databricks_workspace_status

Get a comprehensive status overview of the Databricks workspace.

SERVERDatabricks MCP Server SOURCEpypi:databricks-sdk-mcp

Low RISK CLASS

Category Read

Parameters 00 required

Recommended Allowedsee the rule below

Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/io-github-pramodbhatofficial-databricks-sdk-mcp/databricks-workspace-status.md

WHAT IT DOES

What databricks_workspace_status does on Databricks MCP Server

AI agents call databricks_workspace_status 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.

RISK

Why databricks_workspace_status is rated Low

This tool retrieves information about the workspace's current state. There are no side effects, no data modification, no code execution, and no destructive operations. It is a pure read operation that gathers and reports existing information.

From the tool's definition Tool name includes 'status' and description states 'Get a comprehensive status overview' — both indicate retrieval/query of workspace state with no modification.

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs databricks_workspace_status 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_workspace_status, this is the rule to start with:

databricks_workspace_status Allowed

databricks_workspace_status is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

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

ALLOW ONLY 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_workspace_status call is checked against it from then on.

FAQ

Questions about databricks_workspace_status

What does the databricks_workspace_status tool do? +

Get a comprehensive status overview of the Databricks workspace. It is categorised as a Read tool in the Databricks MCP Server MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on databricks_workspace_status? +

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

databricks_workspace_status is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit databricks_workspace_status? +

Yes. Add a rate_limit block to the databricks_workspace_status 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_workspace_status completely? +

Set action: deny in the PolicyLayer policy for databricks_workspace_status. 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_workspace_status? +

databricks_workspace_status 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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