databricks_create_query

A write tool on the Databricks MCP server.

SERVERDatabricks MCP Server SOURCEpypi:databricks-sdk-mcp

Medium RISK CLASS

Category Write

Parameters 00 required

Recommended Rate-limitedsee the rule below

Registry record Grade F, identity unverified Pull the record →

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

WHAT IT DOES

What databricks_create_query does on Databricks MCP Server

AI agents use databricks_create_query to create or update resources in Databricks MCP Server, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Databricks MCP Server environment.

RISK

Why databricks_create_query is rated Medium

The 'create_' prefix combined with context from sibling tools strongly indicates this creates a new query resource in Databricks, which is a reversible Write operation. Confidence is not higher due to the empty description. If this tool executes arbitrary SQL (like sibling query tools), it could be Execute instead, but 'create_query' most naturally means storing/defining a query object rather than executing it.

From the tool's definition Tool name 'databricks_create_query' indicates creation of a query object in Databricks. Sibling tools (create_catalog, create_alert, create_app) all perform Write operations.

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs databricks_create_query 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_create_query, this is the rule to start with:

databricks_create_query Rate-limited

databricks_create_query stays usable, but capped: an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "databricks_create_query": {
      "limits": [
        {
          "counter": "databricks_create_query_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

LIMIT 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_create_query call is checked against it from then on.

FAQ

Questions about databricks_create_query

What does the databricks_create_query tool do? +

databricks_create_query is a write tool on the Databricks MCP Server MCP server. It is categorised as a Write tool in the Databricks MCP Server MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on databricks_create_query? +

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

databricks_create_query is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit databricks_create_query? +

Yes. Add a rate_limit block to the databricks_create_query 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_create_query completely? +

Set action: deny in the PolicyLayer policy for databricks_create_query. 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_create_query? +

databricks_create_query 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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