Snowflake MCP Server
[](https://mseep.ai/app/isaacwasserman-mcp-snowflake-server)
# Snowflake MCP Server
[](https://smithery.ai/server/mcp_snowflake_server) [](https://pypi.org/project/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.
---
## 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](https://smithery.ai/server/mcp_snowflake_server):
```bash
npx -y @smithery/cli install mcp_snowflake_server --client claude
```
---
### Installing via UVX
```json
"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](https://claude.ai/download)
2. Install `uv`:
```bash
curl -LsSf https://astral.sh/uv/install.sh | sh
```
3. Create a `.env` file with your Snowflake credentials:
```bash
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:
```bash
uv --directory /absolute/path/to/mcp_snowflake_server run mcp_snowflake_server
```
6. Add the server to your `claude_desktop_config.json`:
```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
TDQS
Scored across 7 tools
Each tool has a clearly distinct purpose with no overlap: append_insight handles data insights, describe_table provides schema details, fetch_violation_videos retrieves video media, list_databases/schemas/tables enumerate database objects, and read_query executes queries. The tools are well-separated by function and target resources.
All tools follow a consistent verb_noun naming pattern (e.g., append_insight, describe_table, fetch_violation_videos, list_databases, list_schemas, list_tables, read_query). The naming is uniform, predictable, and uses snake_case throughout without any deviations.
With 7 tools, the server is well-scoped for Snowflake database operations. The count is appropriate, covering core functions like listing databases/schemas/tables, describing tables, executing queries, and adding insights, without being too sparse or bloated.
The toolset provides good coverage for Snowflake database interactions, including listing, describing, and querying. However, there are minor gaps such as lacking tools for creating or modifying database objects (e.g., create_table, update_table) or handling transactions, which agents might need to work around.