databricks_list_secret_acls
A read tool on the Databricks MCP server.
This record as markdown: /tools/io-github-pramodbhatofficial-databricks-sdk-mcp/databricks-list-secret-acls.md
What databricks_list_secret_acls does on Databricks MCP Server
AI agents call databricks_list_secret_acls 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_list_secret_acls is rated Low
The 'list' operation is a read-only action that retrieves existing ACL (Access Control List) data for secrets. While the tool itself is not destructive or modifying, the medium severity reflects that listing secret ACLs reveals security-sensitive information that could be exploited if an AI agent misuses this capability to enumerate secret access patterns.
From the tool's definition Tool name 'databricks_list_secret_acls' uses the verb 'list', which retrieves information about secret access control lists. The description is empty, but the naming convention strongly indicates a query/retrieval operation with no modification.
Attacks that exploit this kind of access
The rule that runs databricks_list_secret_acls 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_list_secret_acls, this is the rule to start with:
databricks_list_secret_acls 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_list_secret_acls call is checked against it from then on.
Questions about databricks_list_secret_acls
databricks_list_secret_acls 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_list_secret_acls: 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_list_secret_acls 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_list_secret_acls 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_list_secret_acls. 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_list_secret_acls 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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