Query Snowflake Data and Access Schema Context
An MCP server for Snowflake - query data, explore schema, and accumulate insights, with write access opt-in.
Why it matters
Execute SQL queries against Snowflake databases to retrieve data and access schema context. This asset enables structured data interaction and analytics.
Outcomes
What it gets done
Execute SQL SELECT, INSERT, UPDATE, and DELETE queries.
Retrieve database schema, table structures, and metadata.
Index and access analytics data and schema summaries as resources.
Manage Snowflake connections with various authentication methods.
Install
Add it to your toolbox
Run in your project directory:
curl -fsSL https://spark.entire.vc/get/vb-snowflake | bash Capabilities
Tools your agent gets
Execute SELECT queries to read data from the database
Execute INSERT, UPDATE, or DELETE queries (requires --allow-write flag)
Create new tables in the database (requires --allow-write flag)
List all databases in the Snowflake instance
List all schemas in a specific database
List all tables in a specific database and schema
View column information for a specific table
Add new analytics data to the insights resource
Overview
Snowflake MCP Server
This MCP server exposes Snowflake SQL querying, schema introspection, and a running insights memo, with write operations (INSERT/UPDATE/DELETE/CREATE TABLE) opt-in via --allow-write. Use it when an AI assistant needs to query Snowflake or explore its schema. Leave write access off (the default) for read-only analysis.
What it does
An MCP server providing Snowflake database interaction, running SQL queries via tools and exposing data insights and schema context as resources. Query tools: read_query executes SELECT statements; write_query (only enabled with --allow-write) executes INSERT/UPDATE/DELETE; create_table (also --allow-write only) runs CREATE TABLE statements. Schema tools: list_databases, list_schemas (given a database), list_tables (given a database and schema), and describe_table (given a fully-qualified database.schema.table name, returning column names, types, nullability, defaults, and comments). An analysis tool, append_insight, adds a data insight discovered during analysis to a continuously updated memo://insights resource, which aggregates all appended insights automatically. If prefetching is enabled, per-table schema summaries (columns and comments) are also exposed as individual context://table/{table_name} resources. Write operations are disabled by default and must be explicitly opted into via --allow-write, and specific databases, schemas, or tables can be excluded from server access via configured exclusion patterns.
When to use - and when NOT to
Use it when an AI assistant needs to query Snowflake data, explore database/schema/table structure, or accumulate discovered insights into a persistent memo during analysis. Write operations (INSERT/UPDATE/DELETE/CREATE TABLE) are off by default and require explicitly passing --allow-write - leave this off for read-only analysis use cases to avoid unintended data modification.
Capabilities
Schema introspection forms a strict drill-down chain - list_databases feeds the database name into list_schemas, whose output feeds list_tables, whose output feeds describe_table - so an assistant with no prior knowledge of the account's structure can walk from nothing down to a single table's column definitions using only the outputs of each prior call.
How to install
npx -y @smithery/cli install mcp_snowflake_server --client claude
Or via uvx with individual connection parameters (--account, --warehouse, --user, --password, --role, --database, --schema, optionally --private_key_path, --allow_write, --log_dir, --log_level, --exclude_tools), or the recommended TOML-based configuration pointing --connections-file at a snowflake_connections.toml file and selecting a --connection-name (allowing multiple named environments like production/staging/development in one client config). Local installation uses uv, a .env file with SNOWFLAKE_* credentials including a private-key path for key-pair auth (or SNOWFLAKE_AUTHENTICATOR=externalbrowser for browser-based auth instead), and an optional runtime_config.json for exclusion patterns, verified with a local test run before wiring the server into claude_desktop_config.json.
Who it's for
Data analysts and engineers who want to query Snowflake, explore its schema, and accumulate analysis insights conversationally through Claude Desktop, with write access opt-in and off by default for safety. Distributed under the MIT License, with its own security posture reviewed under the MseeP.ai security assessment program.
Source README
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 theappend_insighttool.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
ExecuteSELECTqueries to read data from the database.
Input:query(string): TheSELECTSQL query to execute
Returns: Query results as array of objects
write_query(enabled only with--allow-write)
ExecuteINSERT,UPDATE, orDELETEqueries.
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 TABLESQL statement
Returns: Confirmation of table creation
Schema Tools
list_databases
List all databases in the Snowflake instance.
Returns: Array of database nameslist_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 databaseschema(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 ofmemo://insightsresource
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
Traditional Configuration (Individual Parameters)
"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: "--private_key_path", "your_private_key_absolute_path"
// 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}"]
]
}
}
TOML Configuration (Recommended)
"mcpServers": {
"snowflake_production": {
"command": "uvx",
"args": [
"--python=3.12",
"mcp_snowflake_server",
"--connections-file", "/path/to/snowflake_connections.toml",
"--connection-name", "production"
// 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}"]
]
},
"snowflake_staging": {
"command": "uvx",
"args": [
"--python=3.12",
"mcp_snowflake_server",
"--connections-file", "/path/to/snowflake_connections.toml",
"--connection-name", "staging"
]
}
}
Installing Locally
Install Claude AI Desktop App
Install
uv:
curl -LsSf https://astral.sh/uv/install.sh | sh
- Create a
.envfile 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"
SNOWFLAKE_PASSWORD="xxx"
SNOWFLAKE_PRIVATE_KEY_PATH=/absolute/path/key.p8
# Alternatively, use external browser authentication:
# SNOWFLAKE_AUTHENTICATOR="externalbrowser"
[Optional] Modify
runtime_config.jsonto set exclusion patterns for databases, schemas, or tables.Test locally:
uv --directory /absolute/path/to/mcp_snowflake_server run mcp_snowflake_server
- Add the server to your
claude_desktop_config.json:
Traditional Configuration (Using Environment Variables)
"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}"]
]
}
}
TOML Configuration (Recommended)
"mcpServers": {
"snowflake_local": {
"command": "/absolute/path/to/uv",
"args": [
"--python=3.12",
"--directory", "/absolute/path/to/mcp_snowflake_server",
"run", "mcp_snowflake_server",
"--connections-file", "/absolute/path/to/snowflake_connections.toml",
"--connection-name", "development"
// 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_insighttool updates thememo://insightsresource dynamically.
FAQ
Common questions
Discussion
Questions & comments · 0
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