Usage Examples

These examples show real conversations you can have with Claude or ChatGPT once the CorralData integration is connected.

Goal: Understand your database structure and pull a specific metric.

You: What schemas and tables do I have available?

Claude/ChatGPT calls list_schemas and list_tables to map out your data model and returns a summary.

You: Describe the appointments and providers tables

Claude/ChatGPT calls describe_tables to retrieve column names, types, and relationships for both tables at once.

You: How are those two tables related?

Claude/ChatGPT calls get_relationships filtered to those tables and shows the foreign key connections.

You: Write a query to show total appointment revenue by provider for the last 30 days, ordered by highest first

Claude/ChatGPT uses the schema context to write accurate SQL and executes it with execute_sql, returning the results in a table.

Goal: Create a new board with widgets to compare performance across locations.

You: Create a new board called "Location Performance"

Claude/ChatGPT calls create_board and returns the new board with its URL.

You: Add a KPI widget showing total revenue this month across all locations

Claude/ChatGPT writes the SQL, validates it with validate_widget_query, then calls create_widget with a KPI chart type.

You: Now add a bar chart showing revenue by location

Claude/ChatGPT creates a bar chart widget, placing it below the KPI.

You: Add a location filter so users can drill into a specific practice

Claude/ChatGPT calls create_board_filter to add an interactive filter that connects to all widgets on the board.

Goal: Review what's on an existing board and fix an issue.

You: Show me all my boards

Claude/ChatGPT calls list_boards and presents a summary with names and URLs.

You: What widgets are on the "Monthly Operations" board?

Claude/ChatGPT calls get_board then list_widgets to show all widgets with their types and queries.

You: The "Avg Ticket Value" widget looks off. Show me its query

Claude/ChatGPT calls get_widget to retrieve the full widget configuration and SQL.

You: It's including voided appointments — fix the query to exclude those

Claude/ChatGPT updates the SQL, validates it with validate_widget_query, then calls update_widget to save the fix.

Goal: Use natural language to dig into a performance issue.

You: I need to understand why our botox revenue dropped last month. What tables do we have related to treatments or services?

Claude/ChatGPT calls search_tables with relevant keywords and returns matching tables.

You: Describe those tables — I need to understand the columns

Claude/ChatGPT calls describe_tables, showing columns, types, and relationships.

You: What are the possible values in the treatment_category column?

Claude/ChatGPT calls get_column_values to retrieve distinct values so filters will be accurate.

You: Write a query comparing botox appointment volume and revenue month-over-month for the last 6 months

Claude/ChatGPT writes and executes the query with execute_sql, returning a table you can analyze directly in the conversation.

Last updated 7 days ago

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