show_tables
Explore Snowflake databases, schemas, and tables with pattern-based filtering. Use database_pattern, schema_pattern, and table_pattern to narrow results or get a summary when the tree is large.
Instructions
Browse databases, schemas, and tables using pattern-based filtering.
USE THIS WHEN: You want to explore what databases/schemas exist, or need to filter by exact patterns.
Like SQL's: SHOW TABLES IN database LIKE 'pattern'
RETURNS (small result): hierarchical tree
- database → schema → list of tables
RETURNS (broad result): when the matching tree is too large to return inline
(e.g. show_tables() with no filter, or a broad database_pattern matching tens
of thousands of tables), the COMPLETE tree is written to a temp `.json` file
and the response is instead a compact summary built to help you NARROW:
`total_tables`, `total_schemas`, `results_file`, and a bounded breakdown that
adapts to what's left to narrow -- `top_schemas` (db.schema=count) when the
result is a single database, else `top_databases` (db=count) -- each with a
`(+X more ..., Y tables)` tail marker, plus a `spilled` hint.
To act on a spilled result, prefer RE-CALLING show_tables with a tighter
database_pattern/schema_pattern (served from cache, no Snowflake) until it
fits inline. To read results_file directly instead -- it is compact JSON
nested THREE levels deep, `{"DB": {"SCHEMA": ["TABLE", ...]}}` (so table
names are the innermost array, not a key) -- list its schemas WITHOUT loading
every table name into context:
jq -r 'to_entries[]|.key as $d|.value|keys[]|"\($d).\(.)"' <results_file>
or, if jq is unavailable:
python3 -c "import json,sys;d=json.load(open(sys.argv[1]));print(chr(10).join(f'{db}.{s}' for db,sc in d.items() for s in sc))" <results_file>
Mind the nesting depth when counting: `jq '[.[][][]]|length'` counts TABLES
(three flattens to reach the leaf array); `jq '[.[][]]|length'` counts
SCHEMAS. (total_tables/total_schemas in the summary already give both.)
HOW IT WORKS:
- Auto-refreshes cache if expired/empty (requires Snowflake auth on first use)
- Uses cached data if available (no auth needed)
- Pattern matching is case-insensitive substring search
Parameters:
- database_pattern: Filter databases (e.g., "SALES" matches "SALES_DB", "SALES_PROD")
- schema_pattern: Filter schemas (e.g., "PUBLIC")
- table_pattern: Filter tables (e.g., "CUSTOMER" matches "CUSTOMERS", "CUSTOMER_ORDERS")
Examples:
- show_tables() - Browse all databases
- show_tables(database_pattern="SALES") - Only SALES databases
- show_tables(schema_pattern="PUBLIC") - All PUBLIC schemas across databases
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| database_pattern | No | ||
| schema_pattern | No | ||
| table_pattern | No |