databricks_delete_vector_search_endpoint

Delete a vector search endpoint.

SERVERDatabricks MCP Server SOURCEpypi:databricks-sdk-mcp

Critical RISK CLASS

Parameters 00 required

Recommended Hiddensee the rule below

Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/io-github-pramodbhatofficial-databricks-sdk-mcp/databricks-delete-vector-search-endpoint.md

WHAT IT DOES

What databricks_delete_vector_search_endpoint does on Databricks MCP Server

AI agents call databricks_delete_vector_search_endpoint to permanently remove resources in Databricks MCP Server, typically in cleanup and lifecycle workflows. It does its job in a single call, and there is no undo.

RISK

Why databricks_delete_vector_search_endpoint is rated Critical

The tool performs an irreversible destructive action (deletion of a vector search endpoint). In a Databricks environment, endpoints are typically persistent resources that may be serving production workloads or contain indexed vector data. Deletion cannot be undone without manual recreation and re-indexing.

From the tool's definition Tool name explicitly contains 'delete' and description states 'Delete a vector search endpoint' — this is an irreversible deletion operation that removes infrastructure/data without possibility of reversal.

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs databricks_delete_vector_search_endpoint 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_delete_vector_search_endpoint, this is the rule to start with:

databricks_delete_vector_search_endpoint Hidden

databricks_delete_vector_search_endpoint is removed from the agent's tool list entirely, so the agent never calls it. The rest of the server keeps working.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "hide": [
    "databricks_delete_vector_search_endpoint"
  ]
}

RESTRICT THIS TOOL → Instant setup, no code required.

The button opens the PolicyLayer dashboard: create your workspace, connect Databricks MCP Server, apply this rule, and every databricks_delete_vector_search_endpoint call is checked against it from then on.

FAQ

Questions about databricks_delete_vector_search_endpoint

What does the databricks_delete_vector_search_endpoint tool do? +

Delete a vector search endpoint. It is categorised as a Destructive tool in the Databricks MCP Server MCP Server, which means it can permanently delete or destroy data. Block by default and require explicit approval.

How do I enforce a policy on databricks_delete_vector_search_endpoint? +

Register the Databricks MCP Server MCP server in PolicyLayer and add a rule for databricks_delete_vector_search_endpoint: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Databricks MCP Server. Nothing to install.

What risk level is databricks_delete_vector_search_endpoint? +

databricks_delete_vector_search_endpoint is a Destructive tool with critical risk. Critical-risk tools should be blocked by default and only enabled with explicit human approval.

Can I rate-limit databricks_delete_vector_search_endpoint? +

Yes. Add a rate_limit block to the databricks_delete_vector_search_endpoint rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.

How do I block databricks_delete_vector_search_endpoint completely? +

Set action: deny in the PolicyLayer policy for databricks_delete_vector_search_endpoint. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.

What MCP server provides databricks_delete_vector_search_endpoint? +

databricks_delete_vector_search_endpoint is provided by the Databricks MCP Server MCP server (pypi:databricks-sdk-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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