databricks_get_app_deployment
A read tool on the Databricks MCP server.
This record as markdown: /tools/io-github-pramodbhatofficial-databricks-sdk-mcp/databricks-get-app-deployment.md
What databricks_get_app_deployment does on Databricks MCP Server
AI agents call databricks_get_app_deployment 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.
Why databricks_get_app_deployment is rated Low
The 'get_' prefix strongly suggests this tool retrieves or queries deployment information about a Databricks app without modifying state. Despite the empty description reducing confidence, the naming convention is a reliable indicator of read-only behavior. Classifying as Read with low severity due to the informational nature of app deployment retrieval.
From the tool's definition Tool name 'get_app_deployment' uses the 'get' verb, which typically indicates a retrieval operation. The description is empty, providing no additional context, which lowers confidence.
Attacks that exploit this kind of access
The rule that runs databricks_get_app_deployment 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_get_app_deployment, this is the rule to start with:
databricks_get_app_deployment is read-only, so it stays allowed. 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_get_app_deployment call is checked against it from then on.
Questions about databricks_get_app_deployment
databricks_get_app_deployment is a read tool on the Databricks MCP Server MCP server. It is categorised as a Read tool in the Databricks MCP Server MCP Server, which means it retrieves data without modifying state.
Register the Databricks MCP Server MCP server in PolicyLayer and add a rule for databricks_get_app_deployment: 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_get_app_deployment is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the databricks_get_app_deployment 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_get_app_deployment. 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_get_app_deployment 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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