databricks_execute_sql
A execute tool on the Databricks MCP server.
This record as markdown: /tools/io-github-pramodbhatofficial-databricks-sdk-mcp/databricks-execute-sql.md
What databricks_execute_sql does on Databricks MCP Server
AI agents invoke databricks_execute_sql to trigger actions in Databricks MCP Server. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call: builds kicked off, notifications sent, workflows started.
Why databricks_execute_sql is rated High
SQL execution tools can run SELECT, INSERT, UPDATE, or potentially DELETE/DROP statements depending on permissions. Without a description limiting scope (e.g., 'read-only queries'), this must be treated as Execute rather than Read. The blast radius is high because an AI could inadvertently run destructive queries, modify data, or corrupt schemas.
From the tool's definition Tool name 'databricks_execute_sql' indicates execution of SQL statements against a Databricks database. The 'execute' verb combined with SQL context strongly suggests arbitrary code/query execution capability.
Attacks that exploit this kind of access
The rule that runs databricks_execute_sql 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_execute_sql, this is the rule to start with:
databricks_execute_sql stays usable, but rate-capped: a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Databricks MCP Server, apply this rule, and every databricks_execute_sql call is checked against it from then on.
Questions about databricks_execute_sql
databricks_execute_sql is a execute tool on the Databricks MCP Server MCP server. It is categorised as a Execute tool in the Databricks MCP Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Databricks MCP Server MCP server in PolicyLayer and add a rule for databricks_execute_sql: 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.
databricks_execute_sql is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the databricks_execute_sql 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.
Set action: deny in the PolicyLayer policy for databricks_execute_sql. 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.
databricks_execute_sql 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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