databricks_stop_app
A execute tool on the Databricks MCP server.
This record as markdown: /tools/io-github-pramodbhatofficial-databricks-sdk-mcp/databricks-stop-app.md
What databricks_stop_app does on Databricks MCP Server
AI agents invoke databricks_stop_app 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_stop_app is rated High
Stopping an app is an Execute action—it triggers an operation whose effects depend on which app is targeted. While not destructive (reversible by restart) or write-based (doesn't modify data), it actively halts a service/process. In a Databricks multi-tenant environment, misuse could disrupt other users' workflows.
From the tool's definition Tool name 'databricks_stop_app' indicates stopping/terminating an application instance, and context of Databricks tools with operations like 'cancel_run', 'cancel_statement' suggests it triggers an external operation. Description is empty, reducing certainty.
Attacks that exploit this kind of access
The rule that runs databricks_stop_app 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_stop_app, this is the rule to start with:
databricks_stop_app 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_stop_app call is checked against it from then on.
Questions about databricks_stop_app
databricks_stop_app 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_stop_app: 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_stop_app 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_stop_app 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_stop_app. 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_stop_app 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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