databricks_start_app
A execute tool on the Databricks MCP server.
This record as markdown: /tools/io-github-pramodbhatofficial-databricks-sdk-mcp/databricks-start-app.md
What databricks_start_app does on Databricks MCP Server
AI agents invoke databricks_start_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_start_app is rated High
Starting an application is an Execute action—it triggers an external operation whose effects depend on which app is started and its configuration. While not irreversible (apps can be stopped), it initiates computational or service operations that may consume resources or interact with external systems.
From the tool's definition Tool name 'databricks_start_app' indicates starting/launching an application. The sibling tools on this server (databricks_create_app, databricks_cancel_run, databricks_create_cluster) establish this is a Databricks operations server where 'start' actions…
Attacks that exploit this kind of access
The rule that runs databricks_start_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_start_app, this is the rule to start with:
databricks_start_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_start_app call is checked against it from then on.
Questions about databricks_start_app
databricks_start_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_start_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_start_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_start_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_start_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_start_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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