databricks_query_vector_search_index

What databricks_query_vector_search_index does on Databricks MCP Server

AI agents call databricks_query_vector_search_index to retrieve information from Databricks MCP Server without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.

Why databricks_query_vector_search_index is rated Low

Query operations are classified as Read operations since they retrieve data without side effects. Though confidence is moderate due to the empty description, the naming convention strongly indicates a retrieval operation. If this tool actually performs searches across vector indices in Databricks, the primary effect would be data retrieval with no side effects on the underlying data or system state.

From the tool's definition Tool name contains 'query' which typically indicates data retrieval. No description provided, but the suffix 'vector_search_index' suggests it queries a search index for vector data rather than modifying or executing operations.

The rule that runs databricks_query_vector_search_index safely

PolicyLayer is an MCP gateway: it sits between your AI agents and Databricks MCP Server, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For databricks_query_vector_search_index, this is the rule to start with:

{
  "version": "1",
  "default": "deny",
  "tools": {
    "databricks_query_vector_search_index": {}
  }
}

Questions about databricks_query_vector_search_index