discover-tools

To discover available tools and resources in a Databricks workspace, you can run a resource discovery skill that queries and inventories UC Functions, Tables, Vector Search Indexes, Genie Spaces, and MCP servers.

Yes, you can list Databricks UC Functions and MCP servers for agent development by executing a workspace tool discovery process that identifies all connectable resources before you write agent code.

You can filter discovered Databricks resources by catalog and schema using the discovery tool's filtering parameters, which narrow the inventory query to specific database scopes and output results in JSON or Markdown formats.

The best way to inventory Vector Search Indexes and Genie Spaces before building an agent is to run a workspace resource discovery process that scans the environment and lists all available data interaction endpoints.

Yes, Databricks tool discovery supports JSON and Markdown output formats, allowing you to export the inventory of UC Functions, Tables, Vector Search Indexes, Genie Spaces, and MCP servers in your preferred structure.

You need to discover Databricks workspace resources before writing agent code to identify existing UC Functions and MCP servers that can be leveraged, saving development time and facilitating seamless data interaction.