List all tables and views in the exposed PostgreSQL schema. Returns table names, types (table/view), and basic metadata. Essential for discovering available data sources and understanding database structure.

Get detailed schema information about a specific table including column names, data types, nullability, defaults, and constraints. Essential for understanding table structure before querying or modifying data.

Retrieve sample rows from a table for quick data exploration. Returns a limited number of rows to understand data format, content, and structure without reading the entire table. Use this to preview data before writing complex queries.

Search for tables and views by name pattern across the database. Useful for finding specific datasets when you don't know their exact location or name. Returns matching table names and types.

Get the total number of rows in a table quickly without fetching data. Uses PostgREST's count header for efficient counting. Useful for understanding table size and data volume.

Query a table with flexible filtering, sorting, column selection, and pagination. This is the main data retrieval tool. Supports PostgREST's powerful filter operators (eq, gt, gte, lt, lte, like, ilike, in, is, etc.). Use this for most data retrieval needs.

Perform full-text search on text columns using PostgreSQL's text search capabilities. Supports different search types (plain, phrase, websearch) and multiple languages. Useful for finding records by keywords or phrases in text fields.

Execute complex queries with OR, AND, NOT logic. Allows combining multiple conditions in flexible ways. For example, find users who are either under 18 OR over 65, or students who have grade >= 90 AND (age is 14 OR age is NOT between 11 and 17).

Query tables with JSON/JSONB columns and extract specific fields. Use arrow operators to access nested JSON data: -> for JSON objects, ->> for text values. Supports filtering and selecting JSON paths. Example: data->>'email' or data->phones->0->>'number'

Get unique values from a column. Useful for discovering what values exist in a column, building filters, or understanding data distribution. Automatically removes duplicates and sorts results.