
"name": "execute-query",
"arguments": {
"query": "SELECT CURRENT_TIMESTAMP;",
"format": "markdown"
}
}
# List all databases
{
"name": "list-databases",
"arguments": {}
}
# config_production.yaml
logging:
level: WARNING
file_logging: true
log_file: "/var/log/mcp_server.log"
server:
read_only: false # Allow write operations
snowflake:
default_query_limit: 5000
max_query_limit: 100000
mcp:
experimental_features:
resource_subscriptions: true
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:
default_query_limit in config.yaml for large result setsInstall via CLI
npx mdskills install YannBrrd/simple-snowflake-mcpSimple Snowflake MCP server is a free, open-source AI agent skill. 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. The server exposes comprehensive MCP tools to interact
Install Simple Snowflake MCP server with a single command:
npx mdskills install YannBrrd/simple-snowflake-mcpThis downloads the skill files into your project and your AI agent picks them up automatically.
Simple Snowflake MCP server works with Claude Code, Claude Desktop, Cursor, Vscode Copilot, Windsurf, Continue Dev, Gemini Cli, Amp, Roo Code, Goose. Skills use the open SKILL.md format which is compatible with any AI coding agent that reads markdown instructions.