Snowflake Automation

SkillDatabases & data

Snowflake Automation connects your AI to your Snowflake data warehouse so it can explore your data and run SQL for you. Once it is added, you can ask your AI to list what you have, create tables, and update data without writing every query yourself.

Instructions available. Your AI can read the instructions. Execution depends on the setup they require.

After adding it, ask your AI to list the databases and tables in your Snowflake warehouse to see what is there. Then try a query, a new table, or a data update in plain language.

Then ask your AI: use the Snowflake Automation skill

What your AI can do with it

  • List databases, schemas, and tables in your Snowflake warehouse
  • Run SQL queries against your data
  • Create new tables
  • Update existing data
  • Manage your data workflows

What this skill tells your AI

The instructions your AI receives, as published by composio-community/awesome-codex-skills in composio-skills/snowflake-automation/SKILL.md and read by ahel’s review.

Automate your Snowflake data warehouse workflows -- discover databases, browse schemas and tables, execute arbitrary SQL (SELECT, DDL, DML), and integrate Snowflake data operations into cross-app pipelines.

Toolkit docs: composio.dev/toolkits/snowflake


Setup

  1. Add the Composio MCP server to your client: https://rube.app/mcp
  2. Connect your Snowflake account when prompted (account credentials or key-pair authentication)
  3. Start using the workflows below

Core Workflows

1. List Databases

Use SNOWFLAKE_SHOW_DATABASES to discover available databases with optional filtering and Time Travel support.

Tool: SNOWFLAKE_SHOW_DATABASES
Inputs:
  - like_pattern: string (SQL wildcard, e.g., "%test%") -- case-insensitive
  - starts_with: string (e.g., "PROD") -- case-sensitive
  - limit: integer (max 10000)
  - history: boolean (include dropped databases within Time Travel retention)
  - terse: boolean (return subset of columns: created_on, name, kind, database_name, schema_name)
  - role: string (role to use for execution)
  - warehouse: string (optional, not required for SHOW DATABASES)
  - timeout: integer (seconds)

2. Browse Schemas

Use SNOWFLAKE_SHOW_SCHEMAS to list schemas within a database or across the account.

Tool: SNOWFLAKE_SHOW_SCHEMAS
Inputs:
  - database: string (database context)
  - in_scope: "ACCOUNT" | "DATABASE" | "<specific_database_name>"
  - like_pattern: string (SQL wildcard filter)
  - starts_with: string (case-sensitive prefix)
  - limit: integer (max 10000)
  - history: boolean (include dropped schemas)
  - terse: boolean (subset columns only)
  - role, warehouse, timeout: string/integer (optional)

3. List Tables

Use SNOWFLAKE_SHOW_TABLES to discover tables with metadata including row counts, sizes, and clustering keys.

Tool: SNOWFLAKE_SHOW_TABLES
Inputs:
  - database: string (database context)
  - schema: string (schema context)
  - in_scope: "ACCOUNT" | "DATABASE" | "SCHEMA" | "<specific_name>"
  - like_pattern: string (e.g., "%customer%")
  - starts_with: string (e.g., "FACT", "DIM", "TEMP")
  - limit: integer (max 10000)
  - history: boolean (include dropped tables)
  - terse: boolean (subset columns only)
  - role, warehouse, timeout: string/integer (optional)

4. Execute SQL Statements

Use SNOWFLAKE_EXECUTE_SQL for SELECT queries, DDL (CREATE/ALTER/DROP), and DML (INSERT/UPDATE/DELETE) with parameterized bindings.

Tool: SNOWFLAKE_EXECUTE_SQL
Inputs:
  - statement: string (required) -- SQL statement(s), semicolon-separated for multi-statement
  - database: string (case-sensitive, falls back to DEFAULT_NAMESPACE)
  - schema_name: string (case-sensitive)
  - warehouse: string (case-sensitive, required for compute-bound queries)
  - role: string (case-sensitive, falls back to DEFAULT_ROLE)
  - bindings: object (parameterized query values to prevent SQL injection)
  - parameters: object (Snowflake session-level parameters)
  - timeout: integer (seconds; 0 = max 604800s)

Examples:

  • "SELECT * FROM my_table LIMIT 100;"
  • "CREATE TABLE test (id INT, name STRING);"
  • "ALTER SESSION SET QUERY_TAG='mytag'; SELECT COUNT(*) FROM my_table;"

Known Pitfalls

PitfallDetail
Case sensitivityDatabase, schema, warehouse, and role names are case-sensitive in SNOWFLAKE_EXECUTE_SQL.
Warehouse required for computeSELECT and DML queries require a running warehouse. SHOW commands do not.
Multi-statement executionMultiple statements separated by semicolons execute in sequence automatically.
SQL injection preventionAlways use the bindings parameter for user-supplied values to prevent injection attacks.
Pagination with LIMITSHOW commands support limit (max 10000) and from_name for cursor-based pagination.
Time TravelSet history: true to include dropped objects still within the retention period.

Quick Reference

Tool SlugDescription
SNOWFLAKE_SHOW_DATABASESList databases with filtering and Time Travel support
SNOWFLAKE_SHOW_SCHEMASList schemas within a database or account-wide
SNOWFLAKE_SHOW_TABLESList tables with metadata (row count, size, clustering)
SNOWFLAKE_EXECUTE_SQLExecute SQL: SELECT, DDL, DML with parameterized bindings

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Item type
skill
Key
snowflake-automation
Source
github.com/composio-community/awesome-codex-skills