databricks_delete_share

A destructive tool on the Databricks MCP server.

SERVERDatabricks MCP Server SOURCEpypi:databricks-sdk-mcp

Critical RISK CLASS

Category Destructive

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-share.md

WHAT IT DOES

What databricks_delete_share does on Databricks MCP Server

AI agents call databricks_delete_share 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_share is rated Critical

The 'delete' action is inherently irreversible and falls squarely into the Destructive category. While the description is empty (lowering confidence slightly), the tool name itself provides sufficient evidence. In a Databricks environment, deleting a share would revoke access to shared data assets and remove the sharing relationship, which is an action that cannot be easily reversed without manual recreation.

From the tool's definition Tool name 'databricks_delete_share' contains the verb 'delete', which is a destructive operation. The Databricks context indicates this operates on data sharing constructs (shares are mechanisms for sharing data/tables across workspaces).

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs databricks_delete_share 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_share, this is the rule to start with:

databricks_delete_share Hidden

databricks_delete_share 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_share"
  ]
}

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_share call is checked against it from then on.

FAQ

Questions about databricks_delete_share

What does the databricks_delete_share tool do? +

databricks_delete_share is a destructive tool on the Databricks MCP Server MCP server. 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_share? +

Register the Databricks MCP Server MCP server in PolicyLayer and add a rule for databricks_delete_share: 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_share? +

databricks_delete_share 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_share? +

Yes. Add a rate_limit block to the databricks_delete_share 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_share completely? +

Set action: deny in the PolicyLayer policy for databricks_delete_share. 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_share? +

databricks_delete_share 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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